Search Results
Your search for courses · during 24FA, 25WI, 25SP · tagged with CS Major Electives · returned 16 results
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CS 304 Social Computing 6 credits
The last decade has seen a vast increase in the number of applications that connect people with one another. This course presents an interdisciplinary introduction to social computing, a field of study that explores how computational techniques and artifacts are used to support and understand social interactions. We will examine a number of socio-technical systems (such as wikis, social media platforms, and citizen science projects), discuss the design principles used to build them, and analyze how they help people mobilize and collaborate with one another. Assignments will involve investigating datasets from online platforms and exploring current research in the field.
- Spring 2025
- FSR, Formal or Statistical Reasoning QRE, Quantitative Reasoning
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Student has completed any of the following course(s): CS 200 or CS 201 with a grade of C- or better or received a Carleton Computer Science 201 or better Requisite Equivalency.
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CS 304.00 Spring 2025
- Faculty:Sneha Narayan 🏫 👤
- Size:16
- M, WAnderson Hall 323 12:30pm-1:40pm
- FAnderson Hall 323 1:10pm-2:10pm
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16 – reserved for REQ: CS 304 Match (Condition Rule) until 2/28/2025
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CS 311 Computer Graphics 6 credits
Scientific simulations, movies, and video games often incorporate computer-generated images of fictitious worlds. How are these worlds represented inside a computer? How are they “photographed” to produce the images that we see? What performance constraints and design trade-offs come into play? In this course we learn the basic theory and methodology of three-dimensional computer graphics, including both triangle rasterization and ray tracing. Familiarity with vectors and matrices is recommended but not required.
- Spring 2025
- FSR, Formal or Statistical Reasoning QRE, Quantitative Reasoning
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Student has completed any of the following course(s): CS 208 with grade of C- or better.
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CS 314 Data Visualization 6 credits
Understanding the wealth of data that surrounds us can be challenging. Luckily, we have evolved incredible tools for finding patterns in large amounts of information: our eyes! Data visualization is concerned with taking information and turning it into pictures to better communicate patterns or discover new insights. It combines aspects of computer graphics, human-computer interaction, design, and perceptual psychology. In this course, we will learn the different ways in which data can be expressed visually and which methods work best for which tasks. Using this knowledge, we will critique existing visualizations as well as design and build new ones.
- Winter 2025
- FSR, Formal or Statistical Reasoning QRE, Quantitative Reasoning
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Student has completed any of the following course(s): CS 200 or CS 201 with a grade of C- or better or received a Carleton Computer Science 201 or better Requisite Equivalency.
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CS 314.00 Winter 2025
- Faculty:Bridger Herman 🏫
- Size:34
- M, WLeighton 304 12:30pm-1:40pm
- FLeighton 304 1:10pm-2:10pm
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CS 320 Machine Learning 6 credits
What does it mean for a machine to learn? Much of modern machine learning focuses on identifying patterns in large datasets and using these patterns to make predictions about the future. Machine learning has impacted a diverse array of applications and fields, from scientific discovery to healthcare to education. In this artificial intelligence-related course, we’ll both explore a variety of machine learning algorithms in different application areas, taking both theoretical and practical perspectives, and discuss impacts and ethical implications of machine learning more broadly. Topics may vary, but typically focus on regression and classification algorithms, including neural networks.
X seats held for CS Match until the day after X priority registration.
- Spring 2025
- FSR, Formal or Statistical Reasoning
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Student has completed any of the following course(s): CS 200 with a grade of C- or better or CS 201 with a grade of C- or better or received a Carleton Computer Science 200 Requisite Equivalency AND CS 202 with a grade of C- or better or received a Carleton Computer Science 202 Requisite Equivalency or MATH 236 with a grade of C- or better or received a Carleton Math 236 Requisite Equivalency. MATH 236 will be accepted in lieu of CS 202.
