Two yearsData ScienceThis program is taught in ENGLISH. The data science is a new frontier of human knowledge and a new domain of discovery. Data scientists have the analytical and programming skills needed to extract valuable knowledge out of data. The burgeoning technology sector is quickly becoming the epicenter for data science.

The MSc program is designed for those who desire to deepen their comprehension of all aspects of the data science. Applicants could be graduates from other degrees with a strong mathematical core, or those continuing their academic pursuit after achieving a BSc in data science.


Year 1

Students begin the program with a foundational knowledge of programming and mathematics, including data structures and algorithms, statistics and machine learning. During the first year, their knowledge of mathematics, programming and data analysis will be significantly extended. The program also offers the opportunity to obtain key soft skills for the professional world including technical project management, writing and presenting. Finally, students are expected to attend a substantial amount of talks and workshops offered by the university, as well as working on the Capstone project.


Combinatorics And Graphs Big Data Analysis/Machine Learning - 2
Object-Oriented Programming (C++) R
Data Structures and Algorithms Convex Optimization
Databases Leadership and Group Dynamics
Theory of Probability and Statistics Technical Writing and Presenting
Practical Unix Сomplexity Theory
Introduction to Interaction Design Technical Project Management
Master's Machine Learning Statistical Data Analysis
Python Capstone Project - 1
Networks Seminars & Workshops - 1
Java Programming

Year 2

During the second year of the program, students will primarily focus on learning the key applications of the data science as well as advanced methods in mathematics and data analysis. A significant part of the year will be allocated to the completion of the capstone project. Through completion of the program, students will learn to conduct data analysis on any scale, develop the software necessary for analysis and present the results in a professional and efficient ways.


Parallel and Distributed Computing Image and Video Analysis - 1
Statistical Data Analysis - 2 Information Retrieval
Software Design Auctions
Stochastic and Huge-scale Optimization Statistical Data Analysis - 3
Foundations of Cryptography Information Theory
Map Reduce Image and Video Analysis - 2
Distributed Databases Machine Translation
Text Mining Data Visualization
Game Theory Algorithms in Bioinformatics
Neural Networks and Deep Learning Spectral Graph Analysis and Data Science Applications
Social Network Analysis Web Graphs
Time Series Capstone Project - 2
Robust Optimization Seminars & Workshops - 2


A Harbour.Space major requirement for all students in tech is a very good level of math. Anyone who lacks the strong math foundation they need for a career in tech, but is eager to learn has a home in our foundation course (link). Students acquire all the basic tools they need to continue studies in Computer Science, Data Science or Cyber Security. Graduating from MSL means opening the doors to apply for a place at Harbour.Space University and any other top-rated tech university in the world.

Program Leadership

Andrei RaigorodskiiAndrei Raigorodskii
Dr.Sci, Ph.D., Chair of the Department of Discrete Mathematics

DSci of Physics and Mathematics Andrei Raigorodskii is a professor of Department of Mathematical Statistics and Stochastic Processes, Faculty of Mechanics and Mathematics at the Lomonosov Moscow State University, Chair of Department of Discrete Mathematics and Chair of the Data Science Bachelor Program at the Moscow Institute of Physics and Technology Faculty of Innovations and Advanced Technology, professor of the joint Bachelor Program of the New Economic School and Higher School of Economics, and professor of Discrete Analysis, Probability Theory, and Graphs at the Yandex Data Analysis School alongside his faculty leadership at Harbour.Space.

He is editor-in-Chief of the Moscow Journal of Combinatorics and Number Theory. He was awarded the prize for breakthroughs in a number of fields in discrete mathematics and their practical applications in 2011. Andrei published more than 100 scientific papers, articles, and books. He also founded a summer school of Combinatorics and Algorithms for senior undergraduate students. Andrei has been working with Yandex (4th largest search engine globally), dedicating himself to the practical application of methods he developed in modeling problems in the internet and other complex networks. His research at Yandex is focused on information retrieval, the relevance of the retrieved information in relation to search parameters and the structure of spam documents. These results have greatly improved the quality of the Yandex search engine. As Data Science Faculty Leader at Harbour.Space, Andrei aspires to breed next generation of internationally recognized data scientists who are capable to meet every single possible challenge in the digital era.

Konstantin MertsalovKonstantin Mertsalov
Ph.D., Director of Software Development Europe, Rational Retention

Konstantin Mertsalov is European Director of Development at Rational Enterprise, a globally leading software development company specializing in enterprise information management.

Originally from Russia, he moved to New York in 1998 to study Computer Science and Applied Mathematics, and continued his academic career with a Rensselaer Polytechnic Institute Ph.D. on large dynamic social networks. He's an expert on machine learning, information diffusion in social network, semantic web search, unstructured data, big data, and data analytics in general. He developed U Rank, a search engine that allows people to organize, edit and annotate search results as well as share information. Konstantin aims to lead the Harbour.Space Data Science program with unbridled enthusiasm about the relatively new field, and he’s determined to use his industry knowledge to share, teach and create for the future with his students.

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Last updated March 12, 2019
This course is Campus based
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