Data science and artificial intelligence

Master's program

Data Analysis and Artificial Intelligence


About program

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

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

You are welcome to watch webinar recording to get more information about the program.

How to enroll?


Place an application

Selection criteria:

— A technical university degree 

— Knowledge of one or several programming languages English language 

— English language Proficiency (Intermediate level or higher) 

Register in admissions portal account, fill in application form with all the mandatory fields, take online tests and press submit to complete an application



Proceed to further selection rounds

Successful applications are selected for further consideration.

Selection criteria:   

— Expertise in mathematics and programming 

— Skilled at programming in Python (preferred) or other programming language 

— Basic knowledge of algorithms and data structure, linear algebra, probability theory, mathematical statistics, programming; 

— English language proficiency (IELTS test format) 

Learn more


Receive scholarship offer/discount offer/acceptance letter

- Scholarship students: Receive the interview results and the scholarship offer. 

Non-Scholarship students: Pay tuition fee (if you receive a discount too). 

- Provide your enrollment and visa documents and come to Innopolis in mid-August.

We appreciate: Practical experience in data science

Admission campaign 21/22


grants offered

to 480 USD

monthly allowance

from 2500 USD 

tuition fee

Course information

Duration: 2 years of full-time studies. Graduation project is a scientific research that students have to defend at the end of the course.

The students will be offered 6 core modules and selective disciplines for gaining necessary skills, tools and techniques needed to embark on careers in big data.
Most of the courses are accompanied by projects that allow students to apply the learned algorithms on real data sets
Science project
At the end of the training, students prepare a thesis: conduct scientific research

Machine learning is the base of the Data Science specialization. The course includes simple ML algorithms, ensembles and an introduction to neural networks. It's balanced between the theoretical foundation of the algorithms and practice. 

Advanced Machine Learning gives deeper knowledge in the area. It covers autoencoders, generative models, recurrent neural networks and LSTM, graphical models, bayesian machine learning and other topics. You will learn practical aspects of training neural networks. 

High-Dimensional Data Analysis gives you a much deeper understanding of clustering algorithms, distribution estimation, and strategies of preprocessing data. 

Big Data Technologies and Analytics cover distributed file systems, MapReduce, Spark, NoSQL databases and distributed machine learning. 

In Metrics and empirical methods, you will recall statistics, construct experiments and apply it in the domain of Software Engineering. 

Mathematical courses Advanced Statistics and Optimization are fundamental in Machine learning. 

The course Managing Software Development is about the predictable process of developing software that is needed by the customer. In ML projects correct assumptions about conditions in which the system will be used are crucial. You will also learn how to organize the teamwork, those skills will be useful when you will achieve the team lead level. 

During the study, you will select Technical electives. There is a wide range of courses, from specializations inside ML, - DS application in applying DS in specific domains like finances, or you can get an additional specialization beyond ML. 

In Humanitarian electives, you will develop your soft skills like communication or public speaking, learn to pass and conduct interviews, understand what is important in launching your startup and cover a lot of other interesting nontechnical aspects. 

In Thesis, you will practice all your acquired knowledge, introduce new approaches in ML. Many students publish papers in the top conferences during the work on their thesis. 

The Center for Artificial Intelligence is one of the six technology centers of Innopolis University

The center's competencies in the field of AI: 

— machine learning (neural networks, deep learning); 

— computer vision; 

— natural language processing;  

— big data analysis; 

— systems of advice and assistance in making decisions.

Innopolis University stays in touch with alumni, continuing to advise and assist in solving engineering and business tasks. 

In 2018, 100 % of the students have been offered jobs by the well-known and reputable organizations, and Innopolis University partner companies: Yandex Technologies, ICL, Tinkoff, Kontur Innovation and others. A number of students created their start-ups aimed to solve machine learning tasks. 

The graduates are employed as: 

— Senior developer; 

— Data Science specialist; 

— Specialist in data analysis; 

— Analysts. 


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

Postal Address

420500 Innopolis, Russia 1, Universitetskaya Str.

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