CSCI 134
Introduction to Computer Science Fall 2023 (also offered Spring 2024)
Division III Quantitative/Formal Reasoning
This is not the current course catalog

Class Details

This course introduces students to the science of computation by exploring the representation and manipulation of data and algorithms. We organize and transform information in order to solve problems using algorithms written in a modern object-oriented language. Topics include organization of data using objects and classes, and the description of processes using conditional control, iteration, methods and classes. We also begin the study of abstraction, self-reference, reuse, and performance analysis. While the choice of programming language and application area will vary in different offerings, the skills students develop will transfer equally well to more advanced study in many areas. In particular, this course is designed to provide the programming skills needed for further study in computer science and is expected to satisfy introductory programming requirements in other departments.
The Class: Format: lecture/laboratory
Limit: 30;15/lab
Expected: 30/lec
Class#: 1176
Grading: yes pass/fail option, yes fifth course option
Requirements/Evaluation: weekly programming projects, weekly written homeworks, and two examinations.
Prerequisites: none, except for the standard prerequisites for a (QFR) course; previous programming experience is not required
Enrollment Preferences: if the course is over-enrolled, enrollment will be determined by lottery.
Unit Notes: Please see the Computer Science Department website for more information on selecting an introductory computer science class: https://csci.williams.edu/. Students with prior experience with object-oriented programming should discuss appropriate course placement with members of the department.
Distributions: Division III Quantitative/Formal Reasoning
QFR Notes: This course includes regular and substantial problem sets, labs, and/or projects in which quantitative/formal reasoning skills are practiced and evaluated.
Attributes: COGS Interdepartmental Electives

Class Grid

Course Catalog Archive Search

TERM/YEAR
TEACHING MODE
SUBJECT
DIVISION



DISTRIBUTION



ENROLLMENT LIMIT
COURSE TYPE
Start Time
End Time
Day(s)