Mastering Generative AI with PyTorch: Hands-on Experience (Udemy.com)
Hands-On Training in Generative Adversarial Networks: Create, Train, and Apply GANs with PyTorch
Created by: Navid Shirzadi
Last updated July 2026
What you will learn
- Understand GAN Fundamentals
- Learn to build and train GAN models from scratch using PyTorch
- Acquire the skills to create synthetic data for various applications
- Explore advanced GAN techniques for converting text into images
How it compares
Against the other 1,182 rated Udemy courses in IT & Software on CourseDuck:
- Rating4.6 out of 5higher than 67% of them
- Reviews183#849 of 1,183 by number of reviews
- Length13.7 hourslonger than 81% of them
- Last updatedJuly 2026more recently than 82% of them
Course Description
Dive into the transformative world of Generative AI with this comprehensive course on Generative Adversarial Networks (GANs) using PyTorch. This course is designed to provide a deep understanding of GANs and their applications, blending theoretical knowledge with extensive hands-on experience.
What You'll Learn:
Core GAN Concepts: Grasp the fundamentals of GANs, including the dynamics between the Generator and Discriminator networks, and understand how they collaborate to create realistic outputs.
Advanced Model Development: Gain practical experience in building and training sophisticated GAN models from scratch using PyTorch. Learn to implement Convolutional Neural Networks (CNNs) for both Generator and Discriminator, and discover how to refine these models for enhanced performance.
Complex Data Generation Techniques: Explore how to integrate complex models such as Long Short-Term Memory (LSTM) networks into GAN frameworks to generate time series and sequential data. Understand the synergy between LSTMs and GANs to create high-quality synthetic data.
Text-to-Image Synthesis: Delve into advanced GAN techniques for generating images from textual descriptions. Learn how to combine textual input with visual data to produce accurate and engaging visual representations.
Ethical Considerations: Engage in discussions about the moral implications of generative AI technologies. Understand the potential impact of GANs on privacy, misinformation, and the ethical use of synthetic data.
Hands-On Coding Experience: Work on real-world projects with step-by-step guidance. You’ll write and debug code collaboratively, with detailed line-by-line explanations of the purpose and function of each line. Learn to troubleshoot and optimize your GAN models for better results.
Who Should Enroll:
This course is ideal for aspiring data scientists, machine learning engineers, and Python developers who want to expand their expertise in generative models. It is also suitable for researchers and practitioners in computer vision and those interested in the ethical dimensions of AI. Whether you're new to GANs or looking to deepen your knowledge with advanced techniques and ethical insights, this course provides the tools and understanding to apply generative AI effectively in real-world scenarios.
Join us to master GANs, leverage complex models for innovative data generation, and gain practical, hands-on experience with detailed debugging and code explanations!
Instructor Details
- 4.6 Rating
183 Reviews
Navid Shirzadi
Welcome! I'm Navid Shirzadi, and I'm thrilled you're here.
I’m an Applied Scientist with a Ph.D. in Engineering and over a decade of experience working with integrated energy systems, optimization, and intelligent control strategies. My background spans mathematical optimization, advanced control, and hybrid modeling techniques that blend physics‑based simulations with modern AI.
I’m deeply experienced in Python, and I build cutting‑edge machine learning, deep learning, and agentic AI models for real‑world applications. My recent work focuses on leveraging agentic AI workflows and LLM‑powered tools to automate and enhance building energy modeling, EnergyPlus pipelines, and large‑scale simulation tasks.
Throughout my career, I’ve published research on intelligent control strategies for energy systems and developed AI‑driven methods that improve efficiency, reliability, and decision‑making. My passion lies in teaching these concepts in a clear, practical, and intuitive way, helping learners build skills they can immediately apply in engineering, data science, and AI‑driven modeling.
I’m excited to share my knowledge and help you grow your expertise in AI, optimization, and energy systems.
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Reviews
By MASOOM HAIDER . on 12/23/2025
its interesting and knowledgeable
By Nicanor Arellano on 8/17/2025
very informative and helpful, great teacher, perfect style of explanation
By Daniel Huber on 2/19/2025
the teacher cannot inspire me compared to other udemy teachers. That does not mean that he does not understand his field. he teaches his lectures in a boring way
By Tom H. on 1/18/2025
Clear explanations with practical GAN projects and synthetic data generation. The assignment at the end of the project is invaluable. A great foundational course to build your AI skills.
By Jairo Silvera on 12/15/2024
Great course, nice an well explanations
By Flavius Aga on 9/24/2024
The practicality, the code along, the questions at the end makes it one of the best starting courses for GAN.
By Jeff K on 9/13/2024
The course was great. The instructor explains thoroughly all the concepts from basic to advance level. Recommended.
By Adonis Andino on 9/11/2024
Good course with explaining all the basic concepts along with the complicated ones! Totally recommend this!
By Robert on 9/10/2024
Very informative course until now, it seems that it covers most of the concepts that we need and also practical coding experience is with line by line explanation. Thanks!
By Chris K on 9/10/2024
This course offers clear, hands-on training with real-world applications, making complex topics like GANs and synthetic data generation easy to understand. The step-by-step approach and practical examples make it perfect for anyone looking to dive into AI-driven creativity! Thanks Dr. Navid!
Quality Score
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Overall Score : 92 / 100












