The AI systems being built today have attack surfaces that most security teams have never seen. This course changes that.
In 10 weeks, you'll go from understanding AI security to actually doing it — conducting real red team engagements, building defences that hold, and producing a professional capstone report you can put straight into your portfolio.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
As AI agents take over business workflows, they become the most dangerous attack surface in your organisation. This course teaches you to find, exploit, and fix vulnerabilities in AI agent systems.
W0 — Orientation: OWASP LLM Top 10, Garak first scan, lab setup
W1 — AI Agent Attack Surfaces: Trust boundaries, STRIDE threat modelling, multi-hop attack paths
W2 — Prompt Injection: Direct and indirect injection, bypass techniques, guard model classifier, defence-in-depth
W3 — Jailbreaking: DAN, roleplay, crescendo, many-shot, Garak automated scanning, NeMo Guardrails
W4 — Tool Call Hijacking: Path traversal, SSRF, exfiltration chains, sandboxing and audit logging
W5 — RAG Poisoning: ChromaDB injection, backdoor triggers, SHA-256 integrity hashing, 4-gate ingest pipeline
W6 — PII Leakage & DPDPA: Aadhaar, PAN, IFSC detection with Presidio, DPDPA-compliant middleware
W7 — Capstone: Full mini red team engagement, professional findings report, peer presentation
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
✅ Security engineers & red teamers who want to add AI to their practice
✅ AI & ML engineers who want to build secure-by-default systems
✅ DevSecOps & platform engineers who own AI security posture
✅ Anyone building AI agents who wants to understand how they break
You need Python basics and curiosity about how things break. No prior AI security experience required.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🛠 7 portfolio deliverables — real artefacts, not just certificates
📄 Professional red team findings report (Capstone W7)
🔧 Tools you'll use in production: Garak, PyRIT, LangGraph, ChromaDB, Presidio, NeMo Guardrails, Azure Prompt Shield
⚖️ DPDPA-compliant AI architecture for Indian deployments
💼 40–60% salary premium — AI red teamers are in high demand
You can prompt ChatGPT. So can everyone else.
The engineers getting hired, promoted, and funded are building something different — production-grade multi-agent AI systems, advanced RAG pipelines that actually work, and deployed AI products with real users.
This is the Advanced AI Engineering programme that bridges that gap.
Not theory. Not toy projects. Real production systems — built, deployed, and presented on Demo Day.
🔍 M10 — Advanced RAG
GraphRAG · RAPTOR · Multi-Modal Retrieval · RAGAS Evaluation
🤖 M11 — LangGraph Agents
State Machines · Conditional Routing · Human-in-the-Loop · Checkpointing
👥 M12 — CrewAI
Role-Based Agent Crews · Sequential & Hierarchical Pipelines · Memory
📊 M13 — LLMOps
LangSmith Tracing · LLM-as-Judge Evaluation · Cost Dashboards · Prompt Versioning
🧠 M14 — Fine-Tuning
QLoRA on 7B Models · Single GPU · LoRA Adapters · vLLM Serving
🔌 M15 — MCP Servers
Model Context Protocol · Build & Publish Tools · Claude Desktop Integration
🏗️ M16 — Enterprise AI Architecture
Semantic Caching · Guardrails · Rate Limiting · Multi-Tenancy
🎙️ M17 — Voice AI
STT · TTS · Real-Time WebSocket Pipeline · Under 400ms Latency
🛡️ M18 — AI Security
Red Teaming · Prompt Injection · Presidio PII · DPDPA Compliance
🚀 M19 — Production Infrastructure
Docker · Kubernetes · HPA + KEDA Auto-Scaling · GPU Scheduling · FinOps
💡 M20 — AI Product Strategy
Product Archetypes · Pricing · Indian B2B GTM · Building in Public
🎓 M21 — Advanced Capstone — Demo Day
Production AI System · Live Deployment · RAGAS Evaluated · Portfolio Launch
A live, deployed AI system — not localhost. A real URL.
GitHub portfolio with architecture diagrams, RAGAS scores, and demo video
Measurable skills — faithfulness scores, latency benchmarks, cost per query
SkillLabz Advanced Certificate — add it to LinkedIn on Demo Day
Working software engineers (3+ years) who want to specialise in AI
Engineers who've done beginner AI courses and want the advanced track
Anyone building AI for enterprise or launching an AI product in India
Developers who want to move from AI hobbyist to Senior AI Engineer
Prerequisites: Python proficiency · Basic ML understanding
(No prior LLM experience required)
Every module is grounded in the Indian market:
DPDPA compliance (India's data privacy law)
Indian language AI — Sarvam, AI4Bharat
Indian B2B pricing and GTM strategy
Rupee-denominated cost benchmarks throughout
AI is not coming for your job. Someone using AI is.
The question is — which side do you want to be on?
Introducing the SkillLabz AI Engineering Course — your complete, hands-on journey from curious beginner to building real AI products, in just 10 modules.
No machine learning maths required. Just Python, real projects, and a certificate signed by our CEO.
🚀 What you'll build
A production-ready AI business assistant called SmartDesk — with RAG (Retrieval-Augmented Generation), a multi-tool AI agent, a live API, and your own fine-tuned model deployed on the cloud.
📚 What's inside the course
✅ 10 self-paced video modules
✅ LLMs, Prompt Engineering, FastAPI, Vector Embeddings, RAG, AI Agents & Fine-tuning
✅ 9 knowledge assessments
✅ Complete SmartDesk production codebase
✅ Completion certificate signed by Dinesh Sharma, CEO & Founder
✅ Live Q&A with a real instructor
💼 Built for
IT professionals, business owners, and fresh graduates who want to lead AI projects, automate work, and land high-paying AI engineering roles in India.
💰 Opportunity
AI engineers in India are earning ₹15–50 LPA.
97 million new AI jobs are being created.
The window is open — but it won't stay open forever.