Finetuning Large Language Models
by DeepLearning.AI × Lamini
Understand when to fine-tune vs. prompt, then do it — data prep, training, and evaluation.
Overview
Taught with Lamini's Sharon Zhou, this course demystifies fine-tuning. It starts with the crucial question of when fine-tuning beats prompting or RAG, then walks through preparing instruction data, running the training process, and evaluating the resulting model. You come away able to judge whether fine-tuning is the right tool and how to execute a first project without getting lost in low-level details.
At a Glance
- Topic
- Fine-Tuning
- Level
- Intermediate
- Format
- Course
- Cost
- Free
- Duration
- ~1-2 hours
- Provider
- DeepLearning.AI × Lamini
- Hands-on
- Yes — code/exercises
- Certificate
- None
What You’ll Learn
- ✓When to fine-tune vs. prompt vs. use RAG
- ✓Preparing and formatting instruction data
- ✓Running and monitoring a fine-tuning job
- ✓Evaluating a fine-tuned model
Highlights
- •Clear decision framework for fine-tuning
- •End-to-end first project
Who It’s For
Best For
- ✓Developers deciding whether/how to fine-tune
Prerequisites
- •Python
- •Basic deep-learning familiarity
FAQ
What is Finetuning Large Language Models?
A concise introduction to why, when, and how to fine-tune LLMs, covering data preparation, training, and evaluation.
Is Finetuning Large Language Models free?
Finetuning Large Language Models is free to access.
What level is Finetuning Large Language Models for?
Finetuning Large Language Models is aimed at a intermediate audience. Recommended background: Python, Basic deep-learning familiarity.
How long does Finetuning Large Language Models take?
Expect roughly ~1-2 hours. Most learners work through it at their own pace.
What will I learn from Finetuning Large Language Models?
You'll learn: When to fine-tune vs. prompt vs. use RAG; Preparing and formatting instruction data; Running and monitoring a fine-tuning job; Evaluating a fine-tuned model.