BCR Cyber adds AI course to cybersecurity training programs

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BCR Cyber, a Baltimore-area cybersecurity training center and provider, announced it has added the Introduction to Artificial Intelligence to its training programs.

The one-week, 40-hour course will aim to introduce students to the “core concepts of AI and machine learning within the context of Security Operations Centers,” according to BCR Cyber. The course is designed for BCR Cyber students with little to no AI experience, hoping to instill a firm, foundational understanding of AI and machine learning technologies in cybersecurity operations, the organization said. 

Combining lectures, hands-on tabletop exercises and case studies, the AI course includes eight modules covering AI history and fundamentals, cybersecurity, data, neural networks, generative AI and more.

The AI course was developed in collaboration with tech expert Nick Reese, who has worked with the U.S. Department of Homeland Security‘s emerging technology policy team, the White House, and other government agencies across the nation and the globe, providing expertise on national technology policy and cutting-edge AI capabilities.

“AI has quickly become a significant element of cybersecurity and continues to grow – from AI-enabled attacks to AI cyber defense tools, so it’s crucial for SOC operators to be AI proficient,” BCR Cyber President and CEO Michael Spector said. 

“By bridging foundational AI instruction with our hands-on training, our course helps prepares students to understand, evaluate, and operate AI-enabled SOC tools.”

The Introduction to AI for Security Operations Centers course will be offered as part of BCR Cyber’s Cybersecurity Operational Methods Education and Training and Intrusion Countermeasures Education & Training programs.

The course will enable students to:

• Explain foundational AI/ML concepts relevant to cybersecurity and SOC environments;
• Identify and analyze AI/ML applications in cybersecurity operations;
• Understand how different AI training methods impact system performance and outcomes;
• Interpret AI system outputs within security workflows;
• Integrate AI/ML best practices into SOC operations;
• Navigate ethical and operational challenges related to AI in cybersecurity