Generative AI: Getting Started

Generative AI is a subset of Deep Learning. It uses AI neural networks and can process both the labelled and unlabeled 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.

The following are the course lessons:

**Course Lessons**

Section A: 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 case

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

After completing this course, you will be ready to learn from our following courses on Udemy (udemy/user/studyopedia):

• Google Gemini Course

• ChatGPT Course

• Microsoft Copilot