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Tilda
Deep Learning Course
Part 1 Basic track
About the course
On the basic course in the first semester, you will be able to get acquainted with the basics of machine learning and neural networks, as well as master the tools of any data scientist. A significant part of the course will be devoted to an introduction to the Python language : both are necessary for learning neural networks.
At the end of the semester, students make an individual project (project topics will be announced closer to the end of the course)
The course takes place on the Stepik platform. Registration is open. Training will start in January 2023
Course program
Python Basics
Libraries for Data Analytics: Numpy, Pandas, Matplotlib
Mathematics for Data Science: linear algebra, mathematical analysis, optimization methods
Fundamentals of machine learning, sklearn library
Linear machine learning models, OOP in data analysis
Algorithm Compositions and Model Selection Methods
Introduction to Neural Networks and PyTorch library
Fundamentals of Convolutional Neural Networks
Methods for designing and training neural networks
Convolutional Neural Network Architectures
Semantic segmentation and object detection
Practical application of computer vision models
Competitions on Kaggle
Final project
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