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Deep Learning for Science

YMX8170
Mathematics and Statistics

About this course

The course offers knowledge and skills to understand, design, use and manage contemporary solutions of deep learning to handle scientific problems. The course introduces high level tools to use algorithms of deep learning. Students learn usage and working principles of different methods of deep learning. They also study the validation and interpretation of results. Moreover, they learn technological and practical risks that may occur in the application of methods of deep learning.

NB! This course will take place in autumn semester 2024/2025 which starts on 2nd of September and ends 26th of January (you can find that information under Start date section). The real course start and end dates will be announced at the beginning of September at the latest.

Learning outcomes

After completing this course, the student:

  • analyses in which situations to use particular methods of deep learning;
  • estimates advantages and disadvantages of methods of deep learning in solution of different problems;
  • is able to work with real data;
  • chooses and uses suitable algorithms and methods to solve scientific problems;
  • estimates content and quality of results of algorithms of deep learning;
  • explains main mathematical principles and technological solutions of deep learning;
  • independently uses methods of deep learning in solving scientific problems.

Examination

Final assessment can consist of one test/assignment or several smaller assignments completed during the whole course. After declaring a course the student can re-sit the exam/assessment once. Assessment can be graded or non-graded. For specific information about the assessment process please get in touch with the contact person of this course. For specific information about grade transfer please contact your home university

Activities

lectures, practices

Link to more information

  • Credits
    ECTS 6
  • Level
    Master
  • Contact hours per week
    4
  • Instructors
    Nataliia Kinash
  • Mode of instruction
    Hybrid
  • Course coordinator
If anything remains unclear, please check the FAQ of TalTech (Estonia).

Offering(s)

  • Start date

    2 September 2024

    • Ends
      26 January 2025
    • Term *
      Fall semester 2024
    • Instruction language
      English
    • Register between
      14 May - 29 Jul 2024
    Apply now
These offerings are valid for students of CTU (Czech Republic)