"Overview: Generative Al has emerged as a game-changer for companies grappling with the challenges of
unstructured data and content generation. In today's data-driven landscape, various business sectors,
such as IT companies, financial corporations, healthcare organizations, and manufacturing firms etc.,
rely heavily on large volumes of diverse textual data, images, audio, video etc. With the increasing
demand for cross-lingual capabilities, Generative Al has gained paramount importance. Generative Al is
the backbone of transformative technologies like language models and creative content generation
shaping industries such as media, entertainment, marketing, and research. This comprehensive course
on Generative Al comprises of three main components: Fundamental Concepts of Generative Al,
Applications of Generative Al, and Deep Learning for Generative Al. Students will gain profound insights
into all three components, mastering algorithms that enable machines to create content, simulate
human behavior, and generate imaginative solutions. Embrace the future of Al innovation and unlock
limitless possibilities with Generative Al. Several case studies will be used to demonstrate the
application of these concepts in business context.
Objective: Introduction to Generative Al and Large Language Models (LLMs)
Transformers Architecture: Understanding the key components and its role in language
generation.
Prompt Engineering and Instruction Fine-Tuning: Techniques to guide LLMs in generating
desired outputs
Parameter Efficient Fine-Tuning (PEFT) for optimized model adaptation.
Reinforcement Learning with Human Feedback: Enhancing LLM performance through human
interaction.
LLM-powered Applications: Text and Image Generation, creative applications, and more.
Retrieval-Augmented Generation (RAG) and its potential
Generative Image Models such as AutoEncoders, GANs, Diffusion Models, OpenAl CLIP etc.
LangChain: Framework for developing applications using LLMs
Training & Deployment Strategies for LLMs.
Responsible Al in Generative Al: Ethical considerations and mitigating biases
Use Cases & Case Studies: Real-world applications of Generative Al and LLMs"
DOWNLOAD APP
FOLLOW US