Master
2024/2025
Machine Learning II
Type:
Elective course (Science of Learning and Assessment)
Area of studies:
Psychology
Delivered by:
Department of Educational Programmes
Where:
Institute of Education
When:
2 year, 2 module
Mode of studies:
offline
Open to:
students of all HSE University campuses
Instructors:
Andrey Zakharov
Master’s programme:
Science of Learning and Assessment
Language:
English
ECTS credits:
3
Contact hours:
30
Course Syllabus
Abstract
Prerequisites: Basic knowledge of Machine Learning, Statistics and Python.
This course aims to provide state-of-the-art techniques of mathematical statistics as well as new and modern methods of machine learning. What is more important, this course will focus on practical activities and it will allow students to learn on their mistakes. Moreover, skills and knowledge obtained during this course could be applied to almost any field of science and industry. Students will know statements of all major machine learning problems and mathematical details of the most important data analysis methods and algorithms. Also, they will obtain skills, such selection of an appropriate method for solving particular data analysis problems, performance of basic data processing and visual analysis, features generation for subsequent machine learning, application machine learning libraries, algorithm's selection hyperparameters, critically evaluate the obtained results and redesign data-processing pipelines, ability to solve real-world data science problems using modern machine learning techniques.