Education: Teach the Hard Stuff, Not the Job Spec

Evgeny Sokolov's path runs from a small town and an informatics competition to Moscow State University, machine learning, and Yandex. He began teaching after graduation and later made education his primary work. At HSE, Evgeny builds Computer Science programs and teaches classical machine learning.

The episode contrasts two views of education. One derives skills from employer tasks; the other provides foundations and the ability to learn future tools. Companies add courses and internships. Some students optimize for an early career, while others seek research and extra challenge, so they need different paths.

A curriculum is a product: every required course should explain why it belongs and where it matters later. Practical context is useful before a tool, but foundations cannot be reduced to today's stack. Soft skills, system design, and operations are better learned through engineering situations, incident simulations, and decision reviews.

Teachers include academic mathematicians, researchers, practitioners, recent graduates, and education organizers. Alumni return to continue the knowledge-transfer cycle. Evgeny advises choosing interesting work, making each course strong, and sharing the result so motivation, feedback, and new opportunities can compound.