AI-Driven Defensive Cybersecurity: One-Day Intensive Workshop – May 13(Tuesday) 2025

Register Now!Price $900

Hands on AI-Driven Cybersecurity training. This one-day intensive course is designed to equip cybersecurity professionals with the skills and knowledge needed to leverage artificial intelligence in combating cyber threats. We will go through the basics of ML/AI theoretical concepts and perform hands-on exercises on related technologies and tools applied to threat detection, incident response, vulnerability management and more. 

We will focus on real-world scenarios where using ML/AI can amplify your current knowledge and skills and get you ready to embrace ML/AI in your cybersecurity career. 

Who is this course for?

This course is ideal for entry-level, junior  professionals in cyber security, IT staff, and anyone interested in understanding the impact of AI on defensive cyber security.

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Hardware & Minimum Course Requirements:
A laptop with 16GB of RAM and the ability to run Virtual Machines. Understanding of basic networking concepts and basic Linux comprehension. Apple M chip laptops are incompatible with the materialused in this course. Recommended OpenAI, HuggingFace API access. 

Skills that will be learned:

In the “Hands-on AI-Driven Cybersecurity Training” course, participants will gain essential skills in leveraging artificial intelligence & Machine Learning to enhance their cybersecurity capabilities, including use of ML tools available in the security industry, cloud based and local AI LLM models, applied to real world scenarios.

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Trainer(s) bio:

Rod Soto has over 15 years of experience in information technology and security. Has worked in Security Operations Centers as a support engineer, soc engineer, security emergency response, and incident response. Previously worked at Prolexic/AKAMAI, Splunk UBA, JASK (SOC Automation).
Rod Soto was the winner of the 2012 BlackHat Las Vegas CTF competition and Red Alert ICS CTF at DEFCON 2022 contest. Currently working as a detection engineer and researcher at Splunk Threat Research Team covering Machine Learning and GenAI model development.

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