Generative AI (English Version): Unleashing Next-Gen AI

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Coursat.ai Dr. Ahmad ElSallab

7:19:45

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1 - Introduction

1 - Introduction.mp4

02:15

2 - Course overview.mp4

24:11

2 - What is Generative AI

3 - What is Generative AI.mp4

08:38

4 - Generative vs Discriminative models.mp4

06:40

5 - Why Generative models.mp4

14:19

6 - EncoderDecoder design pattern.mp4

05:01

7 - GenAI modalities mappings.mp4

05:06

3 - Txt2Txt GenAI

8 - Unimodal mappings Txt2txt and Language models.mp4

05:03

9 - Statistical Language Models SLM.mp4

12:14

10 - Neural Language Models NLM Char level.mp4

08:55

11 - Neural Language Models NLM Word level.mp4

03:41

12 - SLM and NLM in Python and Keras.mp4

14:27

13 - Seq2seq models.mp4

07:20

14 - Seq2seq Attention models.mp4

06:10

15 - Transformers.mp4

12:29

16 - Huggingface Transformer Pipeline.mp4

10:32

17 - LargeScale Language Models LLM Transfer Learning in NLP.mp4

13:09

18 - Pretrained Transformers.mp4

05:52

19 - BERT.mp4

04:49

20 - GPT.mp4

10:06

21 - ChatGPT.mp4

11:58

22 - OpenAI API.mp4

09:37

23 - GPT3 Finetuning.mp4

06:12

24 - GPT3 Chatbot.mp4

09:11

25 - ChatGPT Clone in Google Colab.mp4

08:41

26 - ChatGPT Clone in Streamlit.mp4

06:47

27 - ChatGPT Clone Excercise.mp4

01:52

4 - Img2Img GenAI

28 - Img2Img EncoderDecoder.mp4

04:13

29 - Auto Encoder AE.mp4

22:34

30 - AE Visualization.mp4

11:32

31 - Variational Auto Encoder VAE.mp4

10:30

32 - Conditional VAE.mp4

06:36

33 - Coding AE in Keras.mp4

15:15

34 - Generative Adversarial Nets GANs.mp4

02:17

35 - Generating images from GANs.mp4

00:37

36 - Training GANs.mp4

10:42

37 - Coding GAN training in Keras.mp4

06:16

38 - DCGAN.mp4

03:42

39 - Conditional GANs.mp4

09:53

40 - AttributeGAN.mp4

06:05

41 - How Good are GANs today.mp4

01:16

42 - Domain adaptation with pix2pix and CycleGAN.mp4

11:17

5 - Multimodal GenAI

43 - Multimodal Txt2Img generation.mp4

03:26

44 - Diffusion models.mp4

14:27

45 - Latent Diffusion Models LDM.mp4

02:24

46 - CLIP.mp4

06:28

47 - StableDiffusion.mp4

03:27

48 - Online tools for txt2img DreamStudio and Midjourney.mp4

01:51

49 - OpenAI API DALLE.mp4

03:49

50 - Huggingface StableDiffusion.mp4

02:00

51 - Excercise Midjourney clone.mp4

01:05

52 - Img2Txt generation Image Captioning.mp4

03:44

53 - Txt2Voice generation VALLE.mp4

01:14

6 - The good the bad and the ugly

54 - The Good.mp4

06:19

55 - The Bad.mp4

09:08

56 - The Ugly.mp4

13:33

57 - What should we do.mp4

05:15

7 - Conclusion

58 - Conclusion.mp4

03:35

8 - Material

59 - Material.html

Description

Generative AI - English version

What You'll Learn?

Generative AI definition, areas of applications, mappings like txt2txt, img2txt, txt2img and txt2voice
How ChatGPT works, and the underlying tech behind like GPT, Large-Scale Language Models (LLM) and Transformers
How Latent Diffusion, StableDiffusion and DALL-E systems work
Generative Adversarial Networks (GANs) and Variational Auto Encoder (VAE)
The good, bad and ugly faces of GenAI, and how to adapt to the new tech
Build ChatGPT clone using OpenAI API and Streamlit
Build NLP applications using OpenAI API like Summarization, Text Classification and fine tuning GPT models
Build NLP applications using Huggingface transformers library like Language Models, Summarization, Translation, QA systems and others
Build Midjourney clone application using OpenAI DALL-E and StableDiffusion on Huggingface

Who is this for?

AI/ML Practitioners, Developers, Engineers and Researchers

NLP Engineers or Researchers

CV Engineers or Researchers

Data Scientists

What You Need to Know?

AI, ML and Deep Learning foundations

NLP: RNN, LSTM, Transformers basics

CV: ConvNets

More details

Description
Hello and Welcome to a new Journey in the vast area of Generative AI

Generative AI is changing our definition of the way of interacting with machines, mobiles and computers. It is changing our day-to-day life, where AI is an essential component.

This new way of interaction has many faces: the good, the bad and the ugly.

In this course we will sail in the vast sea of Generative AI, where we will cover both the theoretical foundations of Generative models, in different modalities mappins: Txt2Txt, Img2Txt, Txt2Img, Img2Txt and Txt2Voice and Voice2Text. We will discuss the SoTA models in each area at the time of this course. This includes the SoTA technology of Transformers, Language models, Large LM or LLM like Generative Pre-trained Transformers (GPT), paving the way to ChatGPT for Text Generation, and GANs, VAE, Diffusion models like DALL-E and StabeDiffusion for Image Generation, and VALL-E foe Voice Generation.

In addition, we will cover the practical aspects, where we will build simple Language Models, Build a ChatGPT clone using OpenAI APIs where we will take a tour in OpenAI use cases with GPT3.5 and ChatGPT and DALL-E. In addition we will cover Huggingface transformers and StableDiffusion.

Hope you enjoy our journey!
Who this course is for:
AI/ML Practitioners, Developers, Engineers and Researchers
NLP Engineers or Researchers
CV Engineers or Researchers
Data Scientists

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