Technical aspects of Machine Learning and Data Science
Specific Skills Acquired: The course focuses on gaining practical skills in working with machine learning tools and libraries in the Python ecosystem. Participants will gain practical experience in building ML models, starting from the analysis of raw data and ending with the evaluation of the model and the hyperparameter tuning, using both traditional algorithms and neural networks. Among the tools mastered by the participants are the libraries of pandas, matplotlib, sckit-learn, keras, etc.
General Objectives: This course is an introductory course in machine learning. The main goal of the course is to provide participants with a general understanding of the problems solved by machine learning methods and basic algorithms for solving them. The course has a practical orientation, so all stages of working with this data are accompanied by practical examples.
Courses targeted at professionals working in managerial and executive roles, software engineers
Course duration: 3 weeks (18 hours)
Online teaching
Language: English
Course held between 19 September - 7 October 2022
Data Science and Machine Learning- General vision over domain
Specific Skills Acquired: The course contains general definitions of machine learning tasks and a description of algorithms for their solution. Participants will gain skills in decomposition and classification of machine learning tasks and a general understanding of possible ways to solve them.
General Objectives: This course is an introductory course in machine learning. The main goal of the course is to provide participants with a general understanding of the problems solved by machine learning methods and basic algorithms for solving them.
Courses targeted at professionals working in managerial and executive roles
Course duration: 2 weeks (8 hours)
Online or teaching center
Language: English
Course held between 18-30 July 2022
Data Science and Machine Learning- Course in detail
Specific Skills Acquired: The course focuses on gaining practical skills in working with machine learning tools and libraries in the Python ecosystem. Participants will gain practical experience in building ML models, starting from the analysis of raw data and ending with the evaluation of the model and the hyperparameter tuning, using both traditional algorithms and neural networks. Among the tools mastered by the participants are the libraries of pandas, matplotlib, sckit-learn, keras, etc.
General Objectives: This course is an introductory course in machine learning. The main goal of the course is to provide participants with a general understanding of the problems solved by machine learning methods and basic algorithms for solving them. The course has a practical orientation, so all stages of working with this data are accompanied by practical examples.
Course for industry, students
Course duration: 7 weeks (28 hours)
Online teaching
Language: English
Course held between 18 May - 30 June 2022