Experiential Learning AI Training Program
What is Experiential Learning AI?
ExLAI (Experiential Learning AI) is an eight-week, in-person training program that aims to create pathways in Trustworthy Artificial Intelligence (TAI) for community college students.
What is TAI?
Trustworthy Artificial Intelligence is the study of making Artificial Intelligence (AI) safe and trustworthy for real-world applications. This includes topics like Robustness, Privacy, Interpretability, Alignment, and Fairness.
Why ExLAI?
The explosive development and application of AI systems highlight an increasing demand for AI professionals in TAI to ensure AI systems behave as expected when deployed and minimize the risk of AI safety issues. The ExLAI program provides a pathway to both research and industry as a TAI professional.
When is ExLAI?
Program start date: May 12, 2025
Program end date: July 3, 2025
Eligibility: Students currently enrolled in a community college and are US citizens or permanent residents are eligible to participate in this program.
Financial support: Each selected student gets a $2,400 stipend and $400 travel support if needed.
Program Structure
Over eight weeks, we will extensively cover both technical lectures and engage in hands-on research. Lectures initially provide foundational knowledge in AI and topics in TAI. Students will join small research groups, led by an AI expert, to learn about the research process and will develop novel advancements in their chosen topic in Trustworthy AI.
Key Activities: Workshops, hands-on exercises, networking forums, cybersecurity games, and career workshops.
| Week | Lecture Schedule | Research Schedule |
|---|---|---|
| 1 | Program Orientation: Introductions, goals, and expectations, followed by an overview of the AI workforce. ExLAI scholars are introduced to projects, team assignments, AI concepts, applications, and ethical considerations. | Functioning in a Research Team: Scholars will learn how to read and discuss primary scientific literature. The path to submitting a conference or journal article will be outlined using overview of projects by both academic and industry mentors. AI security and assurance will then be introduced so that program members can begin discussing research plans. |
| 2 | Programming & Data Skills: Introduction to Python programming and data manipulation using hands-on exercises. | Research Integrity: Program participants will explore the importance of replicability, transparency, and data availability in research. We will cover standard practice in handling data as well as experimental design. Oral progress reports on project status will be given. |
| 3 | Machine Learning (ML) Fundamentals: We will demonstrate supervised and unsupervised learning applications, followed by their practical implementations. | Trustworthy AI (TAI) Project Research: Scholars will work in small groups with their mentors to develop a novel contribution to the field. Examples of topics include explainable AI, AI fairness and bias, AI ethics, AI accountability and responsibility, AI security, human-AI interaction, AI in autonomous systems, AI and cybersecurity, and AI in applications. |
| 4 | Deep Learning: An introduction to deep neural networks and their frequently used libraries, including PyTorch and Tensorflow. ExLAI scholars will then construct a basic neural network. | Trustworthy AI (TAI) Project Research Continued |
| 5 | Ethics and Bias in AI: Learn about ethical dilemmas in AI, and the transferability of human bias to AI. We will further examine these phenomena in case studies. | Trustworthy AI (TAI) Project Research Continued |
| 6 | AI Tools and Platforms: Utility and capabilities of cloud-based AI services including AWS, Google AI, and Azure | Trustworthy AI (TAI) Project Research Continued |
| 7 | AI for Social Good: Examine the potential for AI to be used in addressing social issues using hands-on exercises. | Communicating Your Science: ExLAI scholars will prepare posters, presentations, and progress reports, learn scientific writing, submit papers, and present their research results. |
| 8 | Final Project and Presentations: Finalize the projects with the guidance and support of mentors. Project showcases, ceremony, career guide, and feedback sessions will conclude the program. | Report Your Science: During the final week of the program, scholars will practice reviewing scientific research, as well as present their own findings and respond to recommendations. Lastly, the program industry career day will open opportunities for scholars to continue in the field. |
Certificate
Get an ExLAI Certificate at the end of the program to show your commitment and experience in Trustworthy AI.
Research Opportunities
- TAI Research Hub: UC’s hub focuses on AI ethics, transparency, and security.
- Experiential Learning in Research: Research activities and hands-on project involvement, with an opportunity to publish your research at the end of the program.
Career Opportunities
ExLAI scholars will work closely with industry professionals and academic experts. Program participants will engage in workshops and webinars led by professionals, providing a path to careers in the AI workforce.
Application
- Application deadline: March 21, 2025
- Application Requirements: Resume/CV, Transcript, and one recommendation letter.
- Selection Criteria: Based on academic excellence and commitment to AI careers.
Contact
Primary Investigator: Dr. Justin Zhan: Justin.Zhan@uc.edu (513-556-7616)
Hanniel Shih: shihhh@mail.uc.edu
Kate Plas: plaska@mail.uc.edu
Computer Science Program Coordinator - Dorothy Young: 513-556-2988