Master PyTorch, an open-source deep learning framework for AI. This course covers everything from the Tensors computations, custom architectures, and advanced functions in PyTorch. It also covers how to debug PyTorch codes to gain confidence in debugging codes. The course is packed with plenty of hands-on activities, homework, and instructor consulting to make learning PyTorch […]

In this course, “Reinforcement Learning”, you will learn about various reinforcement learning (RL) algorithms, a branch of machine learning and AI. This course covers everything you need to know about RL, including an overview of the basic concepts of RL, value-based methods, policy-based methods, and actor-critic algorithms. You will also learn how to leverage these […]

In this course, “Interpretability in AI”, you will learn about various interpretable and explainable machine learning algorithms, a branch of machine learning and AI. This course covers everything you need to know about interpretability, including an overview of basic concepts of interpretability, interpretable models, model-agnostic methods, and example-based explanations. You will also learn how to […]

In this course, “Parallelism in Deep Learning,” you will learn about the need for parallelism in deep learning and how to use different methods of parallelism in deep learning. You will also learn about leveraging data parallelism and model parallelism workflows for your AI models on HPC infrastructures. In this course, you will engage in […]

In this course, “End-to-End Natural Language Processing”, you will learn about text data and how to process textual data using state-of-the-art AI tools. This course covers everything you need to […]

In this course, “3D Vision – NeRFs and INRs”, you will learn about the basics of 3D Vision and how to use state-of-the-art 3D vision algorithms such as Neural Radiance […]