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Course Description

Courses taken through this site at $20 each, or $50 for all 4 courses in the Beginner series (discount code: bundleai).

UF faculty, staff, and students can get a discount code for free access from the UFIT Research Computing Practicum AI page.

Presented by UFIT Research Computing, Practicum AI is a hands-on AI curriculum intended for learners with limited coding and math backgrounds. Using interactive exercises and graphically based conceptual content, our hope is to support learners who seek to begin exploring applied AI. 

The beginner series of courses includes: 

  1. Getting Started with AI: An introduction to AI, AI models and their development, and AI Ethics. 

  1. Computing For AI: An introduction to the computational tools used in AI—Git and GitHub.com, and Jupyter Notebooks, run on either a high-performance computer system or Google Colab. 

  1. Python for AI: An introduction to the basics of Python programming and data science tools used in AI. We don’t cover everything but instead focus on the core aspects needed for applied AI. We also introduce strategies for working with AI coding assistants to accelerate your skills! 

  1. Deep Learning Foundations: An introduction to neural networks, deep learning, and how to train AI models using the skills you’ve gained in previous courses. 

Cost: 

  • Courses taken through this site at $20 each, or $50 for all four courses (discount code: bundleai) in the Beginner series. This includes: 

  • In-course quizzes to check your learning. 

  • Digital badges from Credly for completing each course. 

  • Practicum AI Beginner Series Digital Certificate from Credly if you complete all four Beginner Series courses. 

  • Our goal is to build AI knowledge. If you don’t want the quizzes, badges, and certificate, enjoy the content for free! 

  • All course content can be found in Canvas Commons. Instructors who use Canvas can easily import our content and re-use it for free in their own courses. 

Note: Course enrollment does not include access to UF’s high-performance computing environment, HiPerGator. You may use your existing HiPerGator resources, or all content can be completed using a free Google account. Detailed instructions are provided for each use case. 

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Enroll Now - Select a section to enroll in
Section Title
Getting Started with AI
Type
self-paced
Dates
Start Now, you have 365 days to complete this course once enrolled.
Course Fee(s)
Registration Fee non-credit $20.00
Drop Request Deadline
TBD
Transfer Request Deadline
TBD
Section Notes
This course is intended to be the first in a series to teach you some tools and techniques to begin training and deploying models independently. The course can also be taken on its own to familiarize yourself with the essential concepts in Artificial Intelligence.
Section Title
Computing for AI
Type
self-paced
Dates
Start Now, you have 365 days to complete this course once enrolled.
Course Fee(s)
Registration Fee non-credit $20.00
Drop Request Deadline
TBD
Transfer Request Deadline
TBD
Section Notes
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 applications.  
Section Title
Python for AI
Type
self-paced
Dates
Start Now, you have 365 days to complete this course once enrolled.
Course Fee(s)
Registration Fee non-credit $20.00
Drop Request Deadline
TBD
Transfer Request Deadline
TBD
Section Notes
The content in this workshop is aimed at beginning coders who may have never programmed before. As with the rest of the Practicum AI workshops, we use Jupyter Notebooks for the learning experience. Jupyter Notebooks are an easy-to-use yet powerful tool that allows interactive coding and nicely formatted explanatory text. Much of exploratory AI research is conducted in Jupyter Notebooks, and it is easy to transfer code from Notebooks to scripts when it is time to scale up analyses.
Section Title
Deep Learning Foundations
Type
self-paced
Dates
Start Now, you have 365 days to complete this course once enrolled.
Course Fee(s)
Registration Fee non-credit $20.00
Drop Request Deadline
TBD
Transfer Request Deadline
TBD
Section Notes
This course is intended to demystify the concepts of neural networks and deep learning. We will touch on how neural networks work, how to use them and why neural networks have dominated AI research in the past decade. The first module of this course provides a high-level overview of deep learning and some hands-on experience with using these models. This course builds on the previous Practicum AI courses and will require some knowledge of Python, Jupyter Notebooks, and high-performance computing environments. 
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