UC Berkeley’s pathbreaking entry-level course on the Foundations of Data Science (Data 8) is launching on edX on April 2. This makes the fastest-growing class in UC Berkeley history available to everyone. Foundations of Data Science teaches computational and inferential thinking from the ground up. It covers everything from testing hypotheses, applying statistical inferences, visualizing distributions and drawing conclusions—all while coding in Python and using real world data sets.
The course is taught by award-winning Berkeley professors and designed by a team of faculty working together across Berkeley’s Computer Science and Statistics Departments, led by RISE faculty Michael Jordan.
The three 5-week online courses cover:
- Foundations of Data Science: Computational Thinking with Python, starting on April 2, teaches the basics of computational thinking, an essential skill in today’s data-driven world, using the popular programming language Python.
- Foundations of Data Science: Inferential Thinking by Resampling teaches how to use inferential thinking to make conclusions about unknowns based on data in random samples.
- Foundations of Data Science: Prediction and Machine Learning teaches how to use machine learning, with a focus on regression and classification, to automatically identify patterns in data and make better predictions.
Each course is free on edX, and the whole sequence is available as a Foundations of Data Science Professional Certificate Program.
More details are on the Division of Data Sciences website.