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Fine-Tuning LLMs
Adapt open models to your domain with supervised fine-tuning, datasets and evaluation.
AdvancedUpdated Sept 2026English
Taught by AssistedCareer Team
What you’ll learn
- Prepare high-quality training datasets
- Run supervised fine-tuning on hosted platforms
- Compare base vs fine-tuned models objectively
Curriculum
2 modules · 6 lessons · 1h 10m
When to fine-tune3 lessons · 34 min
RAG, prompting or training?
- Fine-tuning vs RAG vs promptsPreview10:00
- Dataset design12:00(available after enrolling)
- Hosted fine-tuning APIs12:00(available after enrolling)
Evaluation3 lessons · 36 min
Prove it worked.
- Holdout sets and metrics12:00(available after enrolling)
- A/B testing models12:00(available after enrolling)
- Maintenance12:00(available after enrolling)
What you’ll build
- Project 1
Domain tone adapter
Fine-tune a small model for your product's voice and terminology.
Before you start
- Python
- AI Fundamentals or equivalent
Who this is for
- ML engineers and senior developers
About this course
Adapt open models to your domain with supervised fine-tuning, datasets and evaluation.
What's insideLink to this section
- When to fine-tune: RAG, prompting or training?
- Evaluation: Prove it worked.
Your instructor
AssistedCareer Team
Sample instructor profile
Placeholder profile created by the seed script. Replace with your real instructors before launch.
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