Exclusive AI Education Resource Hub

A curated repository of curriculum, materials and training designed specifically for community colleges to teach AI.

Tools for AI Education

The AI Education Resource Hub is a gateway to a growing collection of resources, tools and materials designed to support community colleges in delivering high-quality applied AI education.

Exclusive Member Resources
Available to approved members:

• AI Courses syllabi and curriculum models

• Canvas course exports

• Faculty workshop recordings and materials

• Program implementation guides

• KSA frameworks

Membership is free and available to faculty and staff with a valid .edu email account.

Register for free to access our resources using your .edu e-mail account.

Resources

Filters
Clear all
Tag
AI Academic Guide for Advisor
Miami Dade College
Advisor guide
AI
AWS AI Practitioner Info Session
Info Session Video
Past Events
Google Career Dreamer Webinar
Info Session Video
Past Events
AI Application Solutions - Course Syllabus
Miami Dade College
Syllabus
Capstone
Applied AI
AI in History, Theory and Platforms - Course Syllabus
Houston Community College
Syllabus
AI
AI History
AI in History, Theory and Platforms - Course Outline
Houston Community College
Curriculum
Course Outline
AI
AI History
AI and Ethics - Course Syllabus
Miami Dade College
Syllabus
Ethics
Associate's degree in Applied AI - Program Sheet
Miami Dade College
Curriculum
AI
Program Sheet
NAAIC Community of Practice Lightning Round
Info Session Video
Past Events
Computer Vision for AI - Course Syllabus
Houston Community College
Computer Vision
Syllabus
CV
Computer Vision for AI - Course Outline
Houston Community College
Curriculum
Course Outline
Computer Vision
CV
Data Science for AI and Robotics - Course Syllabus
Houston Community College
Syllabus
Data Science
DS
Robotics
Data Science for AI and Robotics - Course Outline
Houston Community College
Curriculum
Data Science
DS
Course Outline
Deep Learning in AI - Course Syllabus
Houston Community College
Deep Learning
Syllabus
DL
Deep Learning in AI - Course Outline
Houston Community College
Curriculum
Course Outline
Deep Learning
DL
NAAIC Information Session
Info Session Video
Past Events
Intro to AI - Course Outline
Maricopa Community Colleges
Curriculum
Course Outline
AI
AI Thinking - Course Syllabus
Miami Dade College
Syllabus
AI
Intro to Computer Vision - Course Syllabus
Miami Dade College
Syllabus
Computer Vision
CV
Introduction to Machine Learning - Course Syllabus
Houston Community College
Syllabus
Machine Learning
ML
Introduction to Machine Learning - Course Outline
Houston Community College
Curriculum
Course Outline
Machine Learning
ML
Intro to NLP - Course Syllabus
Miami Dade College
Syllabus
Natural Language Process
NLP
ML Foundations - Course Syllabus
Miami Dade College
Syllabus
Machine Learning
ML
Natural Language Processing - Course Syllabus
Houston Community College
Syllabus
Natural Language Process
NLP
Natural Language Processing - Course Outline
Houston Community College
Curriculum
Course Outline
Natural Language Process
NLP
AI Thinking course - Canvas shell
Miami Dade College
Canvas Shell
Ready-to-Use
AI
AI Thinking
ML Foundations course - Canvas shell
Miami Dade College
Machine Learning
ML
Canvas Shell
Ready-to-Use
Introduction to NLP course - Canvas shell
Miami Dade College
Natural Language Process
NLP
Canvas Shell
Ready-to-Use
AI Application Solutions course - Canvas shell
Miami Dade College
Applied AI
Canvas Shell
Ready-to-Use
Intro to Computer Vision course - Canvas shell
Miami Dade College
Computer Vision
CV
Canvas Shell
Ready-to-Use
AI and Ethics course - Canvas shell
Miami Dade College
Canvas Shell
Ready-to-Use
Ethics

Do you have resources to share?

Contribute to the repository by sharing your course materials, syllabi, or teaching tools to support peer faculty nationwide.

Resource Hub Disclaimer

The information and materials provided in the National Applied AI Consortium (NAAIC) AI Education Resource Hub are intended for general informational purposes only. While NAAIC strives to ensure the accuracy and relevance of the content, we make no representations or warranties of any kind, express or implied, about the completeness, accuracy, reliability, suitability, or availability of the information contained therein.

Any reliance you place on such content is strictly at your own risk. We do not assume any responsibility for errors, omissions, or inaccuracies in the catalog. Additionally, the inclusion of any specific resource does not constitute an endorsement or recommendation by us. All works contained in the resource catalog are submitted by third parties. Any opinions, findings, conclusions or recommendations expressed in these materials are those of the author(s) and do not necessarily reflect the views of NAAIC. Furthermore, we disclaim liability for any direct, indirect, incidental, consequential, or punitive damages arising out of or in connection with the use of our resource hub. This includes but is not limited to loss of data, revenue, or profits.

Users are encouraged to independently verify the accuracy and relevance of any information before making decisions based on it. If you have specific concerns or questions about any content, please seek professional advice or consult the original sources. By accessing and using our resource hub, you agree to these terms and conditions. If you do not agree with any part of this disclaimer, please refrain from using our resources.