AI-212 Deep Learning Foundations with PyTorch
Course Description: Artificial intelligence has become an extremely important area for IT professionals and engineers in the past 10-20 years with the scientific breakthroughs and practical applications of deep learning and more recently of generative AI systems, especially with its Large Language Model (LLM) variant such as OpenAI’s ChatGPT and Google’s Bard. Due to its importance and impact on every aspect of our lives, understanding the concepts, functionalities and practical usage of AI systems is quickly becoming essential for all IT and other technical professionals as well as for managers with technical background.
This training focuses on Machine Learning and Deep Learning (aka Artificial Neural Networks) foundations and teaches participants the following topics:
- Basic concepts and building blocks of Artificial Neural Networks (ANN)
- PyTorch Introduction and its usage for basic Deep learning models
- Convolutional Neural Networks (CNN) for Image recognition
- Recurrent Neural Networks (RNN) for Text classification
- Transfer Learning with PyTorch
Besides gaining basic understanding of the theory of deep learning, students will also make extensive lab exercises using the Python based PyTorch deep-learning framework to see how these concepts work in practice.
Course Length: 16 training hours
Structure: 50% theory, 50% hands on lab exercises
Target audience: All types of IT, telecom, and other technical professionals as well as managers with technical background who want to understand the basic concepts, programming of Deep Learning (aka Artificial Neural Networks) using the most popular Python based PyTorch framework.
Prerequisites: Basic understanding of IT systems and programming concepts. Basic Python programming skills needed for doing the lab exercises.