{"id":5,"date":"2015-08-17T13:51:00","date_gmt":"2015-08-17T13:51:00","guid":{"rendered":"https:\/\/www.bates.edu\/digital-computational-studies\/?page_id=5"},"modified":"2025-09-18T14:59:58","modified_gmt":"2025-09-18T18:59:58","slug":"courses","status":"publish","type":"page","link":"https:\/\/www.bates.edu\/digital-computational-studies\/courses\/","title":{"rendered":"Courses"},"content":{"rendered":"<div class=\"catalog-block catalog-course-listing departmental-course-listing\"><div class=\"catalog-course _full-view\" id=\"course-477\">\n\t\t\t\t\t<h5>DCS 105: Calling Bull: Data Literacy and Information Science<\/h5>\n\t\t\t\t\t<p class=\"course-description\">Our world is rife with misinformation. This course is designed to hone digital citizenship skills. It is about &quot;calling bullshit&quot;: spotting, dissecting, and publicly refuting false claims and inferences based on quantitative, statistical, and computational analysis of data. Students explore case studies in policy and science and dissect the \u201cwho, what, where, when, why, and how\u201d of bullshit propagation. Examples include election misinformation, interpreting health risk, facial recognition algorithms, and science communication. Students practice visualizing data; interpreting scientific claims; and spotting misinformation, fake news, causal fallacies, and statistical traps. In doing so, the course offers an introduction to programming with R for data analysis and visualization.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> [QF], [SR]<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C093, C095<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> None<\/li><li><span class=\"label\">Instructor:<\/span> Carrie Eaton<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+105\" target=\"course-477\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-478\">\n\t\t\t\t\t<h5>DCS 109C: Introduction to Computer Science through Community-Engaged Learning<\/h5>\n\t\t\t\t\t<p class=\"course-description\">This course introduces computer science, computational thinking, and problem-solving through community-engaged learning. Students learn about computing in terms of the representation and manipulation of data, fundamental algorithms, and societal implications of computing. They will learn the fundamentals of computer programming using Python, including conditional statements, iteration, abstraction, testing, modularity, and debugging. Students will work collaboratively with their peers on a community-engaged project.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> [QF]<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C093, C095<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> None<\/li><li><span class=\"label\">Instructor:<\/span> Andy Elliot Ricci<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+109C\" target=\"course-478\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-479\">\n\t\t\t\t\t<h5>DCS 109D: Introduction to Computer Science for Data Analysis<\/h5>\n\t\t\t\t\t<p class=\"course-description\">This course is an introduction to computational thinking and problem solving via programming, designed for students interested in addressing problems in brain research, as well as experimental science more broadly. Students learn fundamentals of computer programming using Python, including basic data structures, flow control structures, functions, recursion, elementary object-oriented programming, and file I\/O, as well as discussion of higher-level concepts including abstraction, modularity, reuse, testing, and debugging. By implementing programs in contexts such as image processing, neural networks, and the analysis of electrical brain activity, students develop an understanding of computational problem solving and gain experience in broadly applicable software development for data analysis. Not open to students who have earned credit for any other <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=DCS109\" data-action=\"result-detail\" data-group=\"code:DCS109\"  class=\"notoffered\">DCS109<\/a> course.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> [QF]<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C093, C095<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> None<\/li><li><span class=\"label\">Instructor:<\/span> Jason Castro<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+109D\" target=\"course-479\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-480\">\n\t\t\t\t\t<h5>DCS 109R: Introduction to Computer Science Using Robots<\/h5>\n\t\t\t\t\t<p class=\"course-description\">This course introduces computer science, computational thinking, and problem-solving in the context of robots. Students learn about computing in terms of the representation and manipulation of data, fundamental algorithms, and societal implications of computing. They will learn the fundamentals of computer programming using Python, including conditional statements, iteration, abstraction, testing, modularity, and debugging. Students will gain an understanding of computational problem solving through implementing programs to control robots and solve robotics problems. Not open to students who have earned credit for any other <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=DCS109\" data-action=\"result-detail\" data-group=\"code:DCS109\"  class=\"notoffered\">DCS109<\/a> course.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> [QF]<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C093, C095<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> None<\/li><li><span class=\"label\">Instructor:<\/span> Andy Elliot Ricci<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+109R\" target=\"course-480\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-481\">\n\t\t\t\t\t<h5>DCS 109S: Introduction to Computer Science for Software Development<\/h5>\n\t\t\t\t\t<p class=\"course-description\">This course (formerly <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=DCS%20109\" data-action=\"result-detail\" data-group=\"code:DCS 109\"  class=\"notoffered\">DCS 109<\/a>) is an introduction to computational thinking and problem solving via an introduction to computer programming, designed for students interested in broadly applying computing and software solutions across a range of disciplines. It considers computing as a discipline of study, exploring the representation and manipulation of data, fundamental algorithms, efficiency, and the limits of computing. Students learn fundamentals of computer programming using Python, including basic data structures, flow control structures, functions, recursion, elementary object-oriented programming, and file I\/O, as well as discussion of higher-level concepts including abstraction, modularity, reuse, testing, and debugging. By implementing programs in contexts such as image processing, voting algorithms, DNA sequence analysis, and simple games, students develop an understanding of computational problem solving and gain experience in broadly applicable software development skills. Not open to students who have earned credit for any other <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=DCS109\" data-action=\"result-detail\" data-group=\"code:DCS109\"  class=\"notoffered\">DCS109<\/a> course.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> [QF]<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C093, C095<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> None<\/li><li><span class=\"label\">Instructor:<\/span> Barry Lawson<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+109S\" target=\"course-481\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-482\">\n\t\t\t\t\t<h5>DCS 109T: Introduction to Computer Science for Text Analysis<\/h5>\n\t\t\t\t\t<p class=\"course-description\">This course (formerly <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=DCS%20111\" data-action=\"result-detail\" data-group=\"code:DCS 111\"  class=\"notoffered\">DCS 111<\/a>) is an introduction to computational thinking and problem solving via programming, designed for students interested in applying computation to the humanities and text analysis. It frames computation as a process of designing systematic solutions to problems; implementing, testing, and verifying those solutions; and making the solutions accessible to other scholars and investigators. Students learn fundamentals of computer programming using Python, including basic data structures, flow control structures, functions, recursion, and elementary object-oriented programming, as well as discussion of higher-level concepts including abstraction, modularity, reuse, testing, and debugging. By the end of the semester, students develop an understanding of computational problem solving and gain experience implementing that problem solving in the context of text analysis. Not open to students who have earned credit for any other <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=DCS109\" data-action=\"result-detail\" data-group=\"code:DCS109\"  class=\"notoffered\">DCS109<\/a> course.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> [QF]<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C093, C095<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> None<\/li><li><span class=\"label\">Instructor:<\/span> Anelise Shrout<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+109T\" target=\"course-482\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-483\">\n\t\t\t\t\t<h5>DCS 117: Introduction to Data Science and Statistics<\/h5>\n\t\t\t\t\t<p class=\"course-description\">This course offers an introduction to data science through data visualization. Through hands-on assignments, students will develop their skills in data cleaning, analysis, and visualization using the R programming language and Github for version control. In the course students will learn to calculate and describe data using descriptive statistics and how to create a range of data visualizations to explore variation and covariation in data.  