You will learn about the possibilities of deep machine learning, get the basics of a promising profession and add real projects to your portfolio that you can show to a potential employer. We guarantee a minimum of water and a lot of practice.
We start on November 5th.
What do we teach
- Work with multi-dimensional convolutions using Padding & stride, Pooling and LeNet. AlexNet, VGG, NiN, GoogLeNet, ResNet and DenseNet.
- Implement NLP from scratch from classic RNN, GRU and LSTM to the top-end Encoder-Decoder architectures.
- Manage your story with Beam-Search and Teacher Forcing.
- Build language models.
- State-of-art segmentation.
Who will suit the course
Date for Scientists
Boost your productivity with neural networks and you can take on more interesting tasks.
Data engineers
Get tools to deepen your skills and move to the team creating data products at the middle + level
Programmers and developers
Change your current trajectory and enter the fastest growing professional field. Practice with the course will not be embarrassing to include in the resume.
Practice teacher
Alexey Kuzmin - Director of Data Development and Work at DomKlik, ex-Data scientist at ABBYY. He was engaged in the recognition of languages with complex writing, at the current place of work he created a team that develops all models of the company.
Course duration
November 5 - December 23.
Learn more about the course .
