Course Description
- Math 108 Foundations of Data Science combines an introduction to inferential statistics with the fundamental skills and concepts of computer programming, using Python and Jupyter notebooks for hands-on experience in analyzing datasets. Additionally, the course investigates ethical issues surrounding Data Science such as algorithmic bias.
- Math 108 is modeled after UC Berkeley’s popular Data 8 course, and it articulates with it. So this course transfers to UC Berkeley in place of Data 8.
- This is a 5-unit class, so it is expected of the average student to spend approximately 15 hours per week on the course material for this class, including class time, reading, homework, studying, etc.
- The digital textbook Inferential Thinking will be offered at no additional cost thanks to Professors Ani Adhikari and John DeNero at UC Berkeley.
- Course website: Math 108
Prerequisites
- The only prerequisite knowledge assumed is algebra: you need to be comfortable with order of operations, variables and functions from algebra.
Materials
- https://ccsf.cloudbank.2i2c.cloud/hub/login?next=%2Fhub%2F