What you'll learn