Winter Camp in Machine Learning

Place of Study: online/on-campus

Language: English

Duration: 2 weeks (January 23 - February 3, 2023)

Outcome: Theoretical knowledge and practical skills in the field of machine learning. 3 ECTS, ITMO official certificate

Deadline: on-campus – November 25, 2022; online – December 20, 2022

Fees: 22,000 RUB


Program description

The camp covers various topics in the field of modern machine learning. Participants will learn the principles of machine learning, gain experience in working with neural networks, and become familiar with ML models, their selection, and optimization. Students are expected to know at least one programming language at an intermediate level and be familiar with the foundations of higher mathematics and probability theory.

Who can apply?

  • Students with programming language skills (Python / C++/ Java) 
  • Students proficient in English language (B1 and higher)

What will you get?

  • ITMO’s official certificate, 3 ECTS
  • Teacher’s assistance during the practical classes 
  • Comprehensive experience in machine learning
  • Practical skills in neural networks optimization
  • Networking
  • Additional points when applying for ITMO’s Master’s programs

What do school fees include?

  • Registration and tuition
  • Virtual tour around St. Petersburg
  • Online cultural tour
  • All taxes
  • Online materials

Why choose ITMO?

Camp schedule

  • Monday – Introduction to Machine Learning
  • Tuesday – Basic Models
  • Wednesday – Linear Models. Support Vector Machine
  • Thursday – Probabilistic Classifiers. Trees and Ensembles
  • Friday – Model Selection and Optimization
  • Monday – Clustering
  • Tuesday – Introduction to Neural Networks. Neural Networks and Optimization
  • Wednesday – Convolutional Neural Networks. Recurrent Neural Networks
  • Thursday – Dimensionality Reduction
  • Friday – Noise Filtering and Missing Values Completion
The program includes one lecture and one practice class held every day from 11.00 to 15.00 (Moscow time, GMT +3)