Data Scientist

ProbAI (Topics: Introduction to Probabilistic Models, Probabilistic Programming, Variational Inference and Optimization, Deep Discrete Latent variable Models.)

EEML (Topics: Introduction to Deep Learning, Vision Models, Multimodal Learning, Deep Reinforcement Learning, GraphNets, Generative models, Bayesian Learning, NLP, Artificial Intelligence in Medicine.)

Coursera x University of Michigan (Topics: Supervised and Unsupervised Machine Learning with Scikit-Learn, Model Evaluation and Selection, Fundamentals of Data Manipulation with Python, Data Processing with Pandas.)

Coursera x Deeplearning.ai (Topics: Neural Networks and Deep Learning, Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization, Convolutional Neural Networks.)

Казахский — Разговорный

Английский — Свободное владение