Welcome to the AI & Cybersecurity Learning Series by KK Mookhey!
In this introductory chapter, we lay the foundation for understanding the powerful intersection of Artificial Intelligence and Cybersecurity. AI is revolutionizing every industry, but it comes with both incredible opportunities and significant security risks.
What You’ll Learn:
• The Evolution of AI – From Alan Turing’s groundbreaking Turing Test in the 1950s to today’s cutting-edge Generative AI
• Key AI Concepts Demystified – Understanding Machine Learning, Deep Learning, and Large Language Models (LLMs)
• The Double-Edged Sword – How AI detects cyber threats while also enabling sophisticated attacks
• Critical AI Technologies – RAG (Retrieval Augmented Generation), AI Agents, and Multi-Agent Systems
• Challenges & Solutions – Tackling data cutoffs, hallucinations, and security vulnerabilities
Key Topics Covered:
• History of AI: Dartmouth Conference, AI Winters, and Modern Breakthroughs
• Machine Learning vs Deep Learning vs Generative AI
• How Large Language Models Actually Work
• Retrieval Augmented Generation (RAG) for Trustworthy AI
• Agentic AI and Multi-Agent Frameworks
• Building Secure and Reliable AI Applications
What’s Next?
This is just the beginning! In upcoming chapters, we’ll dive deep into hands-on coding, build our first RAG application, dissect it line by line, and learn how to secure AI systems against emerging threats.
About the Instructor:
KK Mookhey is a cybersecurity expert with over 25 years of experience in the field. Through this comprehensive learning series, he brings practical, real-world insights into building, testing, and securing AI-powered applications.
Connect with KK on https://www.linkedin.com/in/kkmookhey/
Course Series:
This video is Chapter 1 of our complete AI & Cybersecurity Learning Series. Subscribe and hit the bell icon 🔔 to get notified when new chapters are released!
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Timestamps:
00:08 – Introduction to AI and Cybersecurity
01:25 – Historical Evolution of Artificial Intelligence
02:36 – Machine Learning and Deep Learning Breakthroughs
04:27 – Emergence of Generative AI and Key Terminology
05:42 – Understanding Large Language Models (LLMs)
07:02 – Limitations and Challenges of LLMs
08:46 – Retrieval Augmented Generation (RAG)
09:58 – Agentic AI and Multi-Agent Systems
11:08 – Recap and Next Steps
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Access the detailed workshop content, including key topics, frameworks, and practical takeaways, here: https://docs.google.com/document/d/1NkGZthHxy3QWdkyeDKC_TB2gFOk2H0n-BKZVZjXwq-Q/edit?tab=t.6ypecfaymbgh
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