Applied Computer Science

About

Participants of the stream Applied Computer Science will learn about the most effective machine learning and artificial intelligence techniques. What is more important, you'll learn not only theoretical bases of ML and AI, but also will acquire practical know-how needed to quickly and power. This year stream will first cover data retrieval and storage techniques as a part of data manipulation, then will cover basic methods of statistical analysis, data mining and machine learning. Lectures will be given on data visualization and tools for data analysis. This program will also investigate various real-world applications of these techniques, including image processing, bioinformatics, social science, and natural language processing. As this stream focuses on ”learning by doing” principle, a number of training exercises applying theoretical knowledge are planned.fully apply those techniques to solve new problems.

Course leader

Mr. Konstantin Tretyakov, MSc., Department of Computer Science, the University of Tartu, Estonia. Mr. Dmytro Prylipko, MSc., Faculty of Electrical Engineering and Information Technology Institute for Electronics, Otto-von-Guericke University Magdeburg, G

Target group

Students and young scientists under 35 years old

Course aim

What is proposed?
This year stream will be structured in the following way: first we will cover data retrieving, compression and storage techniques as a part of data manipulation phase, then we will look into some basic methods of statistical analysis, data mining and machine learning. Some lectures will be given on data visualisation and tools for data analysis. We will also study interesting real-world applications of above techniques: image processing, bioinformatics, social science, natural language processing etc. As the stream stands for ‘learning through doing’ principle, a number of practices for applying gained theoretical knowledge and training skills is planned.

Fee info