Master's program

Artificial Intelligence and Data Engineering

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ABOUT PROGRAM

The program is aimed at providing students with real-industry Data Science skills: defining a business problem, presenting work results, solution implementation and reporting. The program is focused on Machine Learning approaches.

The program is offered to candidates interested in Research & Development, with fundamental knowledge in mathematics and skills in information search and reporting. The program enables graduates to respond to professional responsibilities that include preliminary data processing, big data management, application of machine learning algorithms, data analysis and reporting.

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Course information

Duration: 2 years of full-time studies.

Start of studies: mid-August

Language of tuition: English

Program

The program is designed for students interested in:

• development of modern machine learning models

• applying modern machine learning approaches to scientific and engineering problems

• understanding received data

• data analysis

• research activities in the field of data analysis and/or machine learning

Project work

Most of the courses are accompanied by projects that allow students to apply learned algorithms on real data sets.

Thesis

At the end of studies students prepare their thesis work by conducting scientific research.

CuRriculum

Click here to learn more about curriculum.

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PRACTICE

Artificial Intelligence Centre (AIC) - one of the six technology centers of Innopolis University.

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Faculty

Adil Khan

Professor, Head of the Laboratory of machine learning and knowledge representation

Courses taught: Machine Learning

Directions of scientific work:

• GAN training with a fraction of data

• Domain adaptation

• Data warehouse

• High-performance computing

Giancarlo Succi

Full Professor, Dean of the Faculty of Computer Science, head of the Laboratory of Industrial Production of Software

Courses taught: Empirical Methods, Advanced Statistics

Directions of scientific work:

• Analysis of the work of the brain while programming

• Analysis of software engineering metrics

• Profiling domains for exploring product features

• Interactive guide for agile/lean software development

Evgene Zuev

Senior Professor; the Laboratory of operating systems, programming languages and compilers construction

Courses taught: Software Design with Python

Directions of scientific work:

• Compiler construction

• Simulation systems

Andrey Sadovykh

Assistant Professor, the Laboratory of Industrial Production of Software

Courses taught: Managing Software Development

Directions of scientific work:

• Natural language processing for cyber-security requirements analysis

• Object-oriented requirements and cyber-security testing

Yaroslav Kholodov

Associate Professor, Head of the Laboratory of Data Analysis and Bioinformatics

Courses taught: High-dimensional Data Analysis

Directions of scientific work:

• Computational modeling in molecular biology

• Traffic modeling

Artem Kruglov

PostDoc, the Laboratory of Industrial Production of Software

Courses taught: Empirical methods

Directions of scientific work:

• Automatic classification of user activities by application in use

• Automatic calculation of code/project metrics from open-source repositories

• User presence identification based on I/O signal analysis

Stanislav Protasov

Assistant Professor, the Laboratory of machine learning and knowledge representation

Courses taught: Advanced Information Retrieval

Directions of scientific work:

• Quantum Machine Learning

• Visual tools for textual dataset exploration

• Computer vision

• Data Structures

CAREER PROSPECTIVE

Our graduates hold the following positions:

• machine learning developer (middle/senior level)

• data scientist

• data analysis specialist

• analyst

• data engineer

And hold these positions in the following companies:

• Yandex

• Tinkoff

• ICL

• Kontur

• S7

Admission campaign 23/24

30

grant places available

to 480 USD

monthly scholarship

from 2500 USD

tuition fee

How to enroll?

APPLY FOR GRANT

Register in the admissions portal account, fill in an application form with all mandatory fields, take tests and click “SUBMIT” to complete the application.

Selection criteria at this stage:

— Technical university degree

— Expertise in mathematics (entry tests)

— English language proficiency (intermediate level or higher)

Practical experience in data analysis will be an advantage.

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GO THROUGH THE CONTEST

Successful applications are selected for further consideration. We would like to see the candidates with strong expertise in physics and mathematics, programming, which can be applied in solving real practical tasks. Knowledge of robotics is not compulsory.

Selection criteria at this stage:

— Strong fundamentals in mathematics (linear algebra, mathematics)

— Programming skills (Python)

— English language proficiency

— Motivation and personal skills

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GO THROUGH THE CONTEST

Successful applications are selected for further consideration. We would like to see the candidates with strong expertise in physics and mathematics, programming skills, and ability to implement them at solving practical tasks. Knowledge of robotics is not compulsory.

Selection criteria at this stage:

— Strong fundamentals in mathematics (linear algebra, mathematical analysis, differential equations, probability theory, statistics)

— Understanding of physics and its processes (mechanics)

— Programming skills (low level or/and high-level programming languages)

— English language proficiency

WHAT DOES THE MAIN ROUND OF THE CONTEST CONSIST OF?

01. Online testing

1. Professional testing:

- Mathematical test (mathematical analysis, linear algebra, discrete mathematics, probability theory and statistics)

- Algorithms and data structures, programming.

2. English language testing

You can confirm English proficiency in one of the following ways:

- providing an international English language test certificate (IELTS, TOEFL (including TOEFL iBT Special Home Edition)),

- taking IU extended English test (free of charge), OR

- providing an official letter from your School/University stating that the studies were delivered in English.

02. Interview with the professor

This is a technical interview with questions on practical experience, on the basics of Computer Science (CS): algorithms, data structures, theory of automata, networks, etc.

03. Interview with HR expert

This interview aims to identify your personal qualities. During the conversation, you may be asked questions about your motivation, study and work, and others.

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GET THE OFFER

Get the offer by email and confirm it. Provide all enrollment and visa documents, pay tuition fee (for Partial Grant candidates) and come to Innopolis in mid-August.

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Students life

Documents

FAQ

CONTACT

Admissions Committee

+7 (843) 203-92-53 (ext. 254)

admissions@innopolis.ru

Postal Address

420500 Innopolis, Russia 1, Universitetskaya Str.

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Innopolis University

Master's program

Artificial Intelligence and Data Engineering

ABOUT PROGRAM