Students will also learn to critique and reflect on data visualizations encountered in everyday life. No prior experience in data science or programming is necessary, making this course accessible to all students interested in exploring the dynamic field of data science. Not open to students who have received credit for <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=DCS%20210\" data-action=\"result-detail\" data-group=\"code:DCS 210\"  class=\"notoffered\">DCS 210<\/a>.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> [QF]<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C093, C095<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> MATH 117<\/li><li><span class=\"label\">Instructor:<\/span> Laurie Baker<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+117\" target=\"course-483\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-484\">\n\t\t\t\t\t<h5>DCS 170: Introduction to Digital Media<\/h5>\n\t\t\t\t\t<p class=\"course-description\">This introductory course explores the ever-evolving world of digital media in the performing arts, where technology, creativity, and communities converge. Students will be trained on the holistic and collaborative process from storyboarding to technical execution, specifically as it relates to live entertainment. We\u2019ll examine the history, current landscape, and emerging technologies in projection and video design.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> [CP]<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C028, C093<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> THEA 170<\/li><li><span class=\"label\">Instructor:<\/span> Courtney Smith<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+170\" target=\"course-484\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-485\">\n\t\t\t\t\t<h5>DCS 204: Archives, Data, and Analysis<\/h5>\n\t\t\t\t\t<p class=\"course-description\">The computational humanities comprise a fast-growing and exciting field that is changing the way scholars work and think. This course provides an opportunity for students with some experience with programming to immerse themselves in semester-long projects in digital environments, moving from &quot;analog&quot; archives, through data structuring, and quantitative analysis, and culminating with a project that makes both the humanities and quantitative analyses legible for people from  diverse backgrounds. Prerequisite(s): one 100-level digital and computational studies course.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> [HS], [SR]<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C093<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> AMST 205<\/li><li><span class=\"label\">Instructor:<\/span> Anelise Shrout<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+204\" target=\"course-485\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-486\">\n\t\t\t\t\t<h5>DCS 206: The Past, Present, and Possible Dystopian Future of Computing<\/h5>\n\t\t\t\t\t<p class=\"course-description\">In this course students examine the history, present, and possible future of computing through film and literature, focusing on questions at the intersection of computing, digital studies, and communication: Who are the stakeholders and participants in this intersectional area? What are the uses and abuses of data and computing in society? Who has the power of technology and who does not, and what are the consequences of that power? Recommended background: Prior critical-studies-oriented digital and computational studies course or similar course work in Africana, American studies, Latin American and Latinx studies and\/or gender and sexuality studies.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> [CP]<\/li><li><span class=\"label\">Writing Credit:<\/span> [W2]<\/li><li><span class=\"label\">Concentration(s):<\/span> C037, C093<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> None<\/li><li><span class=\"label\">Instructor:<\/span> Carrie Eaton<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+206\" target=\"course-486\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-487\">\n\t\t\t\t\t<h5>DCS 211: Computing for Insight<\/h5>\n\t\t\t\t\t<p class=\"course-description\">Building on any of the Introduction to Computer Science courses, this course explores the practical application of software composition as a bridge to other disciplines. Students continue to develop programming and problem-solving skills, with the clear purpose of providing insight to inquiry in other fields that is made possible by modern computing, software composition, and libraries. The course includes study of additional data structures and algorithms; bash scripting for system administration and task automation; data harvesting, analysis, and visualization; machine learning; version control systems; and considerations of human- and machine-efficiency. As a final course project, students design, implement, and assess a computing project of their choosing. Prerequisite(s): Any <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=DCS109\" data-action=\"result-detail\" data-group=\"code:DCS109\"  class=\"notoffered\">DCS109<\/a> course.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> [QF]<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C093, C095<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> None<\/li><li><span class=\"label\">Instructor:<\/span> Barry Lawson<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+211\" target=\"course-487\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-488\">\n\t\t\t\t\t<h5>DCS 212: Digital History Methods<\/h5>\n\t\t\t\t\t<p class=\"course-description\">Through a combination of analytical, experiential, and collaborative exercises, students merge traditional historical methods with digital tools to explore new useful methodologies for collecting, analyzing, and disseminating historical knowledge. They develop technical and theoretical proficiency within the broader field of digital humanities. They engage digital tools and resources to rethink old historical questions. They develop with new questions that can be investigated only through digital practice. They contemplate avenues for collaboration between historical research and public communities. Finally, they weigh the practical and theoretical implications of using digital history to create more inclusive scholarship.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> [HS]<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C093<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> HIST 212<\/li><li><span class=\"label\">Instructor:<\/span> Anelise Shrout<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+212\" target=\"course-488\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-489\">\n\t\t\t\t\t<h5>DCS 216: Computational Physics<\/h5>\n\t\t\t\t\t<p class=\"course-description\">An introduction to computational methods for simulating physical systems, this course focuses on the numerical analysis and algorithmic implementation necessary for efficient solution of integrals, derivatives, linear systems, differential equations, and optimization. While the course presents a rigorous introduction to the numerical analysis underlying these techniques, the emphasis remains on practical solutions to important physical problems. Students solve problems across a wide range of applications of computational physics, including astrophysics, biological population dynamics, gravitational wave detection, urban traffic flow, and materials science. No prior experience in programming is required, though students without a technical computing background are encouraged to take <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=PHYS%20S10\" data-action=\"result-detail\" data-group=\"code:PHYS S10\"  class=\"notoffered\">PHYS S10<\/a> before enrolling. Prerequisite(s): <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=MATH%20106\" data-action=\"result-detail\" data-group=\"code:MATH 106\" >MATH 106<\/a>, and <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=PHYS%20108\" data-action=\"result-detail\" data-group=\"code:PHYS 108\" >PHYS 108<\/a>, <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=PHYS%20210\" data-action=\"result-detail\" data-group=\"code:PHYS 210\" >210<\/a>, or S31. Prerequisite(s), which may be taken concurrently: <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=MATH%20205\" data-action=\"result-detail\" data-group=\"code:MATH 205\" >MATH 205<\/a>.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> [QF], [SR]<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C006, C056, C093<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> PHYS 216<\/li><li><span class=\"label\">Instructor:<\/span> Jeffrey Oishi<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+216\" target=\"course-489\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-490\">\n\t\t\t\t\t<h5>DCS 219: Composing Sonic Systems<\/h5>\n\t\t\t\t\t<p class=\"course-description\">This course takes computational and communications systems concepts, such as randomness, probability, generativity, signal processing, feedback, control (and non-control), and listening as parameters for electronic sound composition. Using the free, user-friendly visual programming environment, Pure Data (Pd), students create unique software-based artworks and compositions. Creative projects are grounded in theoretical and historical readings as well as listening assignments that provide context for the application of computational concepts and communications systems thinking to sonic arts practice. The course culminates in a final showing of sound art installations and performances. Recommended background: experience in one or more of the following: music composition, music performance, experimental arts, digital media, computer programming, electronics, media studies.