Modeling and Learning in Data Science

Fall 2023 @ Illinois

Welcome to the webzone for the Fall 2023 semester of CS 307, Modeling and Learning in Data Science, at the University of Illinois Urbana-Champaign. CS 307 is an undergraduate machine learning course that is appropriate for students pursing any of the X + DS programs at Illinois.

If this is your first visit, we recommend reading the Getting Started page which will help you better navigate this website and the course in general. If you’re returning, use this link to navigate to the current week.

After this course, students are expected to be able to:

• Identify supervised (regression and classification) and unsupervised (clustering) learning problems.
• Understand the bias-variance tradeoff and its relationship to model complexity and overfitting.
• Validate and select machine learning models and their parameters using techniques such as cross-validation.
• Prepare and process data for use with machine learning methods.
• Formulate practical, real-world problems as machine learning problems.
• Evaluate effectiveness of machine learning methods when used as a tool for data analysis or as a component of a system.
• Implement simple machine learning methods from scratch using Python’s numpy.
• Apply machine learning methods using frameworks such as Python’s scikit-learn and pytorch.

Welcome! We hope you enjoy the course!