The objective of this project course is to provide hands-on experience in solving real-world problems using Deep Learning and Generative AI techniques. Students will participate in a dedicated Kaggle competition designed specifically for this course, where they will apply their learning to build effective solutions for real-world datasets. Participants will work on an end-to-end project involving data preprocessing, model building (CNNs, RNNs, Transformers), fine-tuning large models, and prompt engineering for GenAI tasks. The competition will run for 8 to 12 weeks and will be structured into multiple milestones to guide students step by step through the development lifecycle of an AI project.
Hands-on experience with deep learning frameworks like PyTorch, Huggingface.
Working with large language models (LLMs) and generative AI models (text, image, etc.)
Applying transformers, diffusion models, and fine-tuning techniques
Enhancing your profile with a Kaggle competition medal and an industry-relevant AI project
Preparing for technical viva conducted by an industry expert to simulate real interview conditions.
Professor , Department of Mechanical Engineering, Wadhwani School of AI , IIT Madras
Balaji Srinivasan is a Professor at the Wadhwani School of AI and Dept. of Mechanical Engineering at IIT-Madras. He has a PhD from Stanford (2005), MS from Purdue, B.Tech from IITM. His current research interests are in Scientific Machine Learning, Numerical solution of PDEs and Applied Deep Learning.
Professor , Wadhwani School of AI , IIT Madras
Ganapathy Krishnamurthi is a Professor at the Wadhwani School of AI. He has a PhD from Purdue University (2008), MSc (Physics) from IITM. His current research interests are in Generative AI, and Deep learning applied to Medical Image Analysis and Medical Image Reconstruction.