Instructor

Prabhu Ramachandran

Semester

4th

Course Difficulty

3 out of 5; 5 being the toughest.

Time Commitment Required

3 out of 5; 5 being 20 hours a week.

Grading Policy and Statistics

Decent. 21% of the students were awarded an AB or above.

Attendance Policy

There was a strict attendance policy of 80%, failing to comply to which would result in a DX grade.

Teaching Style

The professor taught us through slides as well as a reference book which was followed throughout the course.

Tutorials/Assignments/Projects

There were 3 assignments which were distributed across the semester. There was also a project towards the end of the semester. The assignments and project were relevant to what was being taught in the class and asked in the assignments.

Course Importance

This course is an introductory course into the statistically aspects of Machine Learning. It also sets a foundation of Machine Learning and its practical applications. Covers some concepts in detail but does not cover all fundamental concepts in Machine Learning. A little more on the mathematical side of ML. Even the quizzes and exams are straight up probability and statistics question based on ML.

AE 240 Review By: Yash Tangri