Lead Instructor: Mian Ahmad Basit — Gujranwala
LLM Fine-Tuning in Gujranwala
Master LoRA, QLoRA, DPO, and GRPO to align and specialize open-weight models.
Gujranwala's tech scene is still emerging — engineers who build genuine AI engineering depth now are positioned ahead of the curve.
Gujranwala
Live cohort location
Live Weekly Classes
Practical, hands-on sessions
Certification
On completion
Freelance-Ready
Practical project focus
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Curriculum Breakdown
LLM Fine-Tuning — What You'll Learn in Gujranwala
Learn the complete fine-tuning lifecycle — from dataset preparation and parameter-efficient adapters through preference alignment, quantization, and production-ready deployment of open-weight models. Gujranwala's tech scene is still emerging — engineers who build genuine AI engineering depth now are positioned ahead of the curve.
Module 01
Data Preparation
- Instruction-pair and chat-format dataset construction
- ChatML and LLaMA-3 chat formatting
- Loss masking and dataset deduplication
- Synthetic instruction generation with Self-Instruct
- Data quality filtering pipelines
Module 02
PEFT & Adapters
- LoRA mathematics and rank/alpha selection
- QLoRA with NF4 quantization and paged optimizers
- DoRA magnitude-direction decomposition
- AdaLoRA adaptive rank allocation
- SFT pipeline design with FLAN and OpenHermes datasets
Module 03
Alignment & Deployment
- DPO, GRPO, and ORPO preference alignment
- RLHF, PPO, and reward model fundamentals
- GPTQ, AWQ, and FP8 quantization for inference
- LoRA adapter merging and multi-LoRA serving
- Deployment with vLLM, SGLang, and GGUF/llama.cpp
Outcome
Fine-tune, align, and deploy an open-weight LLM using production-grade techniques.
Program Instructor & Mentor
Learn LLM Fine-Tuning With Mian Ahmad Basit
Live mentorship for students in Gujranwala and across Pakistan — practical training, not just theory.
Every module pairs structured theory with real, hands-on work — so students in Gujranwala leave with skills they've actually practiced, not just watched.
Mian Ahmad Basit
Lead Instructor & Program Architect
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Live sessions, media appearances, and speaking engagements
Media / Talks / Featured
Watch & Learn
Featured talks, sessions, and insights from conferences, podcasts, and tech programs.
Frequently Asked Questions
LLM Fine-Tuning in Gujranwala — FAQs
What hardware do I need?
QLoRA techniques covered in the course allow fine-tuning on a single consumer GPU — no enterprise hardware required.
Which tools does the course use?
Hugging Face TRL, PEFT, Unsloth, and Axolotl are all covered as fine-tuning frameworks.
Does this cover reasoning models like DeepSeek-R1?
The alignment section covers GRPO and rule-based rewards, the same techniques behind reasoning-model training.
Is this a standalone course or part of the full program?
This module is drawn from Mian Ahmad Basit's full-length program and can be taken as a focused track or as part of the complete curriculum.
Is this class online or in-person?
Classes run live online, so students anywhere in Pakistan — including this city — can join without relocating.
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