This module is crafted to provide an in-depth understanding of how these models function, their architectural nuances, and their wide array of applications in the tech industry. Starting with the basics of Autoencoders, learners will explore the workings and variations of these networks, including Variational Autoencoders (VAEs), and understand their significance in data compression and generative tasks. The journey continues with an exploration of GANs, from their foundational architecture to the nuances of training and the exploration of their diverse variants. Through practical assignments, engaging video content, and focused readings, participants will gain hands-on experience working with these models, culminating in a deeper comprehension of their capabilities and limitations.

This module provides an in-depth exploration of Language Models and Transformer-based Generative Models, foundational elements in natural language processing and artificial intelligence. Starting with an overview of language models, it progresses to cover the revolutionary transformer architecture, detailing its attention mechanism and various advanced models. The module then shifts focus to groundbreaking models such as GPT and BERT, examining their development, capabilities, and the wide array of applications they enable in the AI domain. Concluding with comprehensive assessments, including practice and graded assignments on cutting-edge topics like VAEs and GANs, the module offers a holistic understanding of how these technologies drive innovation in AI research and applications.

This final module is designed to consolidate the knowledge and skills learners have acquired throughout the course. It starts with a Practice Project, encouraging learners to apply their understanding in a hands-on manner, thus bridging the gap between theoretical knowledge and practical application. Following this, the module offers a Graded Assignment on Gen AI Fundamentals, aimed at rigorously evaluating the learners' grasp of the key concepts, techniques, and applications explored in the course.