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LinkedIn Learning

Artificial Intelligence for Cybersecurity

via LinkedIn Learning

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Overview

Syllabus

Introduction
  • Unleashing the power of AI for cybersecurity
1. Demystifying Artificial Intelligence for Cybersecurity
  • Defining artificial intelligence
  • Applying AI to cybersecurity
  • Disciplines of artificial intelligence
  • Role of machine learning in AI
  • Agentic AI vs. generative AI vs. discriminative AI
  • AI agents and cybersecurity
2. Cybersecurity Gaps and Goals
  • CIA model of security
  • Cybersecurity framework
  • Resource challenges
  • Prevention, detection, and response
  • AI agents security goals
3. Solving Cybersecurity Problems with AI
  • Intrusion detection at scale
  • Insider threat
  • Phishing and decision errors
  • Speed of incidence response
  • AI-generated threats
  • Using AI agents to solve cybersecurity challenges
4. Applying Machine Learning to Security
  • Choosing the right ML approach
  • Prediction by regression
  • Classification: Intruder or not
  • Security anomaly detection
  • GAN, BERT, GPT, and more
5. Practical Considerations, Risks, and Limitations
  • The ways AI can fail you
  • Limitations and poor design
  • Attack against your AI
  • Criminals use AI too
  • Recipe for a successful AI project
  • How to choose AI-based security products

Taught by

Sam Sehgal

Reviews

4.7 rating at LinkedIn Learning based on 1872 ratings

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