AI 101/201 Crash Courses

Event

Thursday, December 17th - 1:00PM - 5:00PM

Location

Room 4-110

Facilitator

Chris Prokes - Director of the AI Excellence Institute

Description

In this session, we will deliver a crash course of AI 101 - AI Fundamentals and AI 201 - AI Systems in Practice. Participants will be able to engage with either the online version of these courses or an in person version.

AI 101 will be from 1-3 and AI 201 will be from 3-5.

Asynchronous versions can be done during this window if that is preferred, and participants will have appropriate badges awarded as part of the Institute and personal goals for the year.

Audience

Faculty and staff

Pertinent FPR or Staff Evaluation Alignment

• Individual/Other Goals – Faculty
• Teaching/Learning Facilitation (Faculty CPA #2)
• Assessment and Evaluation (Faculty CPA #3)
• Curriculum Development & Design (Faculty CPA #5)
• Individual/Other Goals – Staff

Objectives

AI 101
- Discover the core concepts of artificial intelligence, its evolution, and its impact on modern life. This module covers the basics of machine learning and neural networks, as well as the key milestones that have shaped AI. You’ll gain a balanced perspective on both the possibilities and limitations of AI.

- Learn how to engage with AI tools ethically and thoughtfully. Explore the importance of human oversight, privacy, transparency, and academic integrity. This module will guide you in making informed, responsible decisions about when and how to use AI in academic and professional settings.

- Develop practical skills to communicate effectively with generative AI systems. You’ll master the art of crafting clear, purposeful prompts and evaluating AI-generated responses, ensuring you get reliable and relevant results.

AI 201
- Investigate emerging patterns for collaborating with AI as part of day-to-day work, with attention to task design, human judgment, and effective division of labor.

- Evaluate AI use through the lens of privacy, overreliance, decision impacts, user well-being, and the continuing need for accountable human involvement.

- Explore how AI assistants and knowledge-based systems can support access to information, workflow execution, and informed decision-making.

- Examine AI systems that can plan, act, and complete multi-step work with varying levels of autonomy, including the role of human oversight and safeguards.

- Consider practical deployment approaches for large language models (LLMs), including how organizational needs may shape choices around access, control, privacy, and integration.