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Generative AI with Python & PyTorch

This course focuses on building and deploying Generative AI models using Python and PyTorch, one of the most popular deep learning frameworks. Learners gain hands-on experience with generative architectures such as GANs and VAEs, learn how to implement neural networks from scratch and apply generative techniques to real-world problems.

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4.8

4.8

Course Includes

  • 16 Hrs of Sessions
  • 24/7 Lifetime Support
  • One-on-one doubt clearing
  • Certification Based Curriculum
  • Career path guidance
  • Real Time Users
  • Flexible Schedules

Why Choose TM SQUARE?

We have delivered the Generative AI with Python & PyTorch Training program to over 2000+ professionals, focusing on practical, application-oriented learning. Our sessions are designed to be engaging, activity-based, and tailored to real-world challenges. With an average participant rating of 4.8/5, the program is consistently recognised for its clarity, relevance, and impact. Join this course to experience the expertise of our professional instructors and best experience of learning concepts.

Course Overview

This course focuses on building and deploying Generative AI models using Python and PyTorch, one of the most popular deep learning frameworks. Learners gain hands-on experience with generative architectures such as GANs and VAEs, learn how to implement neural networks from scratch and apply generative techniques to real-world problems.

 

Course Outline

What is your return policy?

We offer a 30-day return policy from the date of purchase.

Do I need a receipt to return an item?

Yes, a valid receipt or proof of purchase is required.

Can I return online purchases in store?

Yes, online purchases can be returned in any of our physical stores.

How long does shipping take?

Standard shipping typically takes 3–5 business days.

Do you ship internationally?

Yes, we ship to most countries worldwide. Additional charges may apply.

Which countries are excluded?

We currently do not ship to embargoed countries or regions with postal restrictions.

Module 1 — Introduction to Generative AI & PyTorch

Generative AI basics and use cases
Overview of PyTorch fundamentals: tensors, autograd, modules
Building simple neural networks in PyTorch
Module 2 — Neural Networks Fundamentals

Deep learning basics: architectures, activation functions, loss functions
Training neural networks with backpropagation
Optimizers and evaluation metrics
Module 3 — Working with Generative Models

Generative Adversarial Networks (GANs) in PyTorch
Building and training GAN models
Understanding generator and discriminator workflows
Variational Autoencoders (VAEs) for data generation
Comparing GANs and VAEs techniques
Module 4 — Advanced Deep Learning Architectures

Convolutional neural networks (CNNs) in generative contexts
Conditional GANs, DCGANs, and advanced generative networks
Multimodal generative applications (inferred typical content)
Module 5 — Real-World Projects & Labs

Building text-to-image or image-to-image generative workflows (inferred typical labs)
Synthetic data generation and augmentation
End-to-end project build & deploy (inferred typical final project)
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