PEER COLLABORATION IN COMPUTER SCIENCES (WES-CS)

Name: PEER COLLABORATION IN COMPUTER SCIENCES (WES-CS)
Availability: OutOfStock
Rating: 4.9 (1064 reviews)

COMPSCI 304

과목 설명

Interactive opportunity to discuss basic computer science concepts such as programming, including data structures, algorithms, object-oriented programming principles and techniques for efficient coding, testing, and debugging in a smaller setting with peers. Requires concurrent enrollment inCOMP SCI 200,220,252,300,320,354, or400.

선수과목

Consent of instructor

충족 요건

This course does not satisfy any prerequisites.

학점

미보고

개설 시기

미보고

평점

2.16% 과거 데이터 대비

수료율

100%

0.95% 과거 데이터 대비

A 비율

100%

6.19% 과거 데이터 대비

학급 규모

-79.7% 과거 데이터 대비

Cumulative Grade Distribution

강사 (2026 Summr)

다음 사이트의 평점순으로 정렬 Rate My Professors

유사 과목

DIRECTED STUDY IN COMPUTER SCIENCE

COMPSCI 298

Undergraduate directed study in computer sciences.

GRADUATE COOPERATIVE EDUCATION

COMPSCI 702

Apply computer sciences principles in a hands-on, professional setting.

PROGRAMMING I

COMPSCI 200

Learn the process of incrementally developing small (200-500 lines) programs along with the fundamental Computer Science topics. These topics include: problem abstraction and decomposition, the edit-compile-run cycle, using variables of primitive and more complex data types, conditional and loop-based flow control, basic testing and debugging techniques, how to define and call functions (methods), and IO processing techniques. Also teaches and reinforces good programming practices including the use of a consistent style, and meaningful documentation. Intended for students who have no prior programming experience.

INTRODUCING COMPUTER SCIENCE TO K-12 STUDENTS

COMPSCI 402

Work in teams to lead Computer Science clubs and workshops for K-12 students at sites in the Madison area. Design and lead activities to help K-12 students learn computational thinking and computer programming.

PROGRAMMING III

COMPSCI 400

The third course in our programming fundamentals sequence. Covers balanced search trees, graphs, graph traversal algorithms, hash tables and sets, and complexity analysis and about classes of problems that require each data type. Involves design and implementation using high quality professional code, a medium sized program, that demonstrates knowledge and use of latest language features, tools, and conventions. Additional topics may include inheritance and polymorphism; anonymous inner classes, lambda functions, performance analysis to discover and optimize critical code blocks. Introduces industry standards for writing high-quality, maintainable code.