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Generative AI & Deep Learning : All Models With Projects
Rating: 4.4 out of 5(33 ratings)
3,768 students

Generative AI & Deep Learning : All Models With Projects

Master Generative AI, Deep Learning Models, LLMs, CNN, RNN & Build Real-World AI Projects from Scratch
Created byARUNNACHALAM SHANMUGARAAJAN
Last updated 5/2026
English

What you'll learn

  • All major deep learning models
  • Fundamentals of Generative AI
  • LLMs, CNN, RNN, GANs explained clearly
  • Build real-world AI projects step by step
  • Deep Learning concepts and neural networks

Course content

2 sections • 32 lectures • 1h 26m total length

  • INTRODUCTION TO COURSE0:28
  • DEEP LEARNING INTRODUCTION1:07
  • IMPORTANT TERMS IN DEEP LEARNING3:22
  • ARTIFICIAL NEURAL NETWORK ( ANN ) MODEL1:06
  • DEEP NEURAL NETWORK ( DNN ) MODEL1:51

    Explore deep neural networks with one input layer, many hidden layers, and one output. Harness hidden layers to extract features for image classification, object detection, NLP, sentiment analysis, and summarization.

  • CONVOLUTIONAL NEURAL NETWORK ( CNN ) MODEL3:29
  • RECURRENT NEURAL NETWORK ( RNN ) MODEL1:33
  • LONG SHORT TERM MEMORY ( LSTM ) MODEL1:46
  • TRANSFORMER MODEL2:01
  • GENERATIVE PRE TRAINED TRANSFORMER MODEL ( GPT )1:48
  • GENERATIVE ADVERSARIAL NETWORK ( GAN ) MODEL2:04
  • OBJECT DETECTION - REGION BASED CNN MODEL ( R CNN )4:39

    Explore region-based deep learning for object detection with R-CNN, detailing the two-stage approach, from image regions and CNN feature extraction to SVM classification and bounding box localization.

  • OBJECT DETECTION - YOLO MODEL1:44
  • OBJECT DETECTION - RESNET MODEL1:18

    Explore the residual network ResNet for object detection, a convolutional neural network that mitigates vanishing gradients with shortcut connections and skip layers.

  • FACE RECOGNITION MODEL & CONCLUSION2:39
  • DEEP LEARNING ASSIGNMENT

Requirements

  • Fundamental knowledge of machine learning

Description

Are you ready to master Generative AI and Deep Learning and understand how modern AI systems actually work?

This course, “Generative AI & Deep Learning: All Models With Projects,” is designed to give you a complete understanding of both Generative AI concepts and Deep Learning models, along with hands-on experience through real-world projects.

You will learn how powerful AI systems generate text, images, and predictions using models like Large Language Models (LLMs), Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Generative Adversarial Networks (GANs).


What is Generative AI?

Generative AI is a type of artificial intelligence that can create new content, such as text, images, code, and more. It uses advanced models trained on large datasets to produce human-like outputs.


What is Deep Learning?

Deep Learning is a subset of machine learning that uses neural networks with multiple layers to learn patterns from data. It powers many modern AI applications including image recognition, speech processing, and natural language understanding.


Why This Course?

This course combines theory + practical projects, making it perfect for anyone who wants to truly understand AI and not just use tools.

By the end of this course, you will be able to:

  • Understand AI models deeply

  • Build your own AI projects

  • Apply AI in real-world scenarios


Who this course is for:

  • Students exploring Artificial Intelligence and Deep Learning
  • Developers aiming to understand modern AI architectures

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