Artificial Intelligence (AI) Security Fundamentals Training

No prequisites

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)

Course Topics Include:

Session 1 Topics:

• Properties of Artificial Intelligence Condensed version
• Resource Requirements for Adopting AI
• Expert Systems
• Machine Learning Models

Session 2 Topics:

• Statistical Modeling
• Machine Learning Algorithms
• Enterprise Usage of Artificial Intelligence
• Consumer Usage of Artificial Intelligence
• Risks Associated with Artificial Intelligence
• Ethics in Artificial Intelligence