We continue a series of educational courses on knowledge-intensive technologies and the use of AI and ML in materials science. We invite you to the fourth course of the BOOSTalent project “Mathematical Foundations of Machine Learning”.
This course is dedicated to the fundamental mathematical concepts essential for understanding machine learning.At its core, any machine learning algorithm involves the minimization or maximization of certain parameters.
The first lecture will focus on mathematical optimization, providing insights into its methods and addressing challenges encountered when searching for the minimum of a function.Following this lecture, you will be acquainted with “Stochastic Gradient Descent”, “Adam”, etc.
Next, we will shift our focus to probability and statistics.This segment aims to provide you with an understanding of generative models.
Additionally, you will enhance your toolkit with Bayes’ theorem, basic statistical analysis, and simple text classification.
- when: on an ongoing regular basis, follow the events.
- who: Dr. Vitaliy Tymchyshyn, Junior Research Fellow at Kyiv Academic University (KAU), Junior Research Fellow at Bogolyubov Institute of Theoretical Physics (BITP);
Dr. Volodymyr Bezguba, Senior Research Fellow at KAU, Acting Head of KAU Laboratory of Data Science and Machine Learning; - language: English;
- the course is for beginners. The purpose is to provide an understanding of the concept of machine learning and teach the modern tools in this field;
- teaching format: self-study with help of video and text materials via educational platform eduportal.kau.org.ua, passing of the final test;
You can meet the lecturer and learn the course structure from this short video:
The course is free. All students will receive certificates with the amount of ECTS credits on completing the course (0,5 credit).
The Deep Tech courses are being delivered to you by the Kyiv Academic University as part of the BOOSTalent project.