Overview What You Will Learn Curriculum Instructor

Course Overview

In the intricate realm of cybersecurity, a revolutionary development has emerged with the advent of Artificial Intelligence (AI), specifically the subset known as Generative AI. Large Language Models (LLMs), as a part of Generative AI, have created significant ripples in the security sector. Their influence is so profound that understanding them, their architectural design and the underlying technology stacks is not just advantageous, it's imperative. Neglecting these aspects could result in overlooked security vulnerabilities that could compromise your defenses. 

We begin by deciphering Generative AI, with a focus on LLMs, elucidating their complex concepts into understandable terms. We then explore the architectural design patterns and technology stacks that form the backbone of Generative AI applications, paying special attention to potential security pitfalls. This deep dive will equip you to preempt and effectively address security issues. But the course isn't just rooted in theory - we also offer hands-on demonstrations and lessons for a direct experience of applying Generative AI, including LLMs, in cybersecurity. The course starts with an introduction to Python, Google Colab, Pytorch, and the basic principles of fine-tuning LLMs, a critical component of Generative AI. Following this, we showcase how to use Google Colab and Huggingface's open-source LLMs with security datasets to fine-tune a model for cybersecurity applications. 

By mastering Generative AI, including LLMs, you will increase your organization's resilience against an ever-growing range of cyber threats. It's time to seize this opportunity to augment your cybersecurity skills. Embrace Generative AI - the future of cybersecurity is here.

What You Will Learn

  • Learn to master the fundamentals of Generative AI and its security impacts.
  • Acquire a comprehensive understanding of Large Language Models (LLMs), their role in cybersecurity, and the potential security risks in Generative AI applications, including LLMs.
  • Comprehend architecture and tech stacks.
  • Empower to identify and mitigate potential security pitfalls.
  • Implement secure Generative AI-powered applications.
  • Hands-on experience fine-tuning open-source LLMs for cyber defense, backed by guided exercises and real-world examples.
  • Practical understanding of AI tools for security.
  • Learn how to use various AI tools for enhancing application security, thereby expanding your toolkit of cybersecurity resources.
  • Learn to make informed choices: Cultivate the capability to make knowledgeable decisions on the usage of open-source vs. closed-source LLMs, based on their advantages and disadvantages in differing scenarios.
  • Learn to equip yourself with the most recent knowledge and skills in AI and LLMs, ensuring that you remain at the cutting edge of the ever-evolving cybersecurity landscape.

Program Curriculum

  • Introduction to Generative AI (GenAI) and LLMs: A New Era in AI
  • The Inner Workings of LLMs
  • The Broad Application Spectrum of LLMs
  • $7 Million Cybersecurity Scholarship by EC-Council
  • Chapter 1 Quiz

  • Architecture Design Patterns of LLM-powered Applications
  • Security in LLM-powered Application Architecture
  • Chapter 2 Quiz

  • Choosing the Right Technology Stack for LLM Applications
  • Maximizing Security in LLM Technology Stacks
  • Chapter 3 Quiz

  • Evaluating Open vs. Closed-sourced LLMs
  • Tools for Evaluating Open-sourced LLMs
  • Closed-sourced LLMs in Specific Use Cases
  • Chapter 4 Lab
  • Chapter 4 Quiz

  • Prompt Engineering and LLM Fine-tuning
  • Introduction to Fine-tuning
  • Code Walkthrough Fine-tuning LLMs
  • Summary and Final Thoughts
  • Chapter 5 Lab
  • Chapter 5 Quiz
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Instructor

Ken Huang

Ken currently serves as the CEO of DistributedApps.ai, a consulting company in Generative AI. He is also the Chair of the Blockchain Security Working Group for the Cloud Security Alliance Great China Region (CSA GCR), where he collaborates with top experts to create impactful white papers on key security topics. Ken's recognition as an authority in the field has seen him serve as a judge for AI and blockchain startup contests organized by Google, Softbank, and Stanford. He's a frequent speaker at prestigious global events, including those hosted by Davos WEF, CoinDesk Consensus, IEEE, ACM, World Bank, and Stanford University.

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