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COMPSCIC88C

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COMPSCI C88C - Computational Structures in Data Science

Electrical Engineering and Computer Sciences Undergraduate COE - College of Engineering

Subject

COMPSCI

Course Number

C88C

Department

Electrical Engineering and Computer Sciences

Course Level

Undergraduate

Formerly Known As

Computer Science 88

Course Title

Computational Structures in Data Science

Course Description

Development of Computer Science topics appearing in Foundations of Data Science (C8); expands computational concepts and techniques of abstraction. Understanding the structures that underlie the programs, algorithms, and languages used in data science and elsewhere. Mastery of a particular programming language while studying general techniques for managing program complexity, e.g., functional, object-oriented, and declarative programming. Provides practical experience with composing larger systems through several significant programming projects.

Minimum Units

3

Maximum Units

3

Grading Basis

Default Letter Grade; P/NP Option

Method of Assessment

Written Exam

Instructors

Ball, Culler, DeNero

Repeat Rules

Course is not repeatable for credit.

Credit Restriction Courses. Students will receive no credit for this course if following the course(s) have already been completed.

-

Credit Restrictions.

Students will receive no credit for DATA C88C after completing COMPSCI 61A.

Credit Replacement Courses. Upon passing, students can use the following course(s) to replace a deficient grade for this course.

-

Course Objectives

Develop a foundation of computer science concepts that arise in the context of data analytics, including algorithm, representation, interpretation, abstraction, sequencing, conditional, function, iteration, recursion, types, objects, and testing, and develop proficiency in the application of these concepts in the context of a modern programming language at a scale of whole programs on par with a traditional CS introduction course.

Student Learning Outcomes

Students will be able to demonstrate a working knowledge of these concepts and a proficiency of programming based upon them sufficient to construct substantial stand-alone programs.

Cross-Listed Course(s)

Formats

Laboratory, Lecture, Supplement

Term

Fall and Spring

Weeks

15 weeks

Weeks

15

Lecture Hours

2

Lecture Hours Min

2

Lecture Hours Max

2

Lecture Mode of Instruction

In Person, Online

Laboratory Hours

2

Laboratory Hours Min

2

Laboratory Hours Max

2

Laboratory Mode of Instruction

In Person, Online

Supplement Hours Max

1

Supplement Mode of Instruction

In Person, Online

Outside Work Hours

5

Outside Work Hours Min

5

Outside Work Hours Max

5

Term

Summer

Weeks

8 weeks

Weeks

8

Lecture Hours

4

Lecture Hours Min

4

Lecture Hours Max

4

Lecture Mode of Instruction

In Person, Online

Laboratory Hours

4

Laboratory Hours Min

4

Laboratory Hours Max

4

Laboratory Mode of Instruction

In Person, Online

Supplement Hours Max

2

Supplement Mode of Instruction

In Person, Online

Outside Work Hours

10

Outside Work Hours Min

10

Outside Work Hours Max

10