PyTorch Mastery
Master PyTorch from tensors and autograd through custom training loops, transfer learning, and production-ready model workflows.
4.9
(410 students)
8 Weeks · 60 hours
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What is this course about?
PyTorch Mastery
Tensors · Autograd · Training Loops · torch.compile · Production Serving
Build framework-depth PyTorch skills—from tensors and custom modules through AMP, profiling, DDP basics, and export/serving—so you write training code you can defend in production and interviews.
What you'll walk away with:
- Confident tensor, autograd, and nn.Module design across CPU/GPU
- Production training loops with datasets, schedulers, and crash-safe checkpoints
- Vision and Transformer starters plus transfer learning / PEFT patterns
- Measurable speedups with AMP, torch.compile, and profiling playbooks
- A train → optimize → ONNX/serve capstone with clear SLOs
Course Features
Post Graduate Diploma
8 Weeks of Content
Hands-on Projects
Community Support
Lifetime Access
Student Reviews
Ananya Krishnan
Finally a PyTorch course that goes past tutorials—custom autograd, crash-safe training loops, and torch.compile labs matched what we do in production. Portfolio-ready capstone.
Infosys LimitedRahul Deshmukh
AMP + profiler labs cut our training step time measurably. Transfer learning and ONNX serve modules helped me pass ML engineer interviews.
FlipkartSofia Alvarez
Clear path from tensors to DDP and FastAPI serving. Best framework-depth course I’ve taken—pair it with Deep Learning Mastery for architectures.
Meta AIJames Okonkwo
Module design and checkpoint/resume labs alone were worth it. Capstone export and load-test gave me a demo I could show hiring managers.
NVIDIA
