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Fine-tuning transforms generic LLMs into powerful domain-specific tools. This course covers the full process from data preparation through training to deployment, using techniques like LoRA and QLoRA that work on consumer hardware. You’ll build a fine-tuned model for a specialized use case of your choice, with clear evaluation benchmarks at every stage.

✅ What’s Inside:

  1. When to Fine-Tune vs Prompt
  2. Dataset Collection and Curation
  3. Data Formatting for Training
  4. Understanding LoRA and QLoRA
  5. Setting Up Training Environment
  6. Training with Transformers Library
  7. Monitoring Training Runs
  8. Evaluating Model Quality
  9. Merging and Exporting Weights
  10. Inference Optimization
  11. Serving Your Fine-Tuned Model
  12. Project: Domain Expert Bot