Artificial Intelligence for Cyber Security Certificate
As artificial intelligence (AI) becomes an integral part of industry and economy, cyber security professionals need to know how to define the scope of AI and its implications. Gain a new perspective on what artificial intelligence is — and what it isn’t — through the Artificial Intelligence for Cyber Security certificate.Enroll
As the most critical technology integral to the success of the U.S., artificial intelligence has the power to reshape everything we do. Explore the history, function and future of artificial intelligence as an industry-agnostic tool through the Artificial Intelligence for Cyber Security certificate.
This career-specific certificate will prepare you with an advanced understanding of how to use AI, and how to secure against risks and the growing presence of AI as a national security concern. Special topics include deepfakes, social media and the role of AI in cyber attack and defense.Enroll
Estimated Time to Complete
*Students have up to one year to complete the certificate from the time of registration.
Tuition: $5,000 with a 10% discount if you pay in full
Projected employment growth for information security analysts by 2030 (U.S. Bureau of Labor Statistics, 2021)
AVERAGE BASE SALARY
For cyber security professionals (Payscale, 2022)
Projected number of unfilled cyber security jobs globally by 2025 (Cybersecurity Ventures, 2021)
By critically assessing the role and ramifications of artificial intelligence in our lives, your Artificial Intelligence for Cyber Security certificate will prepare you to:
- Articulate a taxonomy and terminology of Adversarial Machine Learning (AML).
- Articulate a conceptual hierarchy, including key types of attacks, defenses and consequences.
- Articulate the four principles for explainable artificial intelligence that comprise the fundamental properties for explainable AI systems.
- Identify the five categories of explainable AI and major classes of explainable algorithms.
- Identify the distinct requirements for machine learning systems, as well as experimental psychology pertaining to interpretation and comprehension.
- Articulate the unique challenges for user trust in AI systems.
- Identify and manage bias in AI systems.
- Articulate the critical issues related to AI and machine learning, specifically AI and ML impact on cyber security.