Generative AI Fundamentals

Generative AI Fundamentals, available at $24.99, has an average rating of 5, with 24 lectures, based on 3 reviews, and has 8 subscribers.

You will learn about Understand the building blocks of Generative AI Business impact of GenAI such as value chain, business models and use cases Evolution of Large Language Models Different types of architectures: probabilistic, neural network based and transformer based How GPT was trained by OpenAI This course is ideal for individuals who are Business professionals such as executives, managers, leaders, strategists, transformation drivers, change agents or Technical professionals such as developers, testers, solution architects, project leads or MBA students or Engineering students It is particularly useful for Business professionals such as executives, managers, leaders, strategists, transformation drivers, change agents or Technical professionals such as developers, testers, solution architects, project leads or MBA students or Engineering students.

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Summary

Title: Generative AI Fundamentals

Price: $24.99

Average Rating: 5

Number of Lectures: 24

Number of Published Lectures: 24

Number of Curriculum Items: 24

Number of Published Curriculum Objects: 24

Original Price: 99.99

Quality Status: approved

Status: Live

What You Will Learn

Understand the building blocks of Generative AI

Business impact of GenAI such as value chain, business models and use cases

Evolution of Large Language Models

Different types of architectures: probabilistic, neural network based and transformer based

How GPT was trained by OpenAI

Who Should Attend

Business professionals such as executives, managers, leaders, strategists, transformation drivers, change agents

Technical professionals such as developers, testers, solution architects, project leads

MBA students

Engineering students

Target Audiences

Business professionals such as executives, managers, leaders, strategists, transformation drivers, change agents

Technical professionals such as developers, testers, solution architects, project leads

MBA students

Engineering students

This course covers the fundamental technical and business concepts of Generative AI, or simply GenAI.

It is the most hyped-up technology existing in the market today. Gartner has listed it on the top of its two hype curves for 2023: AI technologies hype curve and Emerging Technologies hype curve. This technology became popular since the launch of ChatGPT, a GenAI-powered chatbot, released by OpenAI, on 30th Nov 2022. ChatGPT has 100 million+ users and its website sees nearly 1.5 billion monthly visits.

GenAI has a massive impact on individuals and businesses around the globe. It is a digital transformation technology, that has the potential to change the ways of doing business. Businesses around the globe are exploring how to best exploit its potential to add value to their customers.

It is important that individuals have the fundamental knowledge of this technology, which will play a significant role in shaping their lives in the coming years- so that they can be more ethically aware and socially responsible while using GenAI. Businesses too must cultivate this knowledge to understand their customer needs better and offer the best GenAI solutions for them. However, most of the content available today is either too high-level or too complex with lots of technical diagrams and jargon.

This has inspired me to develop this course with substantial content in a simplified and easy-to-understand language for people with both technical and non-technical backgrounds.

This course currently contains four sections:

1. Overview

2. Business Impact

3. Architecture

4. Training

More sections such as Prompt Engineering, Inference, will be added soon.   

The lecture videos contain a simplified explanation of the technical and business concepts for people with both technical and non-technical backgrounds. For the audience interested in exploring the technicalities further, kindly refer to the additional content attached to some of the lectures.

If you have any questions or doubts, kindly email me through the Udemy platform. You can also connect with me through LinkedIn.

Happy Learning!

 

Course Curriculum

Chapter 1: Overview

Lecture 1: Definition

Lecture 2: Content Classification

Lecture 3: Traditional v Gen AI

Lecture 4: Building blocks

Lecture 5: Evolution of LLM

Chapter 2: Business Impact

Lecture 1: Value Chain

Lecture 2: Business models

Lecture 3: Use cases

Lecture 4: HELM

Chapter 3: Architecture

Lecture 1: Probabilistic method based architecture: n-gram model

Lecture 2: Limitations of n-gram

Lecture 3: Neural Networks: Introduction, Perceptron, Backpropagation

Lecture 4: Complex Neural Networks: Multiple Input Multiple Output (MIMO)

Lecture 5: Text Vectorization

Lecture 6: Word Embeddings

Lecture 7: Word2Vec

Lecture 8: Recurrent Neural Networks

Lecture 9: Limitations of Recurrent Neural Networks

Lecture 10: Long Short Term Memory (LSTM)

Lecture 11: Seq2seq

Lecture 12: Advent of Transformers

Lecture 13: Transformers: Encoder-Decoder Configuration

Lecture 14: Transformers: Decoder Only Configuration

Chapter 4: Training

Lecture 1: How GPT was trained

Instructors

Amit Prabhu
Author, Trainer, Speaker, Faculty, Entrepreneur, Swim-coach

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4 stars: 0 votes

5 stars: 3 votes

Frequently Asked Questions

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You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

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