I love teaching! Over the last several years I've taught a variety of courses in engineering and computer science, ranging topics in control theory, signal processing, statistics, optimization, programming and AI. I view teaching as an opportunity to interact with curious students, and to enrich their learning and growth processes. 

This year (2023-2024) on both semesters I will be teaching Artificial Intelligence (89-570) at Bar-Ilan University.

Although I am a strong proponent for open-sourcing academic materials, the universities I teach in utilize a closed system (Moodle) for enlisted students, so the materials are not openly available. Fortunately, there are numerous other (probably better) open sources on The Web. For instance, freely open and curated online materials for introductory statistics are available at OpenStax (which is a truly wonderful educational project, check it out!). In addition, I do have recorded lectures from the last two years, available in my YouTube channel. Students of current (and past!) courses are more than welcome to contact me for assistance and advice.

My personal experience, both from participating in classes and teaching them at the academia, has taught me that knowing the course material and having good will, although essential, are typically not enough for doing a good job as a teacher. Adding value to students (on top of the course's written material) also requires preparation, experience and willingness to learn from others. It can take quite some time to reach a high level, where student feedback testifies of satisfaction and interest (personally, I'm still working on it 😃). It is thus especially important for young professionals to learn from the experience of others. I strongly recommend to participate in workshops that are regularly held at universities, intended both for graduate students and seasoned academic staff. I sympathize with the teaching philosophy of Aswath Damodaran, and find his presentation on teaching concrete and helpful.