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fine‑tuning a small language model on your data

23 lessons · 50:57 · updated 9/9/2026

Watch them in order, then explain the topic in your own words below.

Nobody with subject knowledge has checked this course yet. It was put together automatically.

What you will do in this course

  • Fine‑tune a simple LLM
  • Fine‑tune for memes
  • Improve fine‑tuning results
  • Simple LLM fine‑tuning
  • Fine‑tune for recipes
  • Fine‑tune with little data
  • Run LLM locally
  • Fine-tune with Unsloth
0 / 23 lessons watched

Getting started

11 lessons

1. How to Finetune LLM ? | Repo in comments and desc

Fine‑tune a simple LLM

Sukhad Anand · watch the original · 0:46

2. LLM Fine-tuning Made Actually Simple

The AI Guide · watch the original · 0:38

3. How to run LLMs locally [beginner-friendly]

Run LLM locally

IndividualKex · watch the original · 0:59

4. Micro Center A.I. Tips | How to Set Up A Local A.I. LLM

Micro Center · watch the original · 0:59

5. How to fine tune a custom AI model

Fine-tuning overview demo

techwithtimhub · watch the original · 1:07

6. Gathering Data

Gather training data

Tech With Tim · watch the original · 3:27

7. Google Collab Setup

Collab environment setup

Tech With Tim · watch the original · 3:25

8. Model Setup in Ollama

Set up Ollama

Tech With Tim · watch the original · 5:04

9. Ingredients and Preparation

Gather training data

Daniel Bourke · watch the original · 2:58

10. Formatting Data for the Model

Format data files

Daniel Bourke · watch the original · 2:14

11. Testing the Base Model

Test base model

Daniel Bourke · watch the original · 9:48

Check yourself

Four questions on this section. Wrong answers are the point: each one explains itself.

Now you explain it

Close what you watched and explain the topic in your own words in 30 seconds. What you can explain is what you have learned. You are marked against this course's lessons and nothing beyond them.

Explain how you would do this: Getting started — Run LLM locally.

You are judged on these, and nothing else in the course:

  • Fine‑tune a simple LLM
  • Simple LLM fine‑tuning
  • Run LLM locally

Doing it properly

6 lessons

1. Fine-tuning an LLM to generate memes

Fine‑tune for memes

Coding with Lewis · watch the original · 0:58

2. Let's train an AI model to generate recipes!

Fine‑tune for recipes

Make Stuff With AI · watch the original · 0:59

3. Fine-Tuning with Unsloth

Fine-tune with Unsloth

Tech With Tim · watch the original · 7:41

4. Testing the Model with Sample Data

Evaluate fine‑tuned model

Daniel Bourke · watch the original · 1:18

5. Setting Up Supervised Fine-Tuning

Configure fine‑tuning

Daniel Bourke · watch the original · 2:16

6. Training the Model Locally

Train model locally

Daniel Bourke · watch the original · 1:56

Check yourself

Four questions on this section. Wrong answers are the point: each one explains itself.

Now you explain it

Close what you watched and explain the topic in your own words in 30 seconds. What you can explain is what you have learned. You are marked against this course's lessons and nothing beyond them.

Explain how you would do this: Doing it properly — Fine-tune with Unsloth.

You are judged on these, and nothing else in the course:

  • Fine‑tune for memes
  • Fine‑tune for recipes
  • Fine-tune with Unsloth

Going deeper

6 lessons · short section, not a full path on its own

1. Improve your fine-tuning results with an identifier - works with even a small number of training

Harper Carroll AI · watch the original · 1:20

2. Fine-tune language models with surprisingly little data!

Google for Developers · watch the original · 0:28

3. Fine-Tuning and Customizing LLMs with NVIDIA RTX Virtual Workstation

Fine‑tune using NVIDIA RTX

NVIDIA Developer · watch the original · 0:19 · a taster

4. Fine-Tune OpenAI GPT-3 Davinci Model - JavaScript Walkthrough

Coding Nexus · watch the original · 0:06 · a taster

5. Evaluation and GGUF export

Evaluate and export model

Zen van Riel · watch the original · 1:08

6. App-level GenAI (LiteRT-LM for custom/boutique models)

Deploy model in app

AI Engineer · watch the original · 1:03

Check yourself

Four questions on this section. Wrong answers are the point: each one explains itself.

Now you explain it

Close what you watched and explain the topic in your own words in 30 seconds. What you can explain is what you have learned. You are marked against this course's lessons and nothing beyond them.

Explain how you would do this: Going deeper — Fine‑tune using NVIDIA RTX.

You are judged on these, and nothing else in the course:

  • Improve fine‑tuning results
  • Fine‑tune with little data
  • Fine‑tune using NVIDIA RTX