Big Data: Theory and Application

Summer School - Online / Tailor-made
August 1 - August 12, 2022

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 holding nationality of the countries Russia resumed international air and railway service with. The countries listed here.

*The list is regularly updated according to the amending documents of the decree of the Government of the Russian Federation dated 16.03.2020 №635-r.

Would you like to go deeper into big data processing and get acquainted with the students from all over the world? This course was launched specially for you!

Big Data Theory and Application
Big Data Theory and Application
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: 2 weeks

ECTS credits: 4.0

Participation fee: 30 000 RUB

Upon successful completion of the course students will receive hard copies of certificates with ECTS credits (mailed by post in case of the online format of the Summer School).

Deadline for registration: July 19, 2022

  • Entrance requirements
    • • 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;
    • • Linear algebra: vectors, matrices, and their products, derivative;
    • • Probability theory: random events, mathematical expectation, variance;
    • • Basic programming knowledge: Python/R, SOLID, SQL, git, docker.
  • Course description
    • Introduction to Data science
    • • Glossary of big data
    • • Types of data
    • • Structured data
    • • Unstructured data
    • • Data in natural language
    • • Machine data
    •  
    • Working with big data
    • • Data collection
    • • Data preparation
    • • Data research
    • • Modeling and building models
    •  
    • A system for collecting, processing and storing big data
    • • SQL databases
    • • NoSQL databases
    • • Tools for working with big data
    • • Highly loaded systems
    • • Big data processing in practice
    •  
    • Machine Learning
    • • Data preprocessing
    • • Statistical data analysis
    • • Building models
    • • Neural networks
    •  
    • Project work: Development of software for working with big data

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

Big Data: Theory and Application Descriptor SS22.pdf

Professors and lecturers

  • Vyacheslav Potekhin, Associate Professor, PhD.
  • Anton Alekseev, PhD, researcher
  • Daniil Lyadsky, PhD, researcher
  • Vladislav Efremov, PhD, researcher

Professors and lecturers

  • FESTO Group
  • PTC, Inc

Contacts:

Summer and Winter Schools Team