Skip to main content
Back
Compton College

CSCI108 - Foundation of Data Science

Course Description

This course examines the foundation of data science from three perspectives: interferential thinking, computational thinking, and real-world relevance. The course combines programming skills and statistical inference to ask questions and explore problems encountered in real-world datasets, from multiple fields of study, career paths, and everyday life. It also delves into social and legal issues surrounding data analysis, including issues of privacy and data ownership.

Transfer Information

Set your college to see transfer options.

Tuition & Fees

Tuition and mandatory fees only. Financial aid may apply. Please contact your local Financial Aid Office for details.

Location

Online

Units

4.0 units

Course Sections

Spring 2026

Apr 18 to Jun 12
section: 30544
Format:
Time: TBA
Professor(s): Jose Manuel Martinez
Live Seat Count: 10 available seats - (about 6 hours ago)
Section notes:
This course examines the foundation of data science from three perspectives: interferential thinking, computational thinking, and real-world relevance. The course combines programming skills and statistical inference to ask questions and explore problems encountered in real-world datasets, from multiple fields of study, career paths, and everyday life. It also delves into social and legal issues surrounding data analysis, including issues of privacy and data ownership.
Open

Fall 2025

Oct 18 to Dec 12
section: 70606
Format:
Time: TBA
Professor(s): Jose Manuel Martinez
Live Seat Count: 16 available seats - (3 months ago)
Section notes:
This course examines the foundation of data science from three perspectives: interferential thinking, computational thinking, and real-world relevance. The course combines programming skills and statistical inference to ask questions and explore problems encountered in real-world datasets, from multiple fields of study, career paths, and everyday life. It also delves into social and legal issues surrounding data analysis, including issues of privacy and data ownership.
Already Started