Curriculum Vitae

Additional list of completed courses, books, schools:

Bishop PRML, Thoroughly completed with exercises
Deep Bayes Summer School 2017, link, participant
Yandex NLP Week 2019, link, participant
Quantum Machine Learning, University_of_TorontoX - UTQML101x, edx.org, Grade: 99%, link
Probabilistic Graphical Models Specialization, Stanford, Coursera, link
- Representation, Grade: 100%
- Inference, Grade: 97%
- Learning, Grade: 100%
Practical Reinforcement Learning, Higher School of Economics, Coursera, link, Grade: 99.2% with Honors
Bayesian Methods for Machine Learning, Higher School of Economics, Coursera, link, Grade: 100% with Honors
Machine Learning and Data Analysis Specialization, MIPT, Yandex, Coursera, link
- Maths and Python for Data Analysis, Grade: 99%
- Supervised Learning, Grade: 98.6%
- Learning Dataset Structure, Grade: 99.6%
- Drawing conclusions from Dataset, Grade: 98.1%
- Applied Problems of Data Analysis, Grade: 99.6%
- Capstone Project, Grade: 100%
Algorithmic Toolbox, University of California San Diego & Higher School of Economics, Grade: 100.0%, link
Data Structures, University of California San Diego & Higher School of Economics, Grade: 100.0%, link
Algorithms on Graphs, University of California San Diego & Higher School of Economics, Grade: 100.0%, link
Bayesian Statistics: From Concept to Data Analysis, University of California, Santa Cruz, Coursera, link, Grade: 100%
Machine Learning, Andrew Ng, Stanford, Coursera, link