Interpretability in AI

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 […]

Parallelism in Deep Learning

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 […]

End-to-End Natural Language Processing

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 know about natural language processing and various tasks. You will also learn about leveraging large language models for NLP, how to perform Prompt Engineering and […]

3D Vision – NeRFs and INRs

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 Fields, Gaussian Splats, and Implicit Neural Representations. In this course, you will engage in hands-on activities, homework, and instructor consulting to make learning 3D Vision […]