Class Schedule

• Description: Introduction to the fundamental concepts and computational skills needed to understand and analyze data arising from real-world phenomena. Topics include key data science concepts such as correlation vs. causation, randomness, sampling, uncertainty, predictive models, and classification. Using a tool such as Jupyter notebooks, students write code for transformation and use of data tables, simulation models, and A/B testing.
• Prerequisite:
• Corequisite:
• Advisory: Advisory: Students will benefit from some experience with computer programming or statistics; demonstrated proficiency in English by placement via multiple measures OR through an equivalent placement process OR completion of ESLL 125 & ESLL 249.
• Repeatability: Not Repeatable.
• Hours: 4 hours lecture per week, 2 hours lab per week. 72 hours total per quarter.
• Foothill GE Area:English
• Transferability: Both
• Transfer GE: Information regarding how this course is applied toward CSU GE/Breadth or IGETC certification is available at:
• Foothill Transfer GE Guide

Department Note: