1.An Introduction to Generative AI

•Explore the fundamentals of generative AI, its key concepts, and how it powers modern AI systems.

2.Capability of Generative AI

•Understand the broad capabilities of generative AI, from creating text to generating images, and its limitations.

3.Application of Generative AI

•Learn how generative AI is transforming industries through diverse and innovative use cases.

4.Application – Writing

•Discover how generative AI assists in content creation, from drafting essays to automating creative writing tasks.

5.Application – Reading

•Learn how AI can enhance comprehension, summarization, and interpretation of text across various contexts.

6.Application – Chatting

•Explore the role of generative AI in conversational applications, including chatbots and virtual assistants.

7.Application – Image Generation

•Understand how AI generates realistic images and creative visuals, revolutionizing design and media.

8.Software Application and Life Cycle

•Gain insight into the development, deployment, and maintenance lifecycle of generative AI-powered software.

9.Cost Intuition

•Learn how to estimate the costs of implementing generative AI.

10.Retrieval-Augmented Generation

•Explore how retrieval-augmented generation integrates external knowledge sources to enhance AI responses.

11.Fine Tuning

•Understand the process of adapting generative AI models to specific tasks or domains for improved performance.

12.Choosing a Model

•Learn how to evaluate and select the most suitable generative AI model for your specific needs.

13.Instruction Tuning and RLHF

•Delve into techniques like instruction tuning and Reinforcement Learning with Human Feedback (RLHF) to improve model alignment.

14.Task Analysis of Jobs

•Analyze how generative AI can be applied to automate, enhance, or augment various job-related tasks.