Course Description

In this course, we study Artificial Intelligence (AI) algorithms and learn intuitive explanations behind them. AI algorithms are the algorithms used for automated decision making and execution. AI algorithms are behind the technologies in scheduling flights, search engines, self-driving vehicles, recommendations systems, navigation systems, robotics, solvers, voice recognition, translation, and so many other complex and advanced problems.

The course assumes students are comfortable with basic concepts in analysis, elementary algebra, elementary probability, statistics, and programming. It is recommended that students have the basic knowledge of linear algebra, the basics of machine learning, and the basics of deep learning, but it is not necessary. We will cover the required material in this course.

Target: This course is targeted to beginning graduate students in Computer Science interested in working in Artificial Intelligence or applying Artificial Intelligence approaches to other areas of Computer Science or interdisciplinary domains. The course should be of interest to graduate students from other STEM disciplines satisfying the prerequisites and interested in learning about Artificial Intelligence.

Course Details


*No late submission would be accepted.

Collaboration Policy

I encourage the students to discuss and exchange ideas about the course materials. The students shall accomplish each of their problem sets, project, midterm, and final individually. No collaboration or discussion prior to the due times.


Extra Resources


In case you observe symptoms or become quarantined or isolated at any point in time during the semester, immediately reach out to the Protect Purdue Health Center, Academic Case Manager, and the Office of the Dean of Students.