Fine-Tuning LLMs for Cybersecurity: Mistral, Llama, AutoTrain, AutoGen, and LLM Agents

سرفصل های دوره

Explore the emergent field of cybersecurity enhanced by large language models (LLMs) in this detailed and interactive course. Instructor Akhil Sharma starts with the basics, including the world of open-source LLMs, their architecture and importance, and how they differ from closed-source models. Learn how to run and fine-tune models to tackle cybersecurity challenges more effectively. Gather insights for identifying new threats, generating synthetic data, performing open-source intelligence (OSINT), and scanning code vulnerabilities with hands-on examples and guided challenges. Perfect for cybersecurity professionals, IT specialists, and anyone keen on understanding how AI can bolster security protocols, this course prepares you to embrace the synergy of AI for cybersecurity, unlocking new potentials in threat detection, prevention, and response.

1 Introduction

01 Introduction to LLMs and LLM agents f

02 Prerequisites of the course

03 What can be learned in this course

04 Google Colab and other important tool

05 How to make the most of this course

2 Open-Source LLMs and Why Theyre Important

06 GenAI a

07 Importa

08 Open so

09 Assets

10 Fine-tu

11 Challen

12 Solutio

3 LLMs and Cybersecurity

13 New evolving threats, power

14 Advanced attacks by hackers

15 How cybersecurity professio

16 Synthetic data generation I

17 Synthetic data generation C

18 Challenge Identify phishing

19 Solution Fine-tune LLMs wit

4 Code Vulnerability Scanning with LLMs

20 Introduction

21 Blockchains

22 Out-of-the-b

23 Fine-tuning

24 Training the

25 Inference an

5 OSINT with LLM Agents

26 Introduction to OSINT and ho

27 Introduction to agents and a

28 Agent frameworks and Crew AI

29 Planning the agents, their t

30 Setting up the project LLMs,

31 Finishing touches and analyz

6 Web Vulnerability Scanning with LLM Agents

32 Introdu

33 Plannin

34 Getting

35 Analyzi

36 Setting

37 Kicking

7 LLM-Powered Firewall

38 Introduction to LLM-powered f

39 Planning the approach

40 Network data gathering and st

41 Data preprocessing

42 LLM setup

43 LLM fine-tuning

44 Inference output and closing

8 The Future of Cybersecurity with LLMs

45 Threats of t

46 LLM powered

47 Decentralize

48 Swarm learni

49 Predictive s

50 Resources to

51 Keep up with

9 Conclusion

52 Summarizing the course

53 Key learnings, best practices, and part

139,000 تومان

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تولید کننده: LinkedIn Learning (Lynda)