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CS 320.00 Spring 2025
- Faculty:Tom Finzell 🏫
- Size:34
- M, WLanguage & Dining Center 104 11:10am-12:20pm
- FLanguage & Dining Center 104 12:00pm-1:00pm
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19 – reserved for REQ: CS 320 Match (Condition Rule) until 3/7/2025
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CS 321 Making Decisions with Artificial Intelligence 6 credits
There are many situations where computer systems must make intelligent choices, from selecting actions in a game, to suggesting ways to distribute scarce resources for monitoring endangered species, to a search-and-rescue robot learning to interact with its environment. Artificial intelligence offers multiple frameworks for solving these problems. While popular media attention has often emphasized supervised machine learning, this course instead engages with a variety of other approaches in artificial intelligence, both established and cutting edge. These include intelligent search strategies, game playing approaches, constrained decision making, reinforcement learning from experience, and more. Coursework includes problem solving and programming.
- Winter 2025
- FSR, Formal or Statistical Reasoning
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Student has completed any of the following course(s): CS 200 with a grade of C- or better or CS 201 with a grade of C- or better or received a Carleton Computer Science 200 Requisite Equivalency AND CS 202 with a grade of C- or better or received a Carleton Computer Science 202 Requisite Equivalency or MATH 236 with a grade of C- or better or received a Carleton Math 236 Requisite Equivalency. MATH 236 will be accepted in lieu of CS 202.
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CS 321.00 Winter 2025
- Faculty:Chelsey Edge 🏫 👤
- Size:34
- M, WAnderson Hall 329 8:30am-9:40am
- FAnderson Hall 329 8:30am-9:30am
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CS 322 Natural Language Processing 6 credits
Computers are poor conversationalists, despite decades of attempts to change that fact. This course will provide an overview of the computational techniques developed in the attempt to enable computers to interpret and respond appropriately to ideas expressed using natural languages (such as English or French) as opposed to formal languages (such as C++ or Lisp). Topics in this course will include parsing, semantic analysis, machine translation, dialogue systems, and statistical methods in speech recognition.
- Fall 2024
- FSR, Formal or Statistical Reasoning QRE, Quantitative Reasoning
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Student has completed any of the following course(s): CS 200 with a grade of C- or better or CS 201 with a grade of C- or better or received a Carleton Computer Science 200 Requisite Equivalency AND CS 202 with a grade of C- or better or received a Carleton Computer Science 202 Requisite Equivalency or MATH 236 with a grade of C- or better or received a Carleton Math 236 Requisite Equivalency. MATH 236 will be accepted in lieu of CS 202.
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CS 322.00 Fall 2024
- Faculty:Eric Alexander 🏫 👤
- Size:34
- M, WLanguage & Dining Center 104 12:30pm-1:40pm
- FLanguage & Dining Center 104 1:10pm-2:10pm
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28 spots held for students in CS Match until 9:00 a.m. May 24
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CS 330 Introduction to Real-Time Systems 6 credits
How can we prove that dynamic cruise control will brake quickly enough if traffic suddenly stops? How must a system coordinate processes to detect pedestrians and other vehicles to ensure fair sharing of computing resources? In real-time systems, we explore scheduling questions like these, which require provable guarantees of timing constraints for applications including autonomous vehicles. This course will start by considering such questions for uniprocessor machines, both when programs have static priorities and when priorities can change over time. We will then explore challenges introduced by modern computers with multiple processors. We will consider both theoretical and practical perspectives.
- Winter 2025
- FSR, Formal or Statistical Reasoning
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Student has completed any of the following course(s): CS 200 with a grade of C- or better or CS 201 with a grade of C- or better or received a Carleton Computer Science 200 Requisite Equivalency AND CS 202 with a grade of C- or better or received a Carleton Computer Science 202 Requisite Equivalency or MATH 236 with a grade of C- or better or received a Carleton Math 236 Requisite Equivalency. MATH 236 will be accepted in lieu of CS 202.
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CS 330.00 Winter 2025
- Faculty:Tanya Amert 🏫 👤
- Size:34
- M, WAnderson Hall 329 1:50pm-3:00pm
- FAnderson Hall 329 2:20pm-3:20pm
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CS 338 Computer Security 6 credits
When hackers can disable gas pipelines, national hospital systems, and electrical grids, and data brokers can create a largely unregulated world-wide surveillance system, there’s a clear need for people who understand the mechanisms of computer security and insecurity. Towards that end, in this course we will study technical and social aspects of computer and network security. Topics will include threat modeling, cryptography, secure network protocols, web security, ethical hacking and penetration testing, authentication, authorization, historical hacking incidents, usability, privacy, and security-related law.
- Fall 2024
- FSR, Formal or Statistical Reasoning
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Student has completed any of the following course(s): CS 200 or CS 201 with a grade of C- or better or received a Carleton Computer Science 201 or better Requisite Equivalency.
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CS 338.00 Fall 2024
- Faculty:Jeff Ondich 🏫 👤
- Size:34
- M, WAnderson Hall 329 8:30am-9:40am
- FAnderson Hall 329 8:30am-9:30am
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21 spots held for students in CS Match until 9:00 a.m. May 24
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CS 344 Human-Computer Interaction 6 credits
The field of human-computer interaction addresses two fundamental questions: how do people interact with technology, and how can technology enhance the human experience? In this course, we will explore technology through the lens of the end user: how can we design effective, aesthetically pleasing technology, particularly user interfaces, to satisfy user needs and improve the human condition? How do people react to technology and learn to use technology? What are the social, societal, health, and ethical implications of technology? The course will focus on design methodologies, techniques, and processes for developing, testing, and deploying user interfaces.
- Winter 2025
- FSR, Formal or Statistical Reasoning QRE, Quantitative Reasoning
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Student has completed any of the following course(s): CS 200 or CS 201 with a grade of C- or better or received a Carleton Computer Science 201 or better Requisite Equivalency.
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CS 344.00 Winter 2025
- Faculty:Jean Salac 🏫 👤
- Size:34
- M, WWeitz Center 235 9:50am-11:00am
- FWeitz Center 235 9:40am-10:40am
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CS 347 Advanced Software Design 6 credits
This course helps students to strengthen their ability to design modular, extensible and maintainable software. The focus of the course is on the design of modern cloud applications. Students will learn how to decompose complex applications into a set of back-end services, develop and debug these services, and deploy them in the cloud. This class is structured around a large project that will be extended over the course of the term.
- Spring 2025
- FSR, Formal or Statistical Reasoning
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Student has completed any of the following course(s): CS 257 with a grade of C- or better or received a Carleton Computer Science 257 Requisite Equivalency.
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CS 348 Parallel and Distributed Computing 6 credits
As multi-core machines become more prevalent, different programming paradigms have emerged for harnessing extra processors for better performance. This course explores parallel computation for both shared memory and distributed parallel programming paradigms. In particular, we will explore how these paradigms affect the code we write, the libraries we use, and the advantages and disadvantages of each. Topics will include synchronization primitives across these models for parallel execution, debugging concurrent programs, fork/join parallelism, example parallel algorithms, computational complexity and performance considerations, computer architecture as it relates to parallel computation, and related theory topics.
- Spring 2025
- FSR, Formal or Statistical Reasoning
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Student has completed any of the following course(s): CS 200 or CS 201 with a grade of C- or better or received a Carleton Computer Science 201 or better Requisite Equivalency.
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CS 348.00 Spring 2025
- Faculty:David Musicant 🏫 👤
- Size:34
- M, WAnderson Hall 329 1:50pm-3:00pm
- FAnderson Hall 329 2:20pm-3:20pm
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21 – reserved for REQ: CS 348 Match (Condition Rule) until 3/7/2025
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CS 361 Artificial Life and Digital Evolution 6 credits
The field of artificial life seeks to understand the dynamics of life by separating them from the substrate of DNA. In this course, we will explore how we can implement the dynamics of life in software to test and generate biological hypotheses, with a particular focus on evolution. Topics will include the basic principles of biological evolution, transferring experimental evolution techniques to computational systems, cellular automata, computational modeling, and digital evolution. All students will be expected to complete and present a term research project recreating and extending recent work in the field of artificial life.