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> [CP]<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C005, C093<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> MUS 219<\/li><li><span class=\"label\">Instructor:<\/span> Louis Goldford<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+219\" target=\"course-490\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-491\">\n\t\t\t\t\t<h5>DCS 229: Data Structures and Algorithms<\/h5>\n\t\t\t\t\t<p class=\"course-description\">This course provides an introduction to common data structures and selected algorithms for solving more complex problems.  Topics covered include: object-oriented programming, including inheritance and polymorphism; concrete data types (arrays and linked structures); abstract data types (including stacks, queues, trees, and maps); an introduction to fundamental algorithms including recursive sorting and graph-search algorithms (breadth-first search, depth-first search); and basic algorithm analysis using big O notation. Students will implement details of selected data structures, understand and identify efficiency considerations that result from the choice of data structure, and apply data structures and algorithms in various problem-solving contexts. Prerequisite(s): Any <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=DCS109\" data-action=\"result-detail\" data-group=\"code:DCS109\"  class=\"notoffered\">DCS109<\/a> course.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> [QF]<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C093, C095<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> None<\/li><li><span class=\"label\">Instructor:<\/span> Barry Lawson, Andy Elliot Ricci<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+229\" target=\"course-491\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-492\">\n\t\t\t\t\t<h5>DCS 236: VECINA: Civic Data Design With And For Community<\/h5>\n\t\t\t\t\t<p class=\"course-description\">In this class, students will learn about and work on an active research collaboration &#8211; Visualizing Environmental and Community Information for Neighborhood Advocacy. VECINA is a collaboration between Woonasquatucket River Watershed Council (WRWC), Latinx residents in Providence, Rhode Island, and dozens of data science researchers. WRWC community program fellows and data scientists will join class to talk about their work advocating for environmental justice in their neighborhoods. Students will learn about Providence\u2019s unique immigrant and environmental history and present challenges. We will explore VECINA\u2019s local knowledge-driven projects in flood modeling, art and data visualization, education, healthcare, and multilingual artificial intelligence &#8211; all designed to help residents make daily decisions and advocate for broader policy change. As a final project, students will join one of these \u201cequipitos\u201d and contribute to advancing the VECINA project. Recommended background: content area experience, local expertise, Spanish language experience, and\/or data analysis. Prerequisite(s): One prior DCS or LALS course or <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=FYS%20505\" data-action=\"result-detail\" data-group=\"code:FYS 505\" >FYS 505<\/a>; or instructor permission.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> None<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C093<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> LALS 236<\/li><li><span class=\"label\">Instructor:<\/span> Carrie Eaton<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+236\" target=\"course-492\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-493\">\n\t\t\t\t\t<h5>DCS 301C: Public History in the Digital Age<\/h5>\n\t\t\t\t\t<p class=\"course-description\">Public history takes place beyond history classrooms and academic contexts. Traditionally, it has been found in museums, walking tours, and performances, and has told the stories of people with social and political privilege. Increasingly, however, public history has come to focus on a greater range of voices, and takes place in a wider range of forms: on websites, graphic novels, interactive sensory experiences, social media, and other digital spaces. In this community-engaged course, students learn to see public history &quot;in the wild,&quot; engage with primary sources, and present those sources and historical interpretation to the public in digital form. Students with interests in history and public engagement are encouraged to enroll in this course.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> [HS]<\/li><li><span class=\"label\">Writing Credit:<\/span> [W2]<\/li><li><span class=\"label\">Concentration(s):<\/span> C091, C093<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> HIST 301C<\/li><li><span class=\"label\">Instructor:<\/span> Anelise Shrout<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+301C\" target=\"course-493\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-494\">\n\t\t\t\t\t<h5>DCS 304: Strategic Digital Communication: Building and Engaging Communities Online<\/h5>\n\t\t\t\t\t<p class=\"course-description\">In this course, students examine digital citizenship from the perspective of online community building. They explore theories of collective action, community building, and network assembly, for example, the use of community organizing to propagate information in systems. In this community-engaged learning course, students produce a plan for social media and online organization for a partner community in higher education or STEM education. Recommended background: Prior critical-studies-oriented digital and computational studies course or similar coursework in Africana, American studies, Latin American and Latinx studies, and\/or gender and sexuality studies.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> None<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C091, C093<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> None<\/li><li><span class=\"label\">Instructor:<\/span> Carrie Eaton<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+304\" target=\"course-494\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-495\">\n\t\t\t\t\t<h5>DCS 305: Digital Maps, Space, and Place<\/h5>\n\t\t\t\t\t<p class=\"course-description\">Space and place-visualized by maps-condition nearly every aspect of our lived experience. It is almost impossible to imagine everyday experiences without access to maps. Maps also encode power. They tell particular stories and represent dominant cultural understandings of spatial relationship. In this course, students consider the reasons for studying maps, the ways in which maps might inscribe or combat extant power structures, the tools needed for geospatial analysis, how to embed and analyze geographical information, and how to link historical maps to modern-day geographies. Prerequisite(s): one 200-level digital and computational studies course.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> [CP]<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C093<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> None<\/li><li><span class=\"label\">Instructor:<\/span> Anelise Shrout<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+305\" target=\"course-495\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-496\">\n\t\t\t\t\t<h5>DCS 306: Animal Learning<\/h5>\n\t\t\t\t\t<p class=\"course-description\">The course examines historical and recent trends in animal learning. Topics include classical and operant conditioning, biological constraints on learning, and cognitive processes. Prerequisite(s): one of the following: NRSC\/<a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=PSYC%20160\" data-action=\"result-detail\" data-group=\"code:PSYC 160\" >PSYC 160<\/a> or <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=PSYC%20200\" data-action=\"result-detail\" data-group=\"code:PSYC 200\"  class=\"notoffered\">200<\/a>, <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=PSYC%20222\" data-action=\"result-detail\" data-group=\"code:PSYC 222\"  class=\"notoffered\">PSYC 222<\/a>, <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=PSYC%20230\" data-action=\"result-detail\" data-group=\"code:PSYC 230\" >230<\/a>, or <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=PSYC%20250\" data-action=\"result-detail\" data-group=\"code:PSYC 250\"  class=\"notoffered\">250<\/a>.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> None<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C093<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> NRSC 306, PSYC 305<\/li><li><span class=\"label\">Instructor:<\/span> Jason Castro<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+306\" target=\"course-496\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-497\">\n\t\t\t\t\t<h5>DCS 317: Algorithms &amp; Theory of Computation<\/h5>\n\t\t\t\t\t<p class=\"course-description\">This course presents an introduction to the design and analysis of efficient algorithms, and to the theory of computation.  Students will learn to apply and analyze standard problem-solving techniques, and will also examine the spaces of problems that can be solved versus those that cannot be solved.  Topics in algorithms will cover design strategies including divide &amp; conquer and dynamic programming, as well as tools for analyzing and conveying algorithmic performance and correctness.  The course will also include topics from the theory of computation, including P vs NP and reductions, deterministic finite automata, Turing machines, undecidability, and the halting problem. Prerequisite(s): <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=DCS%20229\" data-action=\"result-detail\" data-group=\"code:DCS 229\" >DCS 229<\/a>.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> [QF]<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C093<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> None<\/li><li><span class=\"label\">Instructor:<\/span> Barry Lawson<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+317\" target=\"course-497\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-498\">\n\t\t\t\t\t<h5>DCS 320: Health Informatics and Digital Health: Data, Systems, and Innovations in Healthcare<\/h5>\n\t\t\t\t\t<p class=\"course-description\">Provides a comprehensive overview of health informatics, examining how digital health technologies and data-driven solutions are transforming healthcare. Includes study of design, implementation, and interoperability of health information systems, including electronic health records (EHRs) and clinical decision support systems (CDSS), and data standards.  Students will learn to acquire, preprocess, and analyze health data using machine learning and predictive modeling techniques to enhance healthcare outcomes.  Students will explore digital health innovations such as telemedicine, wearable devices, and mobile health applications. Students will critically analyze ethical, societal, and regulatory challenges, particularly in patient data privacy, security, and bias in artificial intelligence.  Students will also develop and evaluate innovative digital health solutions to address current and future healthcare challenges through practical, project-based learning using real-world datasets. Recommended background: Basic knowledge of structured computer programming is necessary. Additional study in either computer science or health sciences is recommended. Prerequisite(s): Any <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=DCS109\" data-action=\"result-detail\" data-group=\"code:DCS109\"  class=\"notoffered\">DCS109<\/a> course; and one of the following: <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=DCS%20211\" data-action=\"result-detail\" data-group=\"code:DCS 211\" >DCS 211<\/a>, <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=DCS%20229\" data-action=\"result-detail\" data-group=\"code:DCS 229\" >229<\/a>, <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=BIO%20202\" data-action=\"result-detail\" data-group=\"code:BIO 202\" >BIO 202<\/a>, or permission of the instructor.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> [QF]<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C093<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> None<\/li><li><span class=\"label\">Instructor:<\/span> Chris Agbonkhese<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+320\" target=\"course-498\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-499\">\n\t\t\t\t\t<h5>DCS 321: Advanced Econometrics<\/h5>\n\t\t\t\t\t<p class=\"course-description\">Econometric estimation techniques beyond least squares, including instrumental variables, maximum likelihood, the generalized method of moments, and both nonparametric and simulation methods are introduced. Models for panel data, stochastically trending variables, and limited dependent variables are also discussed. Students&#8217; choice of projects determines which topics are considered in detail. Prerequisite(s): <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=ECON%20255\" data-action=\"result-detail\" data-group=\"code:ECON 255\" >ECON 255<\/a> and <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=ECON%20260\" data-action=\"result-detail\" data-group=\"code:ECON 260\" >ECON 260<\/a>.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> None<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C093<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> ECON 320<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+321\" target=\"course-499\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-500\">\n\t\t\t\t\t<h5>DCS 325: Introduction to Web Development<\/h5>\n\t\t\t\t\t<p class=\"course-description\">This course provides an introduction to full-stack web development, including user-facing website design and construction, back-end frameworks, and client communication. The course will cover fundamental core web technologies (HTML, CSS, and JavaScript), as well as select libraries and frameworks used in current practice (e.g., React, Tailwind CSS). The course will also cover various web data formats (e.g., JSON, XML), server-side \/ back-end frameworks (e.g., Firebase, Django, Flask), fundamental UI and UX concepts (e.g., prototyping, usability, accessibility), and website security. Students will work directly with clients, with a focus on planning and maintenance. Prerequisite(s): <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=DCS%20211\" data-action=\"result-detail\" data-group=\"code:DCS 211\" >DCS 211<\/a> or <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=DCS%20229\" data-action=\"result-detail\" data-group=\"code:DCS 229\" >229<\/a>.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> None<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C093<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> None<\/li><li><span class=\"label\">Instructor:<\/span> Barry Lawson<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+325\" target=\"course-500\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-501\">\n\t\t\t\t\t<h5>DCS 331: Mathematics for Machine Learning<\/h5>\n\t\t\t\t\t<p class=\"course-description\">This course begins with linear regression models and introduces students to a variety of techniques for learning from data, as well as principled methods for assessing and comparing models. Topics include bias-variance trade-off, resampling and cross-validation, linear model selection and regularization, classification and regression trees, bagging, boosting, random forests, support vector machines, generalized additive models, principal component analysis, unsupervised learning and k-means clustering. Emphasis is placed on the mathematics behind these concepts and on the statistical computing in a high-level language (e.g. R or Python). Recommended background: prior coursework in programming and statistics. Prerequisite(s): <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=MATH%20205\" data-action=\"result-detail\" data-group=\"code:MATH 205\" >MATH 205<\/a>.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> [QF], [SR]<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C093<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> MATH 331<\/li><li><span class=\"label\">Instructor:<\/span> Fatou Sanogo<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+331\" target=\"course-501\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-502\">\n\t\t\t\t\t<h5>DCS 340: Evolutionary Computing<\/h5>\n\t\t\t\t\t<p class=\"course-description\">This seminar introduces students to Evolutionary Computing, a field of Artificial Intelligence where software mimics biological natural selection to solve problems. The course focuses on understanding key ideas in Evolutionary Computing by developing intuition and by computational experimentation. First, students are introduced to numerical optimization methods which tend to seek local optima. Then, we introduce evolutionary computing &#8212; exploring how to grow solutions, potentially finding global optima, by using the principles of mutation, crossover, and survival of the fittest. We will also explore paradigms for efficient implementation, such as implementation in parallel programming environments. Finally, we discuss Artificial Life \u2014simulating digital ecosystems and the emergence of complex behavior, the search for computational \u201cintelligence,\u201d and the ethical implications of creating autonomous, self-optimizing systems. Recommended background: Comfortability in programming in at least one language. Prerequisite(s): <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=DCS%20211\" data-action=\"result-detail\" data-group=\"code:DCS 211\" >DCS 211<\/a> or <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=DCS%20229\" data-action=\"result-detail\" data-group=\"code:DCS 229\" >DCS 229<\/a>; or one course from the <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=DCS109\" data-action=\"result-detail\" data-group=\"code:DCS109\"  class=\"notoffered\">DCS109<\/a> series, or <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=DCS%20111\" data-action=\"result-detail\" data-group=\"code:DCS 111\"  class=\"notoffered\">DCS 111<\/a>, and <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=BIO%20206\" data-action=\"result-detail\" data-group=\"code:BIO 206\" >BIO 206<\/a>; or instructor permission.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> None<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C093<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> None<\/li><li><span class=\"label\">Instructor:<\/span> Carrie Eaton<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+340\" target=\"course-502\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-503\">\n\t\t\t\t\t<h5>DCS 347: Robots &amp; Embodied AI: Critical Digital Studies Seminar<\/h5>\n\t\t\t\t\t<p class=\"course-description\">Robots and other embodied artificial intelligence (AI) technologies, such as self-driving cars, autonomous drones, robot vacuum cleaners, and smart home technologies, are increasingly present in our lives. What is the purpose of embodied AI technologies? Why do they exist? Who decides how they should look and act? How do these systems impact individuals and communities? In this interdisciplinary seminar, students will engage with theories from critical digital studies to critically examine embodied AI technologies through an intersectional lens.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> None<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C093<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> GSS 347<\/li><li><span class=\"label\">Instructor:<\/span> Andy Elliot Ricci<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+347\" target=\"course-503\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-504\">\n\t\t\t\t\t<h5>DCS 351: Computational Macroeconomics<\/h5>\n\t\t\t\t\t<p class=\"course-description\">This course is an introduction to dynamic general equilibrium models, which have become the workhorses of modern macroeconomics. These models involve intertemporal optimization by the different agents in the economy: households, firms, and the government. They are often used to analyze the modern theories of growth and aggregate fluctuations, and to study the role of monetary and fiscal policy. Most of these dynamic models, however, do not have analytical (closed form) solutions and one often has to rely on computational methods to analyze their behavior. The goal of this course is to provide an introduction to the computational tools that are necessary to solve dynamic economic models quantitatively. Prerequisite(s): <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=ECON%20255\" data-action=\"result-detail\" data-group=\"code:ECON 255\" >ECON 255<\/a> and <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=ECON%20270\" data-action=\"result-detail\" data-group=\"code:ECON 270\" >270<\/a>.