Machine Learning: Theory and Application (St. Petersburg - Moscow) — Winter School
JANUARY 27 — FEBRUARY 07, 2020
Do you want to go deeper to machine learning and visit two Russian capitals? Join this Winter School!
The outstanding Winter School “Machine Learning theory and application” is a joint program with MISIS university in Moscow and is cut out for those who are keen on machine learning applications and development.
We welcome students to come to the largest cities in Russia. Moscow is a business center, while Saint-Petersburg is the cultural heart of Russia. You will definitely enjoy staying in Saint-Petersburg and Moscow and having fun while winter holidays
The course introduces students to the theoretical foundations of machine learning and data science, as well as to the solution of real business problems with the help of computer vision, classification and regression algorithms. The optimal balance between theory and practice provides both a good foundation and the ability to apply knowledge in practice
Arrival: Jan 25 – 26, 2020
- Jan 27 – Feb 01, 2020 (in St. Petersburg)
- Feb 02 – transportation from St. Petersburg to Moscow
- Feb 03 – Feb 07, 2020 (in Moscow)
Departure from Moscow: Feb 08 – 09, 2020
Duration: 2 weeks
ECTS credits: 4.0
Participation fee: 555 euro
Participation fee includes tuition fee, study materials, visits to companies and cultural program.
The cultural program includes:
- Excursion to the Hermitage, one of the world’s largest and oldest museums of fine art;
- Pub Quiz;
- Full-day Wintry Event with sleigh riding and skating (optional for extra price).
The extracurricular activities in Moscow are to be announced yet.
Deadline for registration:
- for non-EU citizens: November 18, 2019
- for EU, Iranian and Indian citizens, citizens of visa-free countries: December 16, 2019
- Good command of English. All classes and extracurricular activities are conducted in English. Knowledge of the Russian language is not required;
- Applicants are expected to have at least 1 year of University level studies.
Request the application form via e-mail address: email@example.com
The course content includes:
- Machine learning applications review;
- ML algorithms classification. Mathematical foundations;
- ML Tools, Libraries, frameworks and best practices review;
- Basics of ML development, using Python language (No Python skills are needed, just some basics of programming);
- Practice. Prediction of manufacturing parameters using ML algorithms;
- Model Predictive Control (MPC) basics;
- Practice. Applying MPC algorithm, based on manufacturing parameters prediction.
Professors and lecturers:
- Potekhin V.V. – Ass. Prof., School of Cyberphysical Systems and Control
- National University of Science and Technology MISIS