Are you excited about using AI in your product but intimidated by all the jargon and complexity? The multitude of random third-party products? Let’s cut through all the fluff: Let me show you how to customize an AI from scratch — and in 3 quick steps.

This course is designed for entrepreneurs, developers, product managers, and curious learners who want to build powerful, custom AI applications—without expensive APIs or third-party subscriptions. You'll discover the fundamental steps to creating practical, tailored AI solutions using entirely free, open-source tools. And most importantly, we'll improve your LLM's capabilities without any training.

What You'll Learn

Here’s what we’ll do—fast:

Pick a real, text-in/text-out problem you care about.
Define the input, the output, and a quick metric so we can judge quality.
Try the top model in chat, then the API for repeatable results and cost checks.
Step down to the cheapest model that still passes your metric.
Make it reliable with prompt structure and constrained outputs (so it always returns the format your app expects).
Spin up a small open-source model on free GPUs and wire it up, so you’re not blocked by budget.

No expensive training is required and we go a step deeper than just "prompt ChatGPT".

Who is this class for?

No prior AI or coding experience required—just curiosity and a desire to learn. Whether you're a beginner or have some technical background, you'll leave with actionable knowledge and the confidence to start building tailored AI solutions. With that said, you’ll get more from the course if you first take my Artificial Intelligence for Beginners: How to Learn Machine Learning and Artificial Intelligence for Beginners: How ChatGPT works.

Resources Required:

Computer (Windows, macOS, or Linux)
Google Chrome browser
Google account
No paid APIs or third-party services

Ready to Dive Deeper?

Interested in advanced machine learning? Try my Computer Vision 101 (Applied ML) course.
Want to code? Check out Coding 101 (Python) or OOP 101 (Python).
Interested in data? Explore SQL 101 (Database Design) or Data 101 (Analytics).

Sindy Arboleya

2

2