This course is designed to familiarize students with the application of machine learning methods in various areas of chemistry. As a result of the training, students will gain an understanding and acquire practical experience in applying machine learning methods to chemical problems. After each practical session, students are given tasks for independent study. At the end of the course, students complete their own research project in a chosen area and defend it. The following is required from the students: - programming skills in any language at the level of a university course; - basic knowledge of linear algebra, statistics, and mathematical analysis. Knowledge of chemistry at the level of a basic university course is also desirable.
Teachers:
Dmitry S. Bezrukov
Education
Ph.D., Faculty of Chemistry
MSU
Areas of Expertise
Computer modeling in chemistry
Alexander K. Pupeza
Education
Faculty of Chemistry
MSU
Areas of Expertise
Machine learning methods in chemistry
Classes are held at the Chemistry Department of Lomonosov Moscow State University (computer classroom 152)
The course program includes 13 sessions, each consisting of 2 periods: 1 lecture and 1 practical session every week
Format: offline
Course start date: February 12, 2025
Classes will be held on Wednesdays from 10:50 to 14:15
Enrollment for the 2025 course is closed
FRIDAYS
09:00–10:30 — period 1
10:40–12:10 — period 2
12:10–13.00 — break
13:00–14:30 — period 3
14:40–16:10 — period 4
Instructor: A. Ganichev
THURSDAYS
09:00–10:30 — period 1
10:40–12:10 — period 2
12:10–13.00 — break
13:00–14:30 — period 3
14:40–16:10 — period 4
Instructor: A. Marakulin
MONDAYS
09:00–10:30 — period 1
10:40–12:10 — period 2
12:10–13.00 — break
13:00–14:30 — period 3
14:40–16:10 — period 4
Instructor: D. Penzar
SATURDAYS
09:00–10:30 — period 1
10:40–12:10 — period 2
12:10–13.00 — break
13:00–14:30 — period 3
14:40–16:10 — period 4
Instructor: I. Konyushok