Udemy - Generative AI with Python - Core Concepts and Coding Examples

  • CategoryOther
  • TypeTutorials
  • LanguageEnglish
  • Total size3.3 GB
  • Uploaded Byfreecoursewb
  • Downloads330
  • Last checkedSep. 30th '25
  • Date uploadedSep. 26th '25
  • Seeders 23
  • Leechers14

Infohash : 6BF8E89F501993977E6FE623F97C6666BF144375

Generative AI with Python: Core Concepts and Coding Examples

https://WebToolTip.com

Published 9/2025
Created by Zahid Halim
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Intermediate | Genre: eLearning | Language: English | Duration: 26 Lectures ( 7h 17m ) | Size: 3.33 GB

Generative AI with Python: Core Concepts with Practical Coding Examples

What you'll learn
Master Generative AI from scratch – Learn GANs, VAEs, Transformers & Diffusion Models, even as a beginner
Hands-on AI projects – Build text, image & music generation projects to showcase real-world skills
Write industry-ready Python code – Use TensorFlow/Keras, Git, and Docker for clean, reproducible AI projects
Boost career & research opportunities – Learn cutting-edge generative AI to stand out in ML, data science & research

Requirements
Basic Python knowledge, high school-level math, a computer with internet, and enthusiasm to learn AI—no prior AI experience needed.

Files:

[ WebToolTip.com ] Udemy - Generative AI with Python - Core Concepts and Coding Examples
  • Get Bonus Downloads Here.url (0.2 KB)
    • ~Get Your Files Here ! 1 - Foundations of AI & Environment Setup
    • 1 - Introduction.mp4 (36.8 MB)
    • 2 - GenAI-AI Introduction.mp4 (52.7 MB)
    • 3 - Generative modeling.mp4 (43.8 MB)
    • 4 - Our First Generative Model.mp4 (64.5 MB)
    • 5 - Representative learning.mp4 (65.9 MB)
    • 6 - Core Probability Theory.mp4 (33.2 MB)
    • 7 - Basics of the Coding Environment.mp4 (34.4 MB)
    • 8 - Git clone & Dockers.mp4 (67.8 MB)
    • 9 - Setting up the IDE.mp4 (96.3 MB)
    2 - Deep Learning Fundamentals
    • 1 - Artificial Neural Networks.mp4 (94.4 MB)
    • 2 - 11.txt (2.0 KB)
    • 2 - Multilayer Perceptron (MLP).mp4 (262.6 MB)
    • 3 - 12.txt (2.3 KB)
    • 3 - Convolutional Neural Networks.mp4 (211.3 MB)
    3 - Generative Modeling & Architectures
    • 1 - 13.txt (5.4 KB)
    • 1 - Autoencoders.mp4 (243.0 MB)
    • 10 - 22.txt (6.6 KB)
    • 10 - Energy-based Models.mp4 (197.2 MB)
    • 11 - 23.txt (5.5 KB)
    • 11 - Diffusion Models.mp4 (285.1 MB)
    • 12 - 24.txt (4.4 KB)
    • 12 - Project-1 MiniGPT.mp4 (234.3 MB)
    • 13 - Project-2 Images Generation.mp4 (98.2 MB)
    • 14 - Project-3 Realistic Images Generation.mp4 (90.6 MB)
    • 2 - 14.txt (8.4 KB)
    • 2 - Variational Autoencoders.mp4 (124.5 MB)
    • 3 - 15.txt (10.4 KB)
    • 3 - Generative Adversarial Networks 1 of 2.mp4 (234.1 MB)
    • 4 - 16.txt (5.6 KB)
    • 4 - Generative Adversarial Networks 2 of 2.mp4 (251.0 MB)
    • 5 - 17.txt (6.6 KB)
    • 5 - Conditional GAN.mp4 (81.2 MB)
    • 6 - 18.txt (3.2 KB)
    • 6 - Autoregressive Models LSTM.mp4 (192.1 MB)
    • 7 - 19.txt (1.9 KB)
    • 7 - RNN Extentions PixelCNN.mp4 (99.0 MB)
    • 8 - Normalizing Flow Models-1.mp4 (101.6 MB)
    • 9 - 21.txt (4.2 KB)
    • 9 - Normalizing Flow Models-2.mp4 (115.7 MB)
    • Bonus Resources.txt (0.1 KB)

Code:

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