Machine learning and artificial intelligence have emerged as crucial research areas due to their wide-ranging applications across diverse fields. Beyond information technology, advanced data science techniques have yielded significant benefits in experimental and theoretical physics, materials science, bioinformatics, climatology, ecology, and other applied sciences.
This year Kyiv Academic University continues the tradition (2018, 2020) of holding a Data Science School in the form of a series of topical lectures on various areas of machine learning.
The lectures will be brought to you by global experts from the University of Notre Dame (USA), Carnegie Mellon University (USA), Center for Advanced Systems Understanding (Germany), Kyiv Academic University (Ukraine), Taras Shevchenko National University of Kyiv (Ukraine) and many other institutions.
Local Organizing Committee: Volodymyr Bezguba (KAU), Volodymyr Barannik (KAU), Mykola Korablov (KAU), Yana Lazorenko (KAU)
What will you learn at Topical Lectures on Machine Learning?
Lectures will offer you a chance to get an overview of modern advancement in machine learning and learn about non-obvious applications in applied sciences (read more on the Lectures page).
Each lecture has up to 20 minutes allocated for Q&A.
What level of expertise is expected from participants?
These lectures are going to be valuable for:
Participants with basic knowledge of machine learning who seek to explore diverse applications of these methods;
Participants with a background in applied sciences looking to enhance their analytical toolkit.
You are expected to have a basic understanding of undergraduate mathematics (analysis, linear algebra, probability, statistics). Some familiarity with physics and biology is recommended.
What will be the format of the event?
All the lectures will be held online, both for safety reasons and for the ability to include participants from different parts of the world.
Will the lectures be recorded?
The lectures and Q&A sessions will be recorded when possible. Thus, registered participants will be able to catch up with all or most of the materials.
Registration
Registration is mandatory for all participants, the number of places is limited!
Registration deadline: April 10, 23:59 (Kyiv time)