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> [QF], [SR]<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C093<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> ECON 351<\/li><li><span class=\"label\">Instructor:<\/span> Pubali Chakraborty, Anamika Sen<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+351\" target=\"course-504\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-505\">\n\t\t\t\t\t<h5>DCS 352: Preserving the Vibration: Digitizing the Life of Vertamae Smart-Grosvenor<\/h5>\n\t\t\t\t\t<p class=\"course-description\">This course introduces public and digital humanities through the life and work of noted journalist, food anthropologist, and public broadcaster Vertamae Grosvenor. Public humanities is concerned with facilitating conversations on topics of humanistic inquiry with the community at large. Digital studies provide unconventional ways to engage communities in public dialogues for the greater good. Drawing from books, operas, NPR audio segments, interviews, cookbooks, and other artifacts of Grosvenor, students create and curate a digital archive. Themes include Gullah culture, African American migration, foodways, memoir, public memory, and monuments. Leading theories and methods of black feminism, material culture, race, food studies, new media, and digital humanities are foregrounded.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> [AC], [CP]<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C093<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> AMST 352, GSS 352<\/li><li><span class=\"label\">Instructor:<\/span> Myron Beasley<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+352\" target=\"course-505\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-506\">\n\t\t\t\t\t<h5>DCS 353: Economics of Artificial Intelligence<\/h5>\n\t\t\t\t\t<p class=\"course-description\">The rapid advancement of Artificial Intelligence (AI) is fundamentally transforming the economy, labor markets, and society. This upper-level seminar explores the economic implications of AI, bringing together theoretical models and cutting-edge empirical research. Students will investigate how AI affects productivity, firm behavior, labor demand, and income inequality. We will examine AI as a general-purpose technology, the economics of automation, and the role of algorithmic predictions in decision-making. Through recent academic papers (e.g., NBER) and policy reports (e.g., Brookings), the course bridges economic theory with real-world applications. Furthermore, we will critically evaluate the ethical and policy dimensions of AI, including algorithmic bias, data privacy, market concentration, and responsible AI governance. Students will apply econometric tools to evaluate AI&#8217;s localized impacts and develop original research proposals. By the end of the course, students will be equipped to rigorously analyze the socioeconomic impacts of emerging digital technologies. Recommended background: Students should be well prepared in econometrics and intermediate-level theories of economics. Prerequisite(s): <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=ECON%20255\" data-action=\"result-detail\" data-group=\"code:ECON 255\" >ECON 255<\/a> and <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=ECON%20260\" data-action=\"result-detail\" data-group=\"code:ECON 260\" >ECON 260<\/a>.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> [HS], [QF]<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C093<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> ECON 353<\/li><li><span class=\"label\">Instructor:<\/span> Leshui He<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+353\" target=\"course-506\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-507\">\n\t\t\t\t\t<h5>DCS 355A: Numerical Analysis<\/h5>\n\t\t\t\t\t<p class=\"course-description\">This course studies the best ways to perform calculations that have already been developed in other mathematics courses. For instance, if a computer is to be used to approximate the value of an integral, one must understand both how quickly an algorithm can produce a result and how trustworthy that result is. While students implement algorithms on computers, the focus of the course is the mathematics behind the algorithms. Topics may include interpolation techniques, approximation of functions, solving equations, differentiation and integration, solution of differential equations, iterative solutions of linear systems, and eigenvalues and eigenvectors. Prerequisite(s): <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=MATH%20106\" data-action=\"result-detail\" data-group=\"code:MATH 106\" >MATH 106<\/a> and <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=MATH%20205\" data-action=\"result-detail\" data-group=\"code:MATH 205\" >205<\/a>.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> [QF]<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C006, C093<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> MATH 355A<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+355A\" target=\"course-507\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-508\">\n\t\t\t\t\t<h5>DCS 355D: Chaotic Dynamical Systems<\/h5>\n\t\t\t\t\t<p class=\"course-description\">The field of dynamical systems is best understood from both theoretical and computational viewpoints, as each informs the other. Students explore attracting and repelling cycles and witness the complicated dynamics and chaos a simple function can exhibit. Topics include chaos in discrete versus continuous dynamical systems, bifurcations, and attractors, with applications to biology and physics. While there will be a significant computational component to the course, previous coding experience is not required.  Recommended background: <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=MATH219\" data-action=\"result-detail\" data-group=\"code:MATH219\"  class=\"notoffered\">MATH219<\/a>. Prerequisite(s): <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=MATH205\" data-action=\"result-detail\" data-group=\"code:MATH205\"  class=\"notoffered\">MATH205<\/a>.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> [QF]<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C006, C093<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> MATH 355D<\/li><li><span class=\"label\">Instructor:<\/span> Chip Ross<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+355D\" target=\"course-508\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-509\">\n\t\t\t\t\t<h5>DCS 355H: Numerical Linear Algebra<\/h5>\n\t\t\t\t\t<p class=\"course-description\">This course studies the best ways to perform calculations that have been developed in Linear Algebra. Topics may include solving systems of equations, error and condition numbers, least squares, and eigenvalues and singular values. Prerequisite(s): <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=MATH%20205\" data-action=\"result-detail\" data-group=\"code:MATH 205\" >MATH 205<\/a><\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> None<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C006, C093<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> MATH 355H<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+355H\" target=\"course-509\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-510\">\n\t\t\t\t\t<h5>DCS 357: Computational Neuroscience\/Lab<\/h5>\n\t\t\t\t\t<p class=\"course-description\">The brain is a complex object, and studying it scientifically requires a facility with tools and concepts for analyzing high dimensional data. This course will provide a survey of such tools through representative case studies in perception (how many types of odors are there?), genomics (how do we classify cell types?), and neural coding and dynamics (how does brain activity encode attributes of the world?).  Students will develop intuitions for framing fundamental neuroscience questions as data-driven problems, and will also develop skills for exploring, visualizing, modeling, and interpreting data. No prior experience with coding is assumed or expected, and the course will emphasize the use of high-level computational tools rather than implementation of algorithms from scratch. Prerequisite(s): NRSC\/<a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=PSYC%20160\" data-action=\"result-detail\" data-group=\"code:PSYC 160\" >PSYC 160<\/a>.