Course description

Generative AI is a subset of deep learning.  It uses AI neural networks and can process both labelled and unlabelled data using supervised, unsupervised, and semi-supervised methods.

It refers to a class of artificial intelligence models and algorithms designed to create new content. These models can generate text, images, music, and other forms of data that mimic human-created content.

Generative AI applications are built on top of large language models (LLMs) and foundation models. LLMs are deep learning models.

LLMs are a subset of deep learning. LLMs are AI models that power chatbots, such as ChatGPT, Copilot, Google Gemini, etc. LLMs refer to large, general-purpose language models that can be pre-trained and then fine-tuned for specific purposes.

Course Lessons

Section A: AI Introduction

 1. Artificial Intelligence vs Data Science vs Machine Learning vs Deep Learning

2. Deep Learning Types

Section B: Generative AI and its techniques

3. What is Generative AI

4. Techniques for implementing Generative AI

Section C: What are Transformer Models

5. Generative AI – Transformers

Section D: Large Language Models

6. Large Language Models (LLMs) and its use cases

Section E: More about Generative AI

7. Generative AI - Applications & Challenges

8. Generative AI - Chatbots (Model Types)

9. Generative AI - Features & Examples

Section F: Prompts and AI Chatbots

10. What are Prompts

11. Popular AI Chatbots

What will i learn?

• Learn Generative AI from scratch.
• Get a quick overview about Generative
• What is a Transformer Model
• Learn about Large Language Models
• Generative AI Applications
• Generative AI Challenges
• AI Chatbots Models with examples