Big Data: theory and application
JANUARY 18 — 29, 2021
The course is held online
ENJOY A 40% DISCOUNT FOR THE TUITION FEE OF SUMMER ON-SITE PROGRAMS IN 2021*
*Available only for students who will have participated in the online courses of a relevant field of study in winter 2021.
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!
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: 270 Euro
Upon successful completion of the course students will receive hard copies of certificates with ECTS credits mailed by post.
Socio-cultural program of extracurricular activities and networking events are included*:
- Online Interactive Campus Tour;
- Online broadcasting of excursion to the Hermitage museum;
- Online Pub Quiz.
*All of the listed above activities will to take place but in case any of those will have to be cancelled, an alternative event will be offered to participants.
Deadline for registration: January 10, 2021
- 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.
- Linear algebra: vectors, matrices, and their products, derivative,
- Probability theory: random events, mathematical expectation, variance.
- Basic programming knowledge: Python/R, SOLID, SQL, git, docker
Request the application form via e-mail address: email@example.com
- Laptop and fast Internet connection
- IDE JetBrains Pycharm CE, Anaconda 3
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
- Data preprocessing
- Statistical data analysis
- Building models
- Neural networks
Project work: Development of software for working with big data
Professors and lecturers
- Vyacheslav Potekhin, Associate Professor, PhD.
- Anton Alekseev, PhD, researcher
- Daniil Lyadsky, PhD, researcher
- Vladislav Efremov, PhD, researcher
- FESTO Group
- PTC, Inc