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Master LLMs for Cybersecurity: Threat Detection & AI Defense 2024

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2:52:10

  • 01 Introduction to LLMs and LLM agents f.mp4
    00:47
  • 02 Prerequisites of the course.mp4
    03:02
  • 03 What can be learned in this course.mp4
    02:39
  • 04 Google Colab and other important tool.mp4
    03:59
  • 05 How to make the most of this course.mp4
    02:09
  • 06 GenAI a.mp4
    05:30
  • 07 Importa.mp4
    03:44
  • 08 Open so.mp4
    04:21
  • 09 Assets.mp4
    04:00
  • 10 Fine-tu.mp4
    02:31
  • 11 Challen.mp4
    01:25
  • 12 Solutio.mp4
    03:53
  • 13 New evolving threats, power.mp4
    03:10
  • 14 Advanced attacks by hackers.mp4
    03:05
  • 15 How cybersecurity professio.mp4
    02:03
  • 16 Synthetic data generation I.mp4
    02:11
  • 17 Synthetic data generation C.mp4
    03:33
  • 18 Challenge Identify phishing.mp4
    01:57
  • 19 Solution Fine-tune LLMs wit.mp4
    06:11
  • 20 Introduction.mp4
    02:25
  • 21 Blockchains.mp4
    03:35
  • 22 Out-of-the-b.mp4
    02:43
  • 23 Fine-tuning.mp4
    02:32
  • 24 Training the.mp4
    02:54
  • 25 Inference an.mp4
    02:30
  • 26 Introduction to OSINT and ho.mp4
    02:42
  • 27 Introduction to agents and a.mp4
    03:27
  • 28 Agent frameworks and Crew AI.mp4
    04:00
  • 29 Planning the agents, their t.mp4
    03:10
  • 30 Setting up the project LLMs,.mp4
    05:49
  • 31 Finishing touches and analyz.mp4
    04:37
  • 32 Introdu.mp4
    03:57
  • 33 Plannin.mp4
    03:40
  • 34 Getting.mp4
    06:25
  • 35 Analyzi.mp4
    05:17
  • 36 Setting.mp4
    04:18
  • 37 Kicking.mp4
    03:30
  • 38 Introduction to LLM-powered f.mp4
    02:33
  • 39 Planning the approach.mp4
    02:58
  • 40 Network data gathering and st.mp4
    04:11
  • 41 Data preprocessing.mp4
    03:32
  • 42 LLM setup.mp4
    03:33
  • 43 LLM fine-tuning.mp4
    03:07
  • 44 Inference output and closing.mp4
    02:13
  • 45 Threats of t.mp4
    02:40
  • 46 LLM powered.mp4
    02:07
  • 47 Decentralize.mp4
    03:12
  • 48 Swarm learni.mp4
    02:52
  • 49 Predictive s.mp4
    02:52
  • 50 Resources to.mp4
    01:48
  • 51 Keep up with.mp4
    02:09
  • 52 Summarizing the course.mp4
    02:06
  • 53 Key learnings, best practices, and part.mp4
    02:36
  • More details


    Course Overview

    This hands-on course teaches cybersecurity professionals how to fine-tune LLMs (Mistral, Llama) for advanced threat detection, vulnerability scanning, and AI-powered security solutions using AutoTrain and AutoGen.

    What You'll Learn

    • Fine-tune open-source LLMs for cybersecurity applications
    • Perform OSINT and code vulnerability scanning with AI
    • Build LLM-powered firewalls and threat detection systems

    Who This Is For

    • Cybersecurity professionals enhancing their AI skills
    • IT specialists implementing AI security solutions
    • AI practitioners entering cybersecurity fields

    Key Benefits

    • Hands-on experience with cutting-edge LLM security tools
    • Practical skills for real-world threat detection
    • Future-proof knowledge of AI-powered cybersecurity

    Curriculum Highlights

    1. Open-Source LLMs for Security
    2. AI-Powered Vulnerability Scanning
    3. Building LLM Security Agents
    Focused display
    • language english
    • Training sessions 53
    • duration 2:52:10
    • Release Date 2025/04/19