[CS61] Introduction to Data Science
This is the first course of CS Data Science Track. This course introduces a collection of powerful tools for data analysis such as Jupiter Notebook, Numpy, Pandas, Matplotlib, Git and more. Students will learn hands-on knowledge on data processing. This course also provides the foundation for the later courses in the data visualization and machine learning.
[CS62] Data Visualization and Statistics
Visualization is one key approach to gaining insight from this mountain of data. It enables the trends and patterns, to be examined and assessed. Data Visualization tools in the Python (Matplotlib) platforms will be covered in the course. Students will also learn the foundation of statistics, probability. They will be given many opportunities to apply theories they’ve learned.
[CS63] Machine Learning Fundamentals
This course is the third course of CS Data Science Track. There is heavy and growing demand for computer scientists who have ‘Machine Learning’ skills. This course will cover the underlying mathematical concepts for a wide variety of Machine Learning methods and algorithms, plus various procedures used to assess the value and validity of them.
[CS64] Machine Learning Research Projects
This course is the final course of CS Data Science Track. This course is designed to challenge students with real-world machine learning problems. The instructor will introduce several open dataset competitions on real world issues that current data scientists are trying to solve in the areas of government, health, and science. Instructors will guide students to explore and build predictive models.