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Academic Catalog 2025-26

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Your search for courses · during 25FA, 26WI, 26SP · taught by ealexander · returned 4 results

  • CS 111 Introduction to Computer Science 6 credits

    This course will introduce you to computer programming and the design of algorithms. By writing programs to solve problems in areas such as image processing, text processing, and simple games, you will learn about recursive and iterative algorithms, complexity analysis, graphics, data representation, software engineering, and object-oriented design. No previous programming experience is necessary.

    Sophomore Priority section is available

    • Fall 2025
    • FSR, Formal or Statistical Reasoning QRE, Quantitative Reasoning
    • NOT open to students who have completed any of the following course(s): CS 200 or greater with a grade of C- or better.

    • CGSC Core CL: 100 level CS Required for Major DGAH Skill Building No Prerequisites PHYS Addl Recommended STAT Supporting
    • CS  111.02 Fall 2025

    • Faculty:Tanya Amert 🏫 👤 · Eric Alexander 🏫 👤
    • Size:48
    • M, WOlin 310 9:50am-11:00am
    • FOlin 310 9:40am-10:40am
    • Sophomore Priority

  • CS 202 Mathematics of Computer Science 6 credits

    This course introduces some of the formal tools of computer science, using a variety of applications as a vehicle. You’ll learn how to encode data so that when you scratch the back of a DVD, it still plays just fine; how to distribute “shares” of your floor’s PIN so that any five of you can withdraw money from the floor bank account (but no four of you can); how to play chess; and more. Topics that we’ll explore along the way include: logic and proofs, number theory, elementary complexity theory and recurrence relations, basic probability, counting techniques, and graphs.

    • Fall 2025
    • FSR, Formal or Statistical Reasoning
    • Student has completed any of the following course(s): CS 111 with a grade of C- or better or received a score of 4 or better on the AP Computer Science exam or received a Carleton Computer Science 111 or better Requisite Equivalency AND MATH 101 or MATH 111 or greater with a grade of C- or better or greater or received a score of 4 or better on the Calculus AB AP exam or received a score of 4 or better on the Calculus BC AP exam or received a score of 5 or better on the Mathematics IB exam or received a Carleton MATH 111 or better Requisite Equivalency.

    • CL: 200 level CS Required for Major LING Related Field
    • CS  202.00 Fall 2025

    • Faculty:Eric Alexander 🏫 👤
    • Size:28
    • M, WOlin 102 12:30pm-1:40pm
    • FOlin 102 1:10pm-2:10pm
    • 7 seats held for CS Match until the day after rising sophomore (only) priority registration.

  • CS 252 Algorithms 6 credits

    A course on techniques used in the design and analysis of efficient algorithms. We will cover several major algorithmic design paradigms (greedy algorithms, dynamic programming, divide and conquer, and network flow). Along the way, we will explore the application of these techniques to a variety of domains (natural language processing, economics, computational biology, and data mining, for example). As time permits, we will include supplementary topics like randomized algorithms, advanced data structures, and amortized analysis.

    • Spring 2026
    • FSR, Formal or Statistical Reasoning
    • 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.

    • CL: 200 level CS Required for Major MATH Discrete Structures MATH Electives SDSC CS Elective
    • CS  252.01 Spring 2026

    • Faculty:Eric Alexander 🏫 👤
    • Size:28
    • M, WAnderson Hall 329 9:50am-11:00am
    • FAnderson Hall 329 9:40am-10:40am
  • CS 314* Data Visualization (*=Junior Seminar) 6 credits

    Though the wealth of data surrounding us can be overwhelming, we have evolved incredible tools for finding patterns in large amounts of information: our eyes! Data visualization is concerned with turning information into pictures to better communicate patterns or discover new insights, drawing from computer graphics, human-computer interaction, design, and perceptual psychology. In this junior seminar, we will learn different ways in which data can be expressed visually and which methods work best for which tasks, with a particular focus on technical communication. Using this knowledge, we will critique existing visualizations as well as design and build new ones.

    • Spring 2026
    • FSR, Formal or Statistical Reasoning QRE, Quantitative Reasoning
    • 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. Not open to students who have taken CS 314.

    • CGSC Elective CL: 300 level CS Junior Seminar Elective CS Major Electives SDSC CS Elective STAT Elective DGAH Critical Ethical Reflection
    • CS  314*.01 Spring 2026

    • Faculty:Eric Alexander 🏫 👤
    • Size:16
    • M, WAnderson Hall 223 12:30pm-1:40pm
    • FAnderson Hall 223 1:10pm-2:10pm

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2025–26 Academic Catalog

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Registrar: Theresa Rodriguez
Email: registrar@carleton.edu
Phone: 507-222-4094
Academic Catalog 2025-26 pages maintained by Maria Reverman
This page was last updated on 10 September 2025
Carleton

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507-222-4000

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