Data Science Degree Program
We are developing a Data Science AS Degree at SRJC. The courses in the program are:
Required
| CS 8 or MATH 8 - Foundations of Data Science | 4 units |
| CS 10B - Programming Concepts and Methodologies 1 | 4 units |
| CS 10C - Programming Concepts and Methodologies 2 | 4 units |
| MATH 1A - Calculus, First Course | 5 units |
| MATH 1B - Calculus, Second Course | 5 units |
| Math 1C - Calculus, Third Course, Multivariable | 5 units |
| MATH 5 - Introduction to Linear Algebra | 4 units |
Recommended Electives
| CS 81.41 - Python Programming | 3 units |
| Math 15 - Elementary Statistics | 4 units |
| MATH 4 - Discrete Mathematics | 4 units |
Once the UCs and CSUs complete their curriculum work, we will convert the JC degree to a Transfer Degree.
For more information on that work, see the UC data science advisory group working document here:
https://docs.google.com/document/d/1bAC5yUJSYDUVR7YdAqlypJF9t5MJh0ca-wfnZ2GZNkY/.
CS 8: Foundations of Data Science Course
In this course, students will study the Foundations of Data Science from three perspectives: inferential thinking, computational thinking, and real-world relevance. Given data arising from some real-world phenomenon, how does one analyze that data so as to understand that phenomenon? The course teaches critical concepts and skills in computer programming and statistical inference, in conjunction with hands-on analysis of real-world datasets, including economic data, document collections, geographical data, and social networks. It delves into social issues surrounding data analysis such as privacy and design.
Student Learning Outcomes
At the conclusion of this course, the student should be able to:
- Employ foundational programming concepts to explore and analyze datasets.
- Apply foundational data science to explore and analyze datasets.
- Analyze real-world data sets using a modern programming language, problem decomposition, and code design strategies.
- Identify limitations and issues surrounding data analysis in terms of bias, ethics, establishing causality, and privacy.
Contact Information
Data Science
Computer Studies Department
Michael McKeever
Department Chair
mmckeever@santarosa.edu
(707) 778-3960
Maggini Hall 3rd Floor