LLM Fine-Tuning for Beginners: HuggingFace & Unsloth

About this course

LLM Fine-Tuning for Beginners: HuggingFace & Unsloth is a beginner-friendly, hands-on course that takes you from understanding how AI models work all the way to fine-tuning state-of-the-art LLMs using the latest techniques — LoRA, QLoRA, DPO, and GRPO — on both CUDA GPUs and Apple Silicon.

No prior machine learning experience required. You will start from the very basics and progressively build up to advanced fine-tuning techniques used in production AI systems today.

What You’ll Learn1. Introduction to Machine Learning & Natural Language Processing (NLP) Libraries

Discover how to process, analyze, and derive insights from textual data using popular NLP tools.2. In-Depth Understanding of the Transformers LibraryDive deep into HuggingFace’s Transformers, the gold standard for building state-of-the-art NLP and LLM solutions.3. Evaluating AI ModelsMeasure performance using robust metrics and refine your models for optimal results.4. Fine-Tuning BERT for Text Classification

Customize pre-trained models or build your own from scratch with Full training of a model5. Fine-Tuning DistilBERT for Q&AUnderstand how to fine-tune a DistilBERT model for Q&A classification with SQuAD format dataset with HuggingFace library6.

BERT + LoRA and QLoRA for Text Classification Understanding LoRA (Low Rank Adaptation) and QLoRA (Quantized Low Rank Adaptation) for efficient training of LLMs on consumer grade GPUs7. Fine-Tuning Qwen with LoRA and QLoRA on both CUDA and MLX on Apple Silicon

Understand how to fine-tune Qwen models on CUDA and MLX frameworks8. DPO and GRPO — Alignment and Reinforcement Learning

Understand DPO and GRPO instead of relaying on SFT alone and how its going t

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