ADVANCED COMPUTATIONAL SCIENCE
Master
In Moscow (Russia)
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Description
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Type
Master
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Location
Moscow (Russia)
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Duration
2 Years
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Start date
Different dates available
Modern science and engineering critically rely on efficient and fast computational techniques and models. ACS program achieves the synergy of state-of-the-art mathematical modeling methods (numerical ODE and PDE, stochastic modeling, machine learning and Big data-based approaches) and their implementation with modern high performance parallel computational facilities furnished with up-to-date software. The cutting-edge scientific MSc project solidifies the theoretical knowledge obtained in the courses.
Facilities
Location
Start date
Start date
About this course
The MSc program is 2 years long: the first year is to strengthen your theoretical background, and the second year is to focus on research. Students have the freedom to choose courses and extracurricular activities to shape their individual trajectory, acquire soft skills, and gain entrepreneurial skills to prepare for employment.
Reviews
Subjects
- Entrepreneurship
- Computing
- Innovation
- Computational Science
- Project
- Technology
- Engineering
- Computational
- IT
- Other IT
- Science
Course programme
DIMMSTrack "Data-Intensive Mathematical Modelling and Simulations"HPCTrack "High Performance Computing (HPC) and Big Data"
Compulsory and Recommended Elective courses (36 credits)Compulsory Сourses:
- Scientific Computing
- Numerical Linear Algebra
- Machine Learning
- Recommended Electives:
- Introduction to Data Science
- Numerical Modeling
- High-Performance Computing and Modern Architectures
- Foundations of Software Engineering
- High-Performance Python Lab
- Efficient Algorithms and Data Structures
- Introduction to Linux and Supercomputers
- Build your own supercomputer
- Neuromorphic Computing
- Parallel Computing in Mathematical Modeling and Data-Intensive Applications
- Performance Engineering
- Soft Condensed Matter
- Stochastic Methods in Mathematical Modeling
- Foundations of Multiscale Modeling: Kinetics
- Introduction to Digital Pharma
- Omics Technologies
- Thermodynamics and Transport at Nanoscale
- Machine Learning in Chemoinformatics
- Biomedical Mass Spectrometry
Elective courses (24 credits)See at the Skoltech Course Catalogue
Entrepreneurship and Innovation (12 credits)
- Technology Entrepreneurship: Foundation
- Entrepreneurial Strategy
- Leadership for Innovators
- Hack Lab: Laboratory for Ideas
- Startup Workshop
- Ideas to Impact: Foundations for Commercializing Technological Advances
- Biomedical Innovation and Entrepreneurship
- IoT: Launching New Products & Startups
- Business Communication
- Technology Planning and Roadmapping: Foundation
- Technology Planning and Roadmapping: Advanced
- Intellectual Property, Technological Innovation and Entrepreneurship
- Technology Entrepreneurship: Advanced
- Technological Innovations: from Research Results to a Commercial Product
- Developing Products and Services through Design Thinking
ADVANCED COMPUTATIONAL SCIENCE
-
edX
Course OnlineFree -
Saylor Academy
Course OnlineFree -
FutureLearn
Course OnlineFree -
edX
Course OnlineFree -
Uplatz
Training Online£ 1 -
openSAP
Course OnlineFree -
Codeacademy
Course OnlineFree
See all