Courses

Practicum AI is a hands-on applied Artificial Intelligence learning curriculum intended for beginners in AI with limited coding and math background. Our approach is to use visual and conceptual explanations, coupled with hands-on coding exercises to lead learners through a progression of content from beginner to more advanced. AI is not just for computer scientists and we seek to broaden diversity of both AI practitioners and the domains where AI is applied. Our content is open source and freely available for learners as well as instructors who may want to adapt modules for their own teaching. For those wishing to obtain certificates, the content will also soon be available via UF Professional and Workforce Development.

Getting Started

Introduction to Artificial Intelligence and Practicum AI Welcome! This is the place to start your AI journey. Here we introduce you to artificial intelligence–it’s a term we hear a lot, but can you define it? Did you know that AI research dates ...

Computing for AI

Welcome to the Practicum AI: Computing for AI Course! This course is the second in the Practicum AI beginner series. This course can also be taken on its own to familiarize yourself with some important tools used in computational science applicat...

Python for AI

Artificial Intelligence has advanced a lot, but still requires human input. Humans must still prepare the data, setup and train the models, and interpret the results. These steps, while increasingly assisted by AI itself, require some understandin...

Deep Learning Foundations

Deep learning is the focus of modern AI. Models have many layers and millions, or now approaching a trillion, parameters! This course breaks things down and introduces you to a small AI model to provide a conceptual understanding of how AI models ...

Computer Vision

Computer vision primarily refers to the field of computer science that focuses on developing techniques that enable computers to understand and interpret visual information from the world. It involves algorithms and systems for acquiring, processi...

Transfer Learning

For the vast majority of AI practitioners, there is little need to develop models from scratch! In most cases, there are models that have already been developed and can be reused either directly or with minimal modification for new tasks. Transfer...

FAIR Data for AI

This module covers making data for AI/ML FAIR (Findable, Accessible, Interoperable, and Reusable). Development of these FAIR AI/ML training modules was supported by a supplement to NIH/NIGMS T34GM118272 (D. Julian, PI; 08/01/2021-05/31/2023). ...

Learning Paths

While each course stands on its own, we recommend following the sequencing, especially for the beginner series.

Practicum AI Beginner Series

Getting started in AI The Practicum AI Beginner series has four courses that lead beginning learners through an introduction to AI, ethical considerations, an overview of the computational tools used in applied AI, an introduction to the Python p...

Practicum AI Intermediate Series

Keep learning AI Intended for learners who have a basic foundation in Python and AI (those that have completed the Practicum AI Beginner Series), the Practicum AI Intermediate series has six modules. These modules each focus on a particular metho...