Master of Data Science

This online Master of Data Science is intended to create opportunities for students to become experts in data science.

The programme includes 3 tracks:

1. Data Scientist,
2. Machine Learning Engineer,
3. Researcher in Data Science.

The program is distinguished by its emphasis on hands-on, project-based training, and, due to its online format, it offers students many advantages over traditional on-campus programs. Students can enroll in the program from anywhere in the world, complete the courses on their own schedule without having to relocate.

In order to apply, students must have a bachelor’s degree and an interest in data science as a career. Some students might have backgrounds as analysts, programmers, or web developers. However, this is not necessary to qualify for the degree.

To be considered for admission, students must have a bachelor’s degree and fill out a brief application form. They must also pass an online exam that tests their understanding of basic knowledge of mathematics.

The degree features introductory courses on math for data science, programming, and algorithms, so students without a computer science bachelor’s degree can learn basic concepts as they complete the program. No coding experience is required, and students of all backgrounds are welcome.

The programme curriculum consists of 21 courses divided into four blocks: mathematics, programming, future profession, and projects. Students start with the mathematics and programming blocks. In order to successfully complete the programme, students must earn 120 ECTS credits. Successful graduates will receive a Master’s degree in Data Science from HSE University.

Graduates will be prepared to enter or continue working in fields like analytics, data science, machine learning and artificial intelligence, research, and academia.

Full tuition is 1 155 000 rubles (equivalent to 17 000 $).

The cost of the tuition will be divided into three payments.

HSE scholarships are available (20% or 50% off on tuition costs) — check the details here.

Admissions webinars: 

November, 20 (in English)

November, 20 (in Russian)

October, 29 (in English)

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