We are continuing a series of educational courses on knowledge-intensive technologies and the use of AI and ML in materials science. We invite you to the second course of the series - Fundamentals of Materials Science. It is ideal for those who want to understand the possibilities of using modern materials in production, those who work with this topic as a technical specialist, and those who see business potential in the latest materials.
Course dates: November 1 to December 1, 2023. Registration is open until November 1, 2023.
Teaching format: online, self-study of video and text materials, final testing.
Lecturer: Doctor of Technical Sciences, Valerii Kostin, Leading Researcher at the E.O. Paton Institute of Electric Welding of the National Academy of Sciences of Ukraine (Metal Science and Heat Treatment of Metals), Associate Professor of the Department of Applied Physics and Materials Science of the Kyiv Polytechnic University
Language of instruction: Ukrainian;
For: undergraduate and graduate students specializing in materials science and mechanical engineering, researchers in the field of materials development and heat treatment, students of economic specialties and entrepreneurs interested in using the latest materials for business development.
The course is an introductory one. Its purpose is to provide an understanding of the fundamental principles of materials science, methods of classification of various materials and alloys, namely: steel, cast iron, aluminum, magnesium and titanium alloys and metal materials.
Registration: please fill in the form to register for the course. After filling it out, you will receive instructions for registration on the portal www.eduporta.kau.edu.ua and will be enrolled in the course of your choice.
You can meet the lecturer and learn what to expect from the course in this video.The course is a part of the large-scale initiative BOOSTalent Project, which brings together several European universities with a common goal: to stimulate innovation in artificial intelligence and machine learning in various industries:
The course is free of charge. After completing the course, all participants who complete the program and pass the test will receive certificates with ECTS credits (0.5 credits).
The courses are prepared and taught by the State National University of Kyiv Academic University within the framework of the BOOSTalent project funded by the European Institute of Technology and Innovation.