IS407: Introduction to Data Science

Spring 2026

Time: Mondays, 1:00 PM - 3:50 PM
Location: 13 Sch of Info Sciences Bldg

[Canvas] [Syllabus]

Course Description

This course introduces students to data science approaches that have emerged from recent advances in programming and computing technology. They will learn to collect and use data from a variety of sources. Supervised and unsupervised statistical learning techniques made possible by recent advances in computing power will also be covered. This course is very computer-oriented, so it is very important to take the time outside of class to learn by doing, to explore the software being covered in class, and practice new skills on real data sets in the homework assignments and final project. The course will include computer exercises using Python and other relevant computing languages.

Pre- and Co-requisites

No prerequisites for this course. The course will also be taught using Anaconda and Python, so prior Python experience is helpful.

Course Materials

• An Introduction to Statistical Learning, by James, Witten, Hastie, Tibshirani (ISL).
• Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2, by Raschka, Sebastian. & Mirjalili, Vahid (PML).

Assignments and Methods of Assessment

• Home assignments 45%
• Final project 45%
• Class participation 10%

Instructor

Yaoyao Liu
Office location: Room 5125, 614 East Daniel St
Email: lyy@g.illinois.edu
Office Hours: By appointment