The course gives a general overview of history, theoretical basis and technological stack for what we now call “artificial intelligence” (AI). Today AI is not only a research area, but also a complex set of exact algorithms, technologies, frameworks, software and services, which can be easily integrated in modern software. In this course students will learn history and major theoretical points and structures of knowledge related to AI. The major goal of the course is to practice contemporary AI technologies and frameworks, including reasoning, natural language processing, computer vision, and machine learning. Working individually and in teams, students will solve a variety of AI problems, both from scratch and using existing solutions.
Here you can find labs, slides and hometasks for the course. Generally you need Anaconda packages to run the code. Specific requirements are specified in comments if any.