Session 1 Learning Objectives
- Explain the basics of AI
- Describe properties of AI
- Identify resource requirements for adopting AI
- Articulate expert systems (e.g., temporal reasoning, logic and inference)
- Distinguish machine learning models (e.g., decision trees, regression models, Bayesian)
Session 2 Learning Objectives
- Describe machine learning algorithms (e.g., supervised learning, unsupervised learning, deep learning)
- Describe enterprise usage of artificial intelligence (e.g., RPA, log analysis, image processing, NLP, fraud detection, cybersecurity, healthcare)
- Identify consumer usage of artificial intelligence (e.g., autonomous vehicles, digital assistants, freelance mobile marketplace)
- Identify risks associated with artificial intelligence (e.g., cybersecurity, privacy, data loss)
- Articulate ethical dilemmas in artificial intelligence (e.g., privacy, bias, nefarious usage)
