DS 4400 - Spring 2026

Course: DS 4400 — Machine Learning and Data Mining I
Term: Spring 2026
Instructor: Zohair Shafi
Email: shafi.z [at] northeastern [dot] edu (Please make sure to add [sp26_ds4400] in the subject line)
Meeting Times: Monday and Wednesday | 02:50 PM - 04:30 PM
Location: Snell 033
Office Hours:

• Zohair Shafi | 1:30PM - 2:30 PM | Monday and Wednesday (Location: EL 311)
• Wanrou Yang | 1:30 PM - 3:00 PM | Tuesday (Location: TBD)
• Zaiba Amla | 1:00 PM - 2:30 PM | Wednesday (Location: 304 Kariotis)

This course provides a broad introduction to machine learning with a focus on fundamental algorithms for supervised learning. Topics include regression, linear and non-linear classification, ensemble methods, and deep learning. Students will gain practical experience implementing algorithms, evaluating models, and understanding the trade-offs involved in real-world applications.

The course also introduces ethical considerations in machine learning, including fairness, transparency, and responsible use of data and models.

• Probability and statistics
• Calculus
• Linear algebra
• Programming experience in Python or a similar language

Primary text: An Introduction to Statistical Learning with Applications in Python (ISL)
(If the link does not work, download the textbook here)

Additional weekly resources are provided in the schedule below

• Assignments — 50% (12.5% x 8 assignments)
• Midterm Exam — 20%
• Final Exam — 25%
• Class Participation — 5%