Sergey Kucheryavskiy
Associate Professor at Section of Chemical Engineering
This course is about how to extract and interpret useful information from experimental data, including large datasets with thousands of samples and variables (e.g. spectroscopic data). It consists of four major sections (blocks). Each block includes several lectures (provided as video sequences using dedicated platform) with examples and live exercises, quizzes and mini-projects, where students can try the discussed methods by solving various problems.
During this course, we will use elements of flipped classrooms and blended learning, often lectures will look more like workshops and seminars. To work effectively, please watch and read all materials provided to each topic before the classes. You will have about three weeks to do this for each part of the course.
The course has 5 ECTS points value. To complete the course and get the points students have to pass a written exam at the end. Details about the exam will be provided during the course and also available via official course description in Moodle.
Basic knowledge of math (statistics, geometry, linear algebra) and experience in R programming as well as general computer skills.
Associate Professor at Section of Chemical Engineering