The Master in Data Science 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.
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++)
Data Structures and Algorithms
Leadership and Group Dynamics
Theory of Probability and Statistics
Technical Writing and Presenting
Introduction to Interaction Design
Technical Project Management
Master's Machine Learning
Statistical Data Analysis
Capstone Project - 1
Seminars & Workshops - 1
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
Stochastic and Huge-scale Optimization
Statistical Data Analysis - 3
Foundations of Cryptography
Image and Video Analysis - 2
Algorithms in Bioinformatics
Neural Networks and Deep Learning
Spectral Graph Analysis and Data Science Applications
Social Network Analysis
Capstone Project - 2
Seminars & Workshops - 2
Check our 2019-2020 academic schedule for an overview of all the classes we are offering.
MATH AS A SECOND LANGUAGE (MSL)A Harbour.Space, a major requirement for all students in tech is a very good level of math. Anyone who lacks the strong math foundation but is eager to learn has a home in our foundation course. Students acquire all the basic knowledge and skills they need to continue their 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.
Andrei RaigorodskiiDr.Sci, Ph.D., Chair of the Department of Discrete MathematicsDSci 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.
Konstantin MertsalovPh.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.
Check out our Data Science program for more information!