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
Online format: 270 Euro
Hybrid format: 270 Euro + 4000 Rub (non-refundable registration fee for the Letter of Invitation)
Participation fee includes tuition fee, study materials, field trips and cultural program.
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).
- - Online Pub Quiz;
- - Online Interactive Tour to SPbPU Museum;
- - Online broadcasting of excursion to the Hermitage museum;
Cultural program in the Hybrid format is discussed with participants individually.
*All of the listed above activities are planned to take place but in case any of those will have to be cancelled, an alternative event will be offered to participants.
Provided only for the Hybrid or the Tailor-made formats:
- on campus at the university dormitory
- off-campus at partner hostels in the city center
Details of the options and booking procedures will be discussed with each applicant individually.
Deadline for registration
Online format: July 19, 2021
- for EU- or visa-free countries nationals: July 05, 2021
- for non-EU nationals: May 24, 2021
- - 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.
- 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 SS21.pdf
Professors and lecturers
- Vyacheslav Potekhin, Associate Professor, PhD.
- Anton Alekseev, PhD, researcher>
- Daniil Lyadsky, PhD, researcher
- Vladislav Efremov, PhD, researcher
Professors and lecturers
Summer and Winter Schools Team