Search Results
Your search for courses · during 25SP · tagged with CS Major Electives · returned 7 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 – Data Structures with Problem Solving or CS 201 – Data Structures with a grade of C- or better or equivalent.
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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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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 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.
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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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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 – Software Design with a grade of C- or better or equivalent.
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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 – Data Structures with Problem Solving or CS 201 – Data Structures with a grade of C- or better or equivalent.
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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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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 – Data Structures with Problem Solving or CS 201 – Data Structures with a grade of C- or better or equivalent.
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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 – Linear Algebra with Applications or MATH 232 – Linear Algebra AND MATH 120 – Calculus 2 or MATH 211 – Multivariable Calculus with a grade of C- or better or equivalents.