Mimir, Keeper of the Well of Wisdom
Ollama: Run Local LLMs Offline and Privately for Free
https://www.udemy.com/course/ollama-local-llm-hugging-face-rag-
python/
Year : 2026
Language : English
Level : All Levels
Category : Development
Subcategory : Data Science
Duration : 2h 41m
Lectures : 32
Rating : 4.0/5 (6 reviews)
Students : 122
INSTRUCTOR(S)
HEADLINE
From Ollama setup to your own local AI on an 8 GB laptop with
no GPU. Hugging Face, Python, RAG and embeddings
WHAT YOU'LL LEARN
* Run powerful AI models on your own computer, with total
privacy and zero API cost, even if you have never installed
one
* Get real results on a normal laptop with 8 GB of RAM, no
dedicated GPU and no cloud bill, including Mac with Apple
silicon
* Build your first RAG from scratch with embeddings, so the AI
answers from your own documents
* Explore, choose and run open source models from Hugging Face
with Python pipelines
* Command Ollama from zero to advanced: install, Generate vs
Chat, parameters, streaming, System Prompt and roles
* Create your own custom models with a Modelfile, and get
reliable answers with Structured Output and Function Calling
* Understand how an LLM works inside and pick the right model
for the hardware you already own
REQUIREMENTS
* A computer with at least 8 GB of RAM, 16 GB recommended, and
we show you which models run well in each range
* About 20 GB of free disk space to download and store the
models
* Basic comfort with the terminal or command line, the
essentials are taught inside the course
* No dedicated GPU needed, the examples run on regular
laptops,
including Mac with Apple silicon
* No previous experience with AI or machine learning is
required, we start from zero
WHO IS THIS COURSE FOR
* Developers who want to add AI to their applications without
paying for APIs or sending data to third parties
* Professionals who work with sensitive material: proprietary
code, internal documents, client information
* Data professionals and machine learning engineers who want
to
master the open source model ecosystem
* Students and AI enthusiasts who want to see how LLMs
actually
work by running them
* Teams and companies evaluating local LLMs to cut cost and
keep
control of their own data
* Anyone already using ChatGPT, Claude or Gemini who wants
their
own AI running at home
* This is not for someone who wants to train or fine tune a
model from scratch, here we run, customize and integrate
existing open source models
* This is not for someone looking for a zero setup experience,
you will install tools and use the terminal
DESCRIPTION
You heard that you can run AI on your own computer, and the
first thing you thought was: that must be for people with a
monster GPU and a free weekend. It is not. Open source models
got small and good at the same time. A model that needed a
data
center two years ago now answers on a laptop with 8 GB of RAM,
and it answers well enough for real work. This course has a
single promise: by the end of it you will have your own AI
running on your own machine, private and free, and you will
know
exactly which tool to reach for in each situation. The first
win
arrives early. In the opening lessons you already have a model
downloaded and answering on your machine, with the wifi off,
before you create any account or type any card number. You
will
set up your Python environment, run models by task with
Hugging
Face pipelines, install and command Ollama from the terminal,
build custom models with a Modelfile, work with embeddings,
put
together a basic RAG that answers from your own documents, and
run multimodal models locally. You leave with a working local
setup, a map of which models fit which hardware, and the
judgment to choose between a graphical interface and the
terminal for each job. I have taught more than a million
students in over 200 countries, and Rodrigo Macedo builds
every
technical lesson with you on screen. The window is open right
now: the models are free, the tools are free, and the distance
between what runs on your desk and what runs in the cloud has
never been this short. If you have a computer and an
afternoon,
your private AI starts running today. See you inside.
COURSE CONTENT
Chapter 1: Course Introduction
1. Welcome to the Course
2. Why Running AI Locally Changes the Game
Chapter 2: Part 1: Introduction and Use of Open Source LLM
Models
3. Introduction
4. Exploring Hugging Face
Chapter 3: Introduction to Local LLM Models
5. Introduction
6. Why Your Organization Needs Local LLMs
7. Running LLM Models Locally
8. How an LLM Model Works
Chapter 4: Using Models on Hugging Face
9. Introduction
10. Setting Up the Environment
11. Running Models with Pipelines
12. Autotokenizer and Automodel
13. Main Models
14. Final Project
Chapter 5: Part 2: Meet Ollama
15. Introduction
16. Getting to Know Ollama
Chapter 6: Installing and Configuring Ollama
17. Introduction
18. Installing Ollama
19. Ollama Overview and Commands
Chapter 7: First Steps with Ollama
20. Introduction
21. Initial Ollama Setup
22. Generate vs Chat
23. How the LLM Works
24. Parameters and Streaming
25. System Prompt and Roles
Chapter 8: Going Further with Ollama
26. Introduction
27. Modelfile and Custom Models
28. Using Structured Output
29. Working with Embeddings
30. Building a Basic RAG
31. Working with Multimodal Models
Chapter 9: Conclusion
32. Congratulations and Next Steps
DATES
Published : 2026-09-10
Last Updated : 2026-09-10
If you fear the truth, dont come to my well.