Stanislav Protasov graduated from the Computer Science department of Voronezh State University in 2009. In 2013 he defended his PhD thesis devoted to computer vision algorithms. While doing his research he was working as software developer in DHL, Parallels, DataArt and other companies. He was also delivering labs and lectures in Voronezh State University, National Research University Higher School of Economics (HSE) and Moscow Institute of Physics and Technology (MIPT).
In 2015-2017 he worked as a postdoc in the Machine Learning and Knowledge Representation lab of Innopolis University. While working there he supervised students in prize-winning projects related to computer vision. Since 2017 Stanislav has been working in Yandex, and he also delivers lectures at the Computer Science department of Higher School of Economics, and in Innopolis Innopolis University.
The course is designed to create a hands-on experience in the creation of AI systems. It also aims to widen students’ knowledge in the area of AI.
At the end of the course students will:
Know:
-Major approaches to construct AI solutions
-Popular libraries and APIs to solve AI tasks
-Algorithms to construct intelligent agents from scratch
-Basic methods of image processing and machine learning
Be able to:
-Create game playing bots using heuristic approaches
-Implement knowledge databases
-Implement systems with speech processing and generation
-Implement image processing and computer vision solutions
-Perform basic data analysis using machine learning
SKILLS:
- Applied Machine Learning
- Multiprocessor Computing
- Full-stack Development
- Applied Mathematics
DATE: 18 Feb - 8 Mar, 2019
DURATION: 3 Week
LECTURES: 3 Hours per day
LANGUAGE: English
LOCATION: Barcelona, Harbour.Space Campus
COURSE TYPE: Offline
WHAT YOU WILL LEARN
ABOUT STANISLAV
HARBOUR.SPACE
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.
STANISLAV PROTASOV
HARBOUR.SPACE UNIVERSITY
DATE: 18 Feb – 8 Mar, 2019
DURATION: 3 Weeks
LECTURES: 3 Hours per day
LANGUAGE: English
LOCATION: Barcelona, Harbour.Space Campus
COURSE TYPE: Offline
All rights reserved. 2017
COURSE OUTLINE
Session 1
AI history and perception. Implementing simple intelligent agent
Session 2
AI as a function: algorithms of AI (search algorithms, A*, minimax, …)
Session 3
Reasoning. Production systems and Bayesian networks
Session 4
Language processing: syntactic analysis
ARTIFICIAL INTELLIGENCE
ARTIFICIAL INTELLIGENCE
BIBLIOGRAPHY