Artificial Intelligence for all

Summer School - Online / Tailor-made
July 24 - July 29, 2023

International Polytechnic Summer School 2022 will be held in 2 available options:

Option 1 – online.

Option 2 – tailor-made. We may also arrange a tailor-made on-campus program for a group of minimum 10 students.

Do you want to go deeper to machine learning? Join this interseasonal course!

Computer Modeling and Simulation for Engineers
Computer Modeling and Simulation for Engineers
  • Brief description

    Artificial Intelligence (AI) became one of the most popular and influential areas of technologies at the beginning of the XXI century.

    It passed a long way from the first steps (back in the 50s) to become an essential part of modern life. Today's immense computing power and processing too much data, strengthen the importance of the AI and its subfields. Nowadays, we are living in a world where AI plays an unexceptionally important role. To adapt today's fast and growing technology and development, any specialist in any area needs to know the essentials of such a comprehensive subject.
Online lectures will be delivered synchronized as live talk with professors and groupmates. Records of classes will be available on SPbPU platform for 1 month after the course end.

Duration: 1 week

ECTS credits: 2.0

Participation fee: 16 200 RUB

Upon successful completion of the course students will receive hard copies of certificates with ECTS credits mailed by post.

Deadline for registration: July 07, 2022

The course is an introduction for the “Machine Learning: Theory and Application” summer program. The participants will get a certificate with 6 ECTS credits, if they take two courses in a row.

  • Entrance requirements
    • • Good command of English. All classes and extracurricular activities are carried out in English. Knowledge of the Russian language is not required;
    • • Applicants are expected to have at least 1 year of University level studies.


  • Course description

    In this course, you will learn:

    • • Meaning of AI terminology (computer vision, data science, machine learning, deep learning etc.)
    • • Historical review of AI area.
    • • Review of modern AI applications and approaches.
    • • Disciplines in relation with AI - ML and Data science project workflow
    • • Review of Technical tools and platforms for AI
    • • Basic ideas behind Supervised and Unsupervised learning

The detailed course description for ECTS credits transfer at your home university:

AI for All Descriptor SS22.pdf

Professors and lecturers:

  • Ogul Unal - PhD, Institute of Computer Science and Technology, SPbPU; M-com Search Engine Optimization specialist”;
  • Nikita Kudryashov – PhD, Institute of Computer Science and Technology, SPbPU; Senior Data Scientist, Rubbles company.


Department of International Educational Programs