PyTorch for Large Language Models
Master PyTorch for LLM engineering — tensors and autograd for transformers, custom GPT blocks, training loops with AMP, LoRA/QLoRA PEFT, FSDP/DDP, and torch.compile inference optimization. Labs every module.
4.9
(340 students)
8 Weeks · 60 hours
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What is this course about?
PyTorch for Large Language Models
Tensors · Transformers · Training · LoRA/QLoRA · FSDP · torch.compile
Build production LLM skills in PyTorch—from tensor/GPU fundamentals through transformer implementation, efficient fine-tuning, distributed training, and optimized inference.
What you'll walk away with:
- Fluent PyTorch for LLM workloads: shapes, devices, autograd, and memory discipline
- Hands-on transformer blocks, attention, and GPT-style stacks you can extend
- Robust training loops with AMP, checkpointing, and evaluation hooks
- PEFT workflows (LoRA/QLoRA) wired into Hugging Face + PyTorch stacks
- Distributed patterns with DDP/FSDP and modern inference with torch.compile / quantization
- A capstone end-to-end LLM pipeline you can defend in interviews
Course Features
Post Graduate Diploma
8 Weeks of Content
Hands-on Projects
Community Support
Lifetime Access
Student Reviews
Aditya Rao
Finally a PyTorch course built for LLMs—attention from scratch, AMP loops, and LoRA labs matched production work. Capstone was interview gold.
Infosys LimitedShreya Menon
FSDP + torch.compile modules changed how I train. Moved from notebook demos to multi-GPU LLM fine-tuning at work.
Wipro TechnologiesNikhil Sharma
Clear path from tensors to PEFT. The DataLoader/collator labs alone were worth it for causal LM training.
TCSKavya Iyer
Loved the KV-cache and SDPA benchmarks. Got hired as LLM Engineer focusing on PyTorch training stacks.
AccentureRohan Desai
QLoRA + merge/export labs were practical. Our team now uses the course pipeline as an internal starter template.
CognizantMeera Krishnan
Best bridge between classical PyTorch and modern LLMs. Capstone metrics tables impressed interviewers.
Capgemini IndiaAlex Morgan
Excellent depth on DDP/FSDP without fluff. Now leading open-model fine-tuning for a US AI product team.
MetaElena Vargas
From transformer blocks to torch.compile serving—portfolio-ready labs every week. Highly recommend.
OpenAI
