4 Weeks /Instructor Led/Weekly Modules/Digital Credentials

Discounts

If you are from a community college, please acquire your code from the ION contact at your institution or email ion@uis.edu before registering. Community college members must also use their college email for verification.

Description

AI has the potential to be a valuable tool in education. In this course we hope to capitalize on what you learning in the first AI course and make your journey with AI smoother, richer, and more productive.  We'll dive deeper into the workings of AI, its use in your life, both inside and outside of education, and its implications on the future of education.

Program

ION Professional eLearning Programs 4 CEU hours. 

Outcomes

As a result of completing course activities and interacting in discussion forums, learners will be able to:

  • Comprehend the fundamental architectures of large language models
  • Gain practical knowledge of fine-tuning pre-trained language models for specific downstream tasks
  • Be able to critically examine the ethical implications of deploying large language models
  • Be able to evaluate language models effectively
  • Be able to utilize the principles of effective prompt design, including clarity, specificity, and context-awareness
  • Understand the nuances of multimodal prompts, combining text, images, and other modalities
  • Be able to use techniques for identifying and mitigating biases in prompts
  • Understand how prompt engineering impacts model performance and adaptability
  • Evaluate prompt quality and its impact on AI model behavior
  • Understand fundamental concepts of intelligent agent architectures, including reactive agents, deliberative agents, and hybrid models
  • Understand decision-making processes within agents, such as utility-based decision models, reinforcement learning, and Bayesian networks
  • Critically examine the ethical and societal impact of intelligent agents
  • Critically evaluate the ethical challenges posed by AI in education, considering issues such as bias, privacy, transparency, and accountability
  • Evaluate the effectiveness of policies related to AI adoption in educational setting, including understanding legal frameworks, stakeholder engagement, and the practical steps required for policy implementation
  • Assess the impact of AI policies on educational outcomes, student experiences, and equity

Prerequisite  

AI: The Future Of Learning