📚 AI Development Guide

Complete learning resource: 45 topics from beginner to expert

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Security-First Learning Path

Duration: 3-4 weeks (for security-focused roles)

Goal: Adopt AI while maintaining enterprise security standards.

Who Is This For?

  • Security Engineers evaluating AI tools
  • Compliance Teams ensuring regulatory adherence
  • Developers in regulated industries (finance, healthcare, government)

Security-Focused Topics

Topic 5: Risk Management
Privacy, security, bias, compliance risks
Topic 28: Security Best Practices
Secure coding with AI, threat mitigation
Topic 34: Enterprise AI Governance
Policies, compliance frameworks
Topic 44: Ethical AI Development
Responsible AI, transparency, accountability

Key Focus Areas

  • Data Privacy: Protecting sensitive information in AI interactions
  • Threat Mitigation: Prompt injection, data leakage, model poisoning
  • Compliance: GDPR, HIPAA, SOC 2, ISO 27001
  • Audit & Monitoring: Tracking AI usage and outputs

Expected Outcomes

  • ✅ Comprehensive security assessment of AI tools
  • ✅ Policy framework for secure AI usage
  • ✅ Compliance with regulatory requirements
  • ✅ Incident response plan for AI-related issues
💡 Recommended Companion Path

Combine this with the Enterprise Path for complete organizational AI adoption with security built-in.

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