The MSc programme 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 programme with 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 programme 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
- Convex Optimization
- Leadership and Group Dynamics
- Theory of Probability and Statistics
- Technical Writing and Presenting
- Practical Unix
- Сomplexity Theory
- Introduction to Interaction Design
- Technical Project Management
- Discrete Optimization
- Nonlinear Optimization
- Master's Machine Learning
- Statistical Data Analysis
- Capstone Project - 1
- Seminars & Workshops - 1
- Java Programming
During the second year of the programme 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 programme, 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 Disrtibuted Computing
- Image and Video Analysis - 1
- Statistical Data Analysis - 2
- Information Retrieval
- Software Design
- 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
MATH AS A SECOND LANGUAGE (MSL)
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-rate tech university in the world.
Programme LeadershipAndrei Raigorodskii
Dr.Sci, PhD, 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 Programme at the Moscow Institute of Physics and Technology Faculty of Innovations and Advanced Technology, professor of the joint Bachelor Programme 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 modelling problems in the internet and other complex networks. His research at Yandex is focused on information retrieval, 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 recognised data scientists who are capable to meet every single possible challenge in the digital era.
PhD, Director of Software Development Europe, Rational Retention
Konstantin Mertsalov is European Director of Development at Rational Enterprise, a globally leading software development company specialising 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 PhD 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 organise, edit and annotate search results as well as share information. Konstantin aims to lead the Harbour.Space Data Science programme 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.
This school offers programs in:
Last updated October 23, 2017