What You’ll Learn
A deep dive into the **art and science of generative modeling**—designed by NanoSchool’s Deep Science Learning Organisation under NSTC guidelines for advanced practitioners ready to build and deploy GANs responsibly.
GAN Fundamentals
Generator/discriminator dynamics, loss functions, mode collapse.
Advanced Architectures
DCGAN, WGAN-GP, Spectral Normalization.
Conditional & CycleGANs
Class-conditional generation and unpaired image translation.
AI to Production
Deploy with ethical safeguards, model cards, and user controls.
Who Should Enroll?
For advanced developers and researchers in India—especially in Delhi NCR—who want to **push the boundaries of generative AI** with technical rigor and ethical awareness.
- Deep learning engineers building creative AI
- PhD researchers in generative modeling
- Startup founders in synthetic media or design tech
- AI artists exploring technical foundations
Hands-On Projects
Indian Art Generator
Train a DCGAN on traditional Indian miniature paintings.
Fashion Translation Engine
Use CycleGAN to transform sarees into modern outfits (and vice versa).
Capstone
Full GAN Pipeline
End-to-end generative system reviewed by NSTC mentors—with model card and usage policy.
4-Week Syllabus
Total: ~40 hours • Lifetime LMS access • Delhi NCR GPU lab support
Week 1: GAN Fundamentals
- Minimax loss, training loop
- Diagnosing mode collapse
- Lab: Generate synthetic digits with vanilla GAN
Week 2: Stable Architectures
- DCGAN, batch norm, strided conv
- Wasserstein loss + gradient penalty
- Lab: Train a stable face generator
Week 3: Conditional & CycleGANs
- cGAN for labeled generation
- Cycle consistency loss
- Lab: Translate Indian street scenes (day ↔ night)
Week 4: Ethics & Deployment
- Model cards for generative AI
- Streamlit demo with user controls
- Capstone: Full GAN system with documentation
NanoSchool LMS & NSTC Mentorship
Access **GPU-enabled cloud labs** (A100) and lifetime LMS resources. Get direct feedback from mentors certified by the NanoSchool Technology Council (NSTC)—many with research experience in generative modeling.
NSTC-Accredited Certificate
Verified by the NanoSchool Technology Council (NSTC). Shareable on LinkedIn. Recognized by Indian AI labs, creative tech startups, and research teams in Delhi NCR.
Frequently Asked Questions
Do I need to know PyTorch or TensorFlow already?
Yes. This is an **advanced course**. You should have built and trained CNNs before. We use both TensorFlow and PyTorch—but fluency in one is sufficient.
Will we cover diffusion models or LLMs?
No. This course focuses **exclusively on GANs**—the foundational generative architecture. Diffusion models are covered in our separate *Generative AI* track.
Is ethical AI part of the curriculum?
Yes. Every capstone includes a **model card** and **usage policy**—aligned with NSTC’s responsible AI guidelines for Indian developers.