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> [SR]<\/li><li><span class=\"label\">Writing Credit:<\/span> [W2]<\/li><li><span class=\"label\">Concentration(s):<\/span> C093, C095<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> NRSC 357, PSYC 357<\/li><li><span class=\"label\">Instructor:<\/span> Jason Castro<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+357\" target=\"course-510\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-511\">\n\t\t\t\t\t<h5>DCS 360: Independent Study<\/h5>\n\t\t\t\t\t<p class=\"course-description\">Students, in consultation with a faculty advisor, individually design and plan a course of study or research not offered in the curriculum. Course work includes a reflective component, evaluation, and completion of an agreed-upon product. Sponsorship by a faculty member in the program\/department, a course prospectus, and permission of the chair are required. Students may register for no more than one independent study per semester. <\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> None<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C093<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> None<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+360\" target=\"course-511\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-512\">\n\t\t\t\t\t<h5>DCS 362: Art, History, and Artificial Intelligence: Artworks not Pixels<\/h5>\n\t\t\t\t\t<p class=\"course-description\">Computers and technology are not new to art and visual culture. In their many forms, both computational and observational technologies have long been used in artistic research and practice\u2013from the 15th century camera obscura to the earliest computers in the 1960s. Over the last decade, the rapid incorporation of Artificial Intelligence into the study of both art and history demands that we (re)consider the relationship between material culture, human creativity, and scientific technology. How are art, history, and AI connected? Students will work to understand AI not just as a tool for artistic production or art historical research but as a genre that can reshape creative and scholarly outputs. They will evaluate training data used to create LLMs in order to understand their curated nature and potential biases as well as engage with ethical issues, including authorship, ownership, and surveillance, and finally question how AI technology might detect forgeries or arrange exhibitions.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> [AC], [HS]<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C093<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> AVC 362<\/li><li><span class=\"label\">Instructor:<\/span> Erin Nolan<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+362\" target=\"course-512\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-513\">\n\t\t\t\t\t<h5>DCS 368: Data Science for Economists<\/h5>\n\t\t\t\t\t<p class=\"course-description\">Economics is at the forefront of developing statistical methods for analyzing data collected from uncontrolled sources. Because econometrics addresses challenges such as sample selection bias and treatment effects identification, the discipline is well-suited to analyze large or unstructured datasets. This course introduces practical tools and econometric techniques to conduct empirical analysis on topics like equality of opportunity, education, racial disparities, and more. These skills include data acquisition, project management, version control, data visualization, efficient programming, and tools for big data analysis. The course also explores how econometrics and statistical learning methods cross-fertilize and can be used to advance knowledge on topics where large volumes of data are rapidly accumulating. We will also cover the ethics of data collection and analysis.  Prerequisite(s): <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=ECON%20255\" data-action=\"result-detail\" data-group=\"code:ECON 255\" >ECON 255<\/a> and <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=ECON%20260\" data-action=\"result-detail\" data-group=\"code:ECON 260\" >ECON 260<\/a> or <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=ECON%20270\" data-action=\"result-detail\" data-group=\"code:ECON 270\" >270<\/a>.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> [QF]<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C093<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> ECON 368<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+368\" target=\"course-513\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-514\">\n\t\t\t\t\t<h5>DCS 374: Computer Systems<\/h5>\n\t\t\t\t\t<p class=\"course-description\">This course provides students with an understanding of computer systems from hardware to the cloud, emphasizing breadth over depth. Students will explore fundamental concepts of computer organization, operating systems, computer networks, and cloud computing, examining how AI influences modern system design and optimization. Topics include processor architecture, memory hierarchies, process management, file systems, network protocols, and distributed and cloud computing fundamentals. Through hands-on laboratory exercises and projects, students will develop practical systems programming skills in C++ while gaining insights into performance, reliability, and security considerations essential for understanding modern computing infrastructure. Prerequisite(s): <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=DCS%20211\" data-action=\"result-detail\" data-group=\"code:DCS 211\" >DCS 211<\/a> or <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=DCS%20229\" data-action=\"result-detail\" data-group=\"code:DCS 229\" >DCS 229<\/a>.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> [QF]<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> None<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> None<\/li><li><span class=\"label\">Instructor:<\/span> Barry Lawson<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+374\" target=\"course-514\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-515\">\n\t\t\t\t\t<h5>DCS 375: Network Science and Analysis<\/h5>\n\t\t\t\t\t<p class=\"course-description\">Networks are everywhere. They describe how people, organisms, and ideas connect and interact. Studying networks reveals patterns, systems, and frameworks that are, in many cases, otherwise invisible. This course introduces network analysis as a tool that offers insights into the construction of social, biological, and information systems. It scaffolds the terminology and theoretical underpinnings of network science. It also introduces the data wrangling, qualitative analysis, quantitative analysis, critical analysis, and data visualization tools that often accompany the studies of networks. Recommended background: Prior coursework in data cleaning and structuring and\/or textual analysis. Prerequisite(s): One course from the <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=DCS%20109\" data-action=\"result-detail\" data-group=\"code:DCS 109\"  class=\"notoffered\">DCS 109<\/a> series, <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=DCS%20111\" data-action=\"result-detail\" data-group=\"code:DCS 111\"  class=\"notoffered\">DCS 111<\/a>, <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=DCS%20117\" data-action=\"result-detail\" data-group=\"code:DCS 117\" >DCS 117<\/a>, <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=DCS%20204\" data-action=\"result-detail\" data-group=\"code:DCS 204\" >DCS 204<\/a>, <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=DCS%20210\" data-action=\"result-detail\" data-group=\"code:DCS 210\"  class=\"notoffered\">DCS 210<\/a>, <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=DCS%20211\" data-action=\"result-detail\" data-group=\"code:DCS 211\" >DCS 211<\/a>, or <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=DCS%20229\" data-action=\"result-detail\" data-group=\"code:DCS 229\" >DCS 229<\/a>; or by instructor permission.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> [SR]<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C093, C095<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> None<\/li><li><span class=\"label\">Instructor:<\/span> Carrie Eaton, Anelise Shrout<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+375\" target=\"course-515\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-516\">\n\t\t\t\t\t<h5>DCS 383: Surveillance and Society<\/h5>\n\t\t\t\t\t<p class=\"course-description\">Surveillance in a pervasive feature of modern societies\u2014indeed, surveillance is often considered part of what defines \u201cmodern\u201d social life. In this course, students will explore how personal, everyday uses of surveillance devices and experiences of data collection shape and are shaped by larger efforts to control populations, and how mobile digital connectivity influences those dynamics. Together, we consider foundational texts in academic studies of surveillance; techniques of surveillance found in health, education, and other social spheres; surveillance as a component of modern governance; and persistent stratifications in surveillance practices.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> None<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C093<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> AMST 383, GSS 383, SOC 383<\/li><li><span class=\"label\">Instructor:<\/span> Rebecca Herzig<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+383\" target=\"course-516\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-517\">\n\t\t\t\t\t<h5>DCS 401: Internship in Digital and Computational Studies<\/h5>\n\t\t\t\t\t<p class=\"course-description\">Part-time internships, which may be local or distant, conducted in-person or remotely. Internships provide digital and computational studies students opportunities to apply what they have learned in courses, learn and apply new skills, gain knowledge in a specific field, build professional skills, and explore career paths in digital and computational studies. Prerequisite(s): one course in digital and computational studies. Enrollment is limited to available positions. *F-1 visa holders are not eligible for this course.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> None<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C093<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> None<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> Yes<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+401\" target=\"course-517\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-518\">\n\t\t\t\t\t<h5>DCS 456: Senior Capstone<\/h5>\n\t\t\t\t\t<p class=\"course-description\">Students work in teams to design, build, analyze, and critique a software\/digital solution in partnership with external stakeholders. The course provides a real-world culminating experience that synthesizes the knowledge, skills, and values developed throughout the major. Required of all DCS majors. Prerequisite(s): <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=DCS%20211\" data-action=\"result-detail\" data-group=\"code:DCS 211\" >DCS 211<\/a> or <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=DCS%20229\" data-action=\"result-detail\" data-group=\"code:DCS 229\" >229<\/a>; completion of the Methods requirement; and one 300-level or higher course in DCS.