About This AI Online Course
As artificial intelligence and machine learning is increasingly integrated into military decision making, surveillance and autonomous systems, the ability to understand and defend against adversarial threats becomes mission-critical.
To safeguard mission success in an increasingly AI-driven battlespace, it is essential that U.S. Department of Defense personnel—both military and civilian—and the government contractors supporting defense operations possess at least a foundational understanding of adversarial machine learning threats, methods for monitoring them, and the strategies needed to defend against these emerging risks.
This self-paced, online course provides an essential introduction to the vulnerabilities and security challenges associated with machine learning systems, with a particular focus on their implications for DoD operations.
Through real-world examples—including the brittleness of commercial algorithms during sudden global events and misclassification of threats like unmanned aerial vehicles—you will explore how machine learning models can be manipulated through attacks, such as data poisoning, Trojan insertion, backdoors, evasion and inference. These attacks can compromise everything from fraud detection and surveillance to tactical battlefield awareness.
You will examine why traditional accuracy testing is insufficient for high-stakes DoD environments, where adversaries actively attempt to exploit system weaknesses. Learners will gain a foundational understanding of how to recognize and respond to these vulnerabilities using methods, such as adversarial training, outlier detection and differential privacy.
The course also reinforces the need for an integrated, security-focused approach to machine learning development—aligning with concepts like DevSecOps—to ensure AI-enabled systems are both effective and resilient against adversarial use.
What You Will Learn
- Evaluate the effectiveness and limitations of machine learning algorithms when applied to cybersecurity use cases
- Describe common adversarial machine learning attacks and their implications for model security
- Explain the challenges of defending machine learning models against adversarial attacks
This online course is aligned with DoD strategies.
Who Should Take This Online Course
This online course is perfect for any DoD, Intelligence Community agency or government contractor company professional interested in gaining a basic understanding of AI and machine learning security in defense environments.
Prerequisites
None. However, prior completion of the FedLearn course, Introduction to AI/Machine Learning Concepts & Terminology (AIDATA109), is recommended.
Course Certificate
To achieve a course certificate of completion, you must score 80 percent or higher on graded lesson quizzes and a final exam.
Course Format
Self-paced, online training course
Course Pricing
Individual courses are $9.99 (per person).
Seat licenses to access the entire FedLearn AI and data science catalog are also available. Click here to learn more and purchase
If you are interested in learning about special team rates for Federal government and government contractor organizations, email [email protected]
Continuing Education Unit Credits
This course provides 1 CEU.