- Spring 2025
- FSR, Formal or Statistical Reasoning
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Student has completed any of the following course(s): CS 200 or CS 201 with a grade of C- or better or received a Carleton Computer Science 201 or better Requisite Equivalency.
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CS 364 Computational Modeling and Simulation of Natural Systems 6 credits
Computational models have become a fundamental part of how we make sense of the world, doing everything from economic forecasting to simulating the birth of the universe. But we need to understand how to use models effectively. In this class we’ll explore computational models used across many disciplines, including: agent-based models to prevent forest fires, compartmental models to protect endangered species, N-body models to track the spread of germs from a sneeze, and more. We’ll learn about what problems are (and are not) suited for computational modeling and engage with extensive datasets to evaluate and refine models for practical use.
- Fall 2024
- FSR, Formal or Statistical Reasoning QRE, Quantitative Reasoning
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Student has completed any of the following course(s): CS 200 or CS 201 with a grade of C- or better or received a Carleton Computer Science 201 or better Requisite Equivalency.
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DGAH 220 Creative Coding and Generative AI 6 credits
Generative AI tools such as ChatGPT and GitHub CoPilot are fundamentally reshaping programming practices and workflows, raising questions about the future of code and so-called "prompt engineering," or writing for the machine. This class will situate this moment of potential transformation in the history of literate programming and "natural language" coding using Inform 7, as well as current tools such as ml5.js, an accessible machine learning library. Students will engage this history and future of computational creativity through writing and re-writing code, both with and without generative AI interventions, for conversational bots, interactive fiction, and experimental games.
- Winter 2025
- FSR, Formal or Statistical Reasoning
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Student has completed any of the following course(s): CS 111 with a grade of C- or better or a score of 4 or better on the Computer Science A AP exam or received a score of 111 or better on the Carleton Computer Science Requisite Equivalency exam. .
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DGAH 220.00 Winter 2025
- Faculty:Anastasia Salter 🏫
- Size:25
- T, THLanguage & Dining Center 104 3:10pm-4:55pm
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ECON 285 Computational Economics 6 credits
This course is an introduction to the use of computational methods for the analysis of economic models. After becoming familiar with the programming environment, we will explore the application of computational methods to constrained optimization, econometric estimation, and calibrating, solving, and simulating static and dynamic economic models.
Previous elective courses involving mathematical modeling in economics recommended.
- Fall 2024
- QRE, Quantitative Reasoning SI, Social Inquiry
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Student has completed any of the following course(s): ECON 110 with a grade of C- or better or received a score of 5 on the Macroeconomics AP exam and ECON 111 with a grade of C- or better or received a score of 5 on the Microeconomics AP exam OR has received a score of 6 or better on the Economics IB exam.
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ECON 285.00 Fall 2024
- Faculty:Anthony Priolo 🏫
- Size:25
- M, WWillis 203 12:30pm-1:40pm
- FWillis 203 1:10pm-2:10pm
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MATH 271 Optimization 6 credits
Optimization is all about selecting the "best" thing. Finding the most likely strategy to win a game, the route that gets you there the fastest, or the curve that most closely fits given data are all examples of optimization problems. In this course we study linear optimization (also known as linear programming), the simplex method, and duality from both a theoretical and a computational perspective. Applications will be selected from statistics, economics, computer science, and more. Additional topics in nonlinear and convex optimization will be covered as time permits.
- Spring 2025
- FSR, Formal or Statistical Reasoning
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Student must have completed any of the following course(s): MATH 134 or MATH 232 AND MATH 120 or MATH 211 with a grade of C- or better or equivalents.