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> None<\/li><li><span class=\"label\">Writing Credit:<\/span> [W3]<\/li><li><span class=\"label\">Concentration(s):<\/span> C093<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> None<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+456\" target=\"course-518\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-519\">\n\t\t\t\t\t<h5>DCS 457: Senior Thesis<\/h5>\n\t\t\t\t\t<p class=\"course-description\">Open to DCS majors only by prior approval from the DCS Program Committee. Prior to entrance into DCS 457, students must submit a proposal for the work they intend to undertake toward completion of a thesis. Required of candidates for Honors. Students register for DCS 457 in the fall semester.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> None<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C093<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> None<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> Yes<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+457\" target=\"course-519\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-520\">\n\t\t\t\t\t<h5>DCS 458: Senior Thesis<\/h5>\n\t\t\t\t\t<p class=\"course-description\">Open to DCS majors only by prior approval from the DCS Program Committee. Prior to entrance into DCS 458, students must submit a proposal for the work they intend to undertake toward completion of a thesis. Required of candidates for Honors. Students register for DCS 458 in the winter semester.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> None<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C093<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> None<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> Yes<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+458\" target=\"course-520\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-521\">\n\t\t\t\t\t<h5>DCS S13: Computation &amp; Mathematical Art<\/h5>\n\t\t\t\t\t<p class=\"course-description\">This course will explore art and how art can be used to visually demonstrate computational and mathematical concepts. Explore the cross-over between two very different disciplines and what you can do with this knowledge. This course will feature work by prominent mathematicians and computer scientists in the mathematical and computational art space. Additionally, students will leave the course with a completed art project of their devising that demonstrates a computational or mathematical concept and a beginner level knowledge of crochet. The course will also include a historical overview of how art, specifically weaving and knitting, were instrumental in creating examples of how to store information that would be used as computer science was developed. Recommended background: Creativity, interest in creating art. Prerequisite(s): any college-level math course, or any <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=DCS109\" data-action=\"result-detail\" data-group=\"code:DCS109\"  class=\"notoffered\">DCS109<\/a> course.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> None<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C093<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> None<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+S13\" target=\"course-521\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-522\">\n\t\t\t\t\t<h5>DCS S17: Modeling &amp; Data Analysis in the Physical Sciences<\/h5>\n\t\t\t\t\t<p class=\"course-description\">How are models used in the physical sciences? How are models informed by data in different disciplines, and how do we analyze it? This course will provide students with an opportunity to explore the many ways that models are used to conduct scientific research, and gain insights into how models can support their academic and career goals. We will discuss a variety of models, techniques, and tools used throughout the physical sciences, and guide students to use them for their own research project. Students will learn data fundamentals as well as specific applications of these data-driven techniques to fields within the physical sciences. Lessons will be taught through a lecture and lab component, going over the concepts before letting students work through coding projects, enabling them to create and conduct their own data-driven research. This course has no prerequisites, and aims to bring together students from a wide variety of academic disciplines and any level of coding experience.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> [QF], [SR]<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C056, C093<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> ASTR S11, EACS S11, PHYS S11<\/li><li><span class=\"label\">Instructor:<\/span> Rebecca Payne<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+S17\" target=\"course-522\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-523\">\n\t\t\t\t\t<h5>DCS S18: Applied Introduction to Databases and SQL<\/h5>\n\t\t\t\t\t<p class=\"course-description\">This course provides an intermediate, applied introduction to relational databases and Structured Query Language (SQL). The course is designed to give students a clear and practical understanding of how structured data is stored, organized, and queried using the relational model. No prior programming experience is required. The course assumes basic computer literacy and an introductory familiarity with working in a computing environment (e.g., using files, spreadsheets, or simple command-line tools). Students will study core principles of relational database design and develop proficiency in writing SQL queries to retrieve and analyze data. Emphasis is placed on conceptual clarity, data integrity, and applied problem-solving using realistic datasets. The course prioritizes practical competence and careful reasoning over advanced theoretical treatment of database systems.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> [QF]<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C093<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> None<\/li><li><span class=\"label\">Instructor:<\/span> Chris Agbonkhese<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+S18\" target=\"course-523\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-524\">\n\t\t\t\t\t<h5>DCS S28: Architectural Visualization: Past and Future<\/h5>\n\t\t\t\t\t<p class=\"course-description\">Three-dimensional models and two-dimensional images are a fundamental part of building, studying, and thinking about architecture. Architectural design practices are culturally specific, and many building traditions planned monuments prior to construction and communicated a structure\u2019s form in a portable format. Students will learn about and practice different modes of historical and contemporary architectural representation, from the paper plan to the digital model. We will introduce the topic of architectural visualization through reading, discussion, and making. No prior experience with architectural history, studio art, or software platforms is required.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> [AC], [CP]<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C093<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> AVC S29<\/li><li><span class=\"label\">Instructor:<\/span> Megan Boomer<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+S28\" target=\"course-524\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-525\">\n\t\t\t\t\t<h5>DCS S29: Logic: Possibility, Proofs, and Paradox<\/h5>\n\t\t\t\t\t<p class=\"course-description\">Building on <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=PHIL%20195\" data-action=\"result-detail\" data-group=\"code:PHIL 195\" >PHIL 195<\/a> (Introduction to Logic), students consider the relationship between logic and reasoning, learn about modal logic (the logic of possibility and necessity), Turing machines, and alternative logics, prove some surprising metalogical results, and puzzle through some logical paradoxes. Prerequisite(s): <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=PHIL%20195\" data-action=\"result-detail\" data-group=\"code:PHIL 195\" >PHIL 195<\/a>.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> [QF]<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C031, C042, C093<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> PHIL S29<\/li><li><span class=\"label\">Instructor:<\/span> Lauren Ashwell<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+S29\" target=\"course-525\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-526\">\n\t\t\t\t\t<h5>DCS S31: Human-Robot Interaction Design Workshop<\/h5>\n\t\t\t\t\t<p class=\"course-description\">How should robots co-exist with humans? In this course, you will learn about the field of human-robot interaction (HRI) with a focus on the theory and processes used to design robots that interact with people. You will work in teams to iteratively design, build, and evaluate a new human-robot interaction system. At the end of the term, each team will share their findings and design process. No prior programming or robotics experience is required. Prerequisite(s): One DCS course or instructor permission.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> None<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C093<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> None<\/li><li><span class=\"label\">Instructor:<\/span> Andy Elliot Ricci<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+S31\" target=\"course-526\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-527\">\n\t\t\t\t\t<h5>DCS S34: Data, AI, and Society: Ethical Implications in Research and Practice<\/h5>\n\t\t\t\t\t<p class=\"course-description\">How do data practices by companies, governments, educators, and researchers shape our world, and what ethical responsibilities come with this power? Open to students from all backgrounds, this course explores the ethical landscape of data science and AI through topics like data privacy, surveillance, algorithmic bias, and data governance, examining how these practices impact personal freedoms, education, and public trust. Through case studies, discussions, and interactive activities, you\u2019ll learn to navigate ethical challenges across the data lifecycle, building skills in transparency, responsible communication, and fairness in data applications. By the end, you\u2019ll apply your insights in a short final project, designing either a research plan with ethical safeguards or a teaching module on data and AI ethics. Recommended background: Basic experience with a statistics or data science course. Prerequisite(s): <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=MATH%20117\" data-action=\"result-detail\" data-group=\"code:MATH 117\" >MATH 117<\/a>, <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=DCS%20204\" data-action=\"result-detail\" data-group=\"code:DCS 204\" >DCS 204<\/a>, <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=DCS%20210\" data-action=\"result-detail\" data-group=\"code:DCS 210\"  class=\"notoffered\">210<\/a>, <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=DCS%20211\" data-action=\"result-detail\" data-group=\"code:DCS 211\" >211<\/a>, or <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=DCS%20375\" data-action=\"result-detail\" data-group=\"code:DCS 375\" >375<\/a>, or instructor permission.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> None<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C093<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> None<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+S34\" target=\"course-527\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-528\">\n\t\t\t\t\t<h5>DCS S45T: Mathematical Image Processing<\/h5>\n\t\t\t\t\t<p class=\"course-description\">This course introduces mathematical methods in digital image processing, including basic image processing tools and techniques with an emphasis on their mathematical foundations. Students implement the theory using MATLAB. Topics may include image filtering, image enhancement, edge detection, and image segmentation. Prerequisite(s): <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=MATH%20205\" data-action=\"result-detail\" data-group=\"code:MATH 205\" >MATH 205<\/a> or <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=MATH%20206\" data-action=\"result-detail\" data-group=\"code:MATH 206\" >206<\/a>.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> None<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C093<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> MATH S45T<\/li><li><span class=\"label\">Instructor:<\/span> Katy Ott<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+S45T\" target=\"course-528\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-529\">\n\t\t\t\t\t<h5>DCS S50: Independent Study<\/h5>\n\t\t\t\t\t<p class=\"course-description\">Students, in consultation with a faculty advisor, individually design and plan a course of study or research not offered in the curriculum. Course work includes a reflective component, evaluation, and completion of an agreed-upon product. Sponsorship by a faculty member in the program\/department, a course prospectus, and permission of the chair are required. Students may register for no more than one independent study during a Short Term.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> None<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C093<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> None<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> No<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+S50\" target=\"course-529\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-530\">\n\t\t\t\t\t<h5>DCS S51A: STIP: Rethinking Archives, Data and Analysis: Critical Approaches to Archival Data and ÀÖ²¥´«Ã½ College<\/h5>\n\t\t\t\t\t<p class=\"course-description\">Through engagement with archives, scholarly literature and ÀÖ²¥´«Ã½&#8217;s history, students in this curricular innovation course will help to re-imagine AMST\/<a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=DCS%20204\" data-action=\"result-detail\" data-group=\"code:DCS 204\" >DCS 204<\/a>: Archives, Data and Analysis. This re-imagining will include considering new archives and\/or data that can help inform our understanding of ÀÖ²¥´«Ã½ College in the past and the present, incorporating innovative work in critical archival and data studies, and considering which computational methods and approaches might be added to enhance the course. This re-designed course will center the operation of race, power, privilege and\/or colonialism in the context of ÀÖ²¥´«Ã½ College. At the end of this short-term course, students will have a grounding in the scholarly work on data analysis, critique and archives, as well as in computational methods necessary to complete those analyses. Recommended background: prior coursework in DCS beyond AMST\/<a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=DCS%20204\" data-action=\"result-detail\" data-group=\"code:DCS 204\" >DCS 204<\/a>. Prerequisite(s): <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=AMST%20204\" data-action=\"result-detail\" data-group=\"code:AMST 204\"  class=\"notoffered\">AMST 204<\/a>, <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=DCS%20104\" data-action=\"result-detail\" data-group=\"code:DCS 104\"  class=\"notoffered\">DCS 104<\/a>, or <a target=\"_blank\" href=\"https:\/\/catalog.bates.edu\/search\/?p=DCS%20204\" data-action=\"result-detail\" data-group=\"code:DCS 204\" >204<\/a>.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> [AC], [HS]<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C093<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> AMST S51B<\/li><li><span class=\"label\">Instructor:<\/span> Anelise Shrout<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> Yes<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+S51A\" target=\"course-530\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><div class=\"catalog-course _full-view\" id=\"course-531\">\n\t\t\t\t\t<h5>DCS S51B: STIP: Generative AI and Human Minds: Peril or Partnership?<\/h5>\n\t\t\t\t\t<p class=\"course-description\">In this class, students will build aspirational, technical, and critical philosophies of how minds like theirs are shaped by generative AI. Are there radical new possibilities for intellectual growth with digital interlocutors who are endlessly patient, customizable, and connected? Or do these same capacities threaten to impose new forms of intellectual atrophy and limitation? Students will work with and interrogate generative AI to explore how learning, creativity, and self-understanding change (and perhaps unravel) when our interlocutors are machines \u2014 developing both reflective and pragmatic theories of their own minds informed by both neuroscience and direct experience.<\/p>\n\t\t\t\t\t<details class=\"course-meta\">\n\t\t\t\t\t\t<summary>More details<\/summary>\n\t\t\t\t\t\t<ul><li><span class=\"label\">Modes of Inquiry:<\/span> None<\/li><li><span class=\"label\">Writing Credit:<\/span> None<\/li><li><span class=\"label\">Concentration(s):<\/span> C093<\/li><li><span class=\"label\">Cross-listed Course(s):<\/span> NRSC S51B<\/li><li><span class=\"label\">Instructor:<\/span> Jason Castro<\/li><li><span class=\"label\">Instructor Permission Required:<\/span> Yes<\/li><\/ul>\n\t\t\t\t\t<\/details><p class=\"catalog-full-link\">\n\t\t\t\t\t\t<a href=\"https:\/\/catalog.bates.edu\/course-search\/?details=1&#038;code=DCS+S51B\" target=\"course-531\">Full Catalog Listing<\/a>\n\t\t\t\t\t<\/p>\n\t\t\t\t<\/div><\/div>","protected":false},"excerpt":{"rendered":"","protected":false},"author":5,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"open","template":"","meta":{"_hide_ai_chatbot":false,"_ai_chatbot_style":"","associated_faculty":[],"_Page_Specific_Css":"","_bates_restrict_mod":false,"_batesModPostContentOverride_prepend":false,"_batesModPostContentOverride_append":false,"_batesModPostContentOverride_append_before_footer":false,"bates_author_byline_override":"","_hide_page_title":false,"_header_override":"","_template_width_override":"","_table_of_contents_display":false,"_table_of_contents_location":"","_table_of_contents_disableSticky":false,"_is_featured":false,"_sidebarChoice":"","footnotes":"","_bates_seo_meta_description":"","_bates_seo_block_robots":false,"_bates_seo_sharing_image_id":0,"_bates_seo_sharing_image_twitter_id":0,"_bates_seo_share_title":"","_bates_seo_canonical_overwrite":"","_bates_seo_twitter_template":""},"class_list":["post-5","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/www.bates.edu\/digital-computational-studies\/wp-json\/wp\/v2\/pages\/5","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.bates.edu\/digital-computational-studies\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.bates.edu\/digital-computational-studies\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.bates.edu\/digital-computational-studies\/wp-json\/wp\/v2\/users\/5"}],"replies":[{"embeddable":true,"href":"https:\/\/www.bates.edu\/digital-computational-studies\/wp-json\/wp\/v2\/comments?post=5"}],"version-history":[{"count":9,"href":"https:\/\/www.bates.edu\/digital-computational-studies\/wp-json\/wp\/v2\/pages\/5\/revisions"}],"predecessor-version":[{"id":870,"href":"https:\/\/www.bates.edu\/digital-computational-studies\/wp-json\/wp\/v2\/pages\/5\/revisions\/870"}],"wp:attachment":[{"href":"https:\/\/www.bates.edu\/digital-computational-studies\/wp-json\/wp\/v2\/media?parent=5"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}