This course will provide you a foundational understanding of machine learning models (logistic regression, multilayer perceptrons, convolutional neural networks, natural language processing, etc.) as well as demonstrate how these models can solve complex problems in a variety of industries, from medical diagnostics to image recognition to text prediction.

In addition, we have designed practice exercises that will give you hands-on experience implementing these data science models on data sets. These practice exercises will teach you how to implement machine learning algorithms with PyTorch, open source libraries used by leading tech companies in the machine learning field (e.g., Google, NVIDIA, CocaCola, eBay, Snapchat, Uber and many more).

The Program

1. Simple Introduction to Machine Learning.
2. Basics of Model Learning.
3. Image Analysis with Convolutional Neural Networks.
4. Recurrent Neural Networks for Natural Language Processing.
5. The Transformer Network for Natural Language Processing.
6. Introduction to Reinforcement Learning.