Big Data: Theory and Application

Winter School - Online/Hybrid
January 17 - January 28, 2022

The course will be held online but 3 participation options are available for certain individuals:

Option 1 - online.

Option 2 - hybrid. Russia resumed international air and railway service with the countries listed here.

Therefore, a hybrid format of the course is offered to students holding citizenship of the states mentioned in the list – you can join the online course for 270 euro (+4000 Rub for reg. fee) but come to St. Petersburg to take touristic advantages for the duration of the program and attend online classes at your dormitory/hostel.

If you choose Option 2, just apply for the online course here and inform us on your choice via email to get further instructions.

Option 3 – 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.

 

Would you like to go deeper into big data processing and get acquainted with the students from all over the world staying home? 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:

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 Winter School).

  • Cultural program

    Online format:*

    • - 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.

Accommodation

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.

 

Big Data Theory and Application
Big Data Theory and Application

Deadline for registration

Online format: December 22, 2021

Hybrid format:

- for EU- or visa-free countries nationals: December 01, 2021

- for non-EU nationals: November 01, 2021

If you have taken the Data Analytics interseasonal course, there are no entrance requirements for you but the last two ones.

  • Entrance requirements
    • - Linear algebra: vectors, matrices, and their products, derivative;
    • - Probability theory: random events, mathematical expectation, variance;
    • - Basic programming knowledge: Python/R, SOLID, SQL, git, docker;
    • - 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.
  • 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 WS21.pdf

 

Professors and lecturers

  • Anton Alekseev, PhD, researcher (SPbPU);
  • Vladislav Efremov, PhD, researcher (SPbPU).

 

Program partners

  • FESTO Group
  • PTC, Inc

 

Contacts:

Department of International Educational Programs