Mathematics and computer science

National Research University "Moscow Institute of Electronic Technology"
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20
Contract-based places
0
places on a budget basis
340 000
Cost of tuition per year

About the training program

The following programs are being implemented: "Computer Methods of Modeling, Processing, and Analyzing Data." The program is intended for in-depth training of researchers and leading developers in the field of AI and Data Science. The focus is on the study of modern mathematical theories of machine learning, deep learning in the context of intelligent analysis and digital image processing (including video). Students participate in real research projects, publish articles, and prepare to solve complex problems at the intersection of science and industry. Graduates become architects of intelligent systems capable of creating and implementing breakthrough technologies.

What will they teach you?

  • Обработка сигналов и изображений (цифровые фильтры, вейвлеты)
  • Применение математической статистики и математической логики в анализе данных и NLP
  • Функциональное программирование для создания алгоритмов
  • Разработка систем компьютерного зрения и распознавания образов

What do graduates do?

· Computer Vision Engineer/Developer (CV Engineer) — for robotics, autonomous transport, medical diagnostics, AR; · Signal and Image Processing Engineer (DSP/Image Processing Engineer) — in telecommunications, media, biomedicine, video surveillance systems; · Data Scientist / ML Engineer in geoinformatics and remote sensing — analysis of satellite data in the agricultural sector, environmental monitoring, cartography; · Research Scientist in machine learning with a focus on theory and methods (wavelets, applied mathematics, statistics); · Research Scientist in research institutes (physics, geology, medicine), where experimental data processing is carried out.

Earnings of specialists

от100 000 ₽
without experience
Beginner
of150 000 ₽
1-3 years
Experienced
of250 000 ₽
from 3 years old
Expert

Entrance exams

Exam 1 of 1

interdisciplinary exam

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