6-month-ai-secops.md

6-Month AI SecOps Roadmap

🎯 Prerequisites

Complete DevOps and DevSecOps fundamentals first.

📅 Month 1-2: AI/ML Fundamentals (Weeks 1-8)

Week 1-2: ML Basics

• Supervised vs unsupervised learning
• Training, validation, testing
• Common algorithms
• Model evaluation metrics

Week 3-4: Python for ML

• NumPy, Pandas
• Scikit-learn basics
• Data preprocessing
• Feature engineering

Week 5-6: Deep Learning Intro

• Neural network basics
• PyTorch/TensorFlow intro
• NLP fundamentals
• LLM concepts

Week 7-8: ML Infrastructure

• Model serving (TorchServe, TF Serving)
• MLflow basics
• GPU management
• Containerized ML

📅 Month 3-4: AI Security (Weeks 9-16)

Week 9-10: LLM Security

• Prompt injection attacks
• Jailbreaking techniques
• Data leakage risks
• Defense strategies

Week 11-12: Model Security

• Model poisoning
• Adversarial attacks
• Model theft protection
• Secure inference

Week 13-14: Guardrails

• Input validation
• Output filtering
• Rate limiting
• Monitoring for abuse

Week 15-16: Secure ML Pipelines

• Data validation
• Model signing
• Artifact management
• Access control

📅 Month 5-6: Mastery (Weeks 17-24)

Week 17-20: Projects

• Secure LLM chatbot
• AI security scanning tool
• ML pipeline with security

Week 21-24: Interview Prep

• AI security concepts
• Scenario practice
• Portfolio completion

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Next: See 6-Month AIOps roadmap.