This is an official ISACA course, it introduces you to the fundamental topics of Artificial Intelligence (AI), essential for every security professional, a growing and rapidly changing field that is becoming increasingly vital to business survival, job stability, and national security.
The ISACA Artificial Intelligence Fundamentals Certificate is intended for a wide-range of individuals, including:
- IT Audit, Risk, Security and Governance professionals looking to gain a fundamental understanding of emerging technology knowledge and skills.
- Those new to IT, students, recent graduates and career changers looking to differentiate themselves from other job candidates.
- Current IT Professionals looking to upskill to broaden their IT knowledge and skills or keep up-to-date with emerging technologies.
This course is not a technical security course and does not cover generative AI ‘prompt’ security engineering.
Delegates will learn how to
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
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