Bachelor of Data Science


Read more about this program on the institution's website

Program Description



This program is taught in ENGLISH. The Data Science bachelor program sets out to develop the skills needed to cut through the deluge of data we’re dealing with on a global scale. Students learn to cut through the noise and employ automated analytical tools to create useful knowledge out of big data.


First Year

In the first year, students obtain the foundational theoretical knowledge they need to become data scientists. The programme builds the mathematical basis upon which students will develop understanding of programming, statistics, machine learning and data management during following years. The courses are mostly given in a form of lectures and takeaway coursework.


  • Mathematical Foundations Of Computing
  • Foundations of Programming
  • Calculus
  • Practical Unix
  • Linear Algebra
  • Data Structures And Algorithms
  • Combinatorics And Graphs
  • Operating Systems
  • Databases
  • Capstone Project
  • Seminars & Workshops

Second Year

In the second year, students learn programming, statistics and machine learning in addition to courses that will further establish the mathematical foundations they need in data science.

The second year also contains courses that start covering tremendously useful data science tools as well as technical writing instruments. Most courses require practical coursework and a course project enabling students to get a feel for the challenges and approaches used in this field. The students will also begin developing software for the Capstone project.

By the end of this year, students will be able to write programmes, use primary data science tools and conduct data analysis and will be ready to study applied courses during the final year of the program.


  • Probability Theory
  • JAVA
  • Introduction To Statistics
  • Parallel And Distributed Computing
  • Introduction To Optimisation
  • Machine Learning
  • Python For Massive Data Analysis
  • Stochastic Processes
  • Introduction To Computer Networking
  • Convex Optimisation
  • Writing, Documentation, Tex, Javadoc
  • Computability and Complexity
  • Introduction to Cryptography
  • Capstone Project
  • Seminars & Workshops

Third year

During the third, the final year, students will complete their studies of programming and data analysis and will primarily focus on applications of data science. The programme offers many practical and interdisciplinary courses. The courses are taught by researchers and professionals who practice the courses they teach either academically or by sharing their professional experiences in their field.


  • Information Theory
  • Software Development Process
  • Machine Learning
  • Mapreduce
  • Stochastic and Hugescale Optimization
  • Bioinformatics
  • Performance Oriented Computing
  • Big Data & Emerging Technologies
  • Computational Genomics
  • Introduction to Interaction Design
  • Image Analysis
  • Technical Project Management
  • Algorithms In Bioinformatics
  • Data Visualization
  • Econometrics
  • Leadership & Group Dynamics
  • Web-Graphs
  • Text Mining
  • Capstone Project
  • Seminars & Workshops

Check our 2019-2020 academic schedule for an overview of all the classes we are offering. 


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.

Programme Leadership

Konstantin Mertsalov
Konstantin 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. 

Andrei Raigorodskii
Andrei 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.

Check out our Computer Science program for more information!

Last updated Apr 2020

About the School

Harbour.Space is an innovative private university that combines technology and design, taught by industry leaders from around the world. The university is located in Barcelona, Spain and Bangkok, Thai ... Read More

Harbour.Space is an innovative private university that combines technology and design, taught by industry leaders from around the world. The university is located in Barcelona, Spain and Bangkok, Thailand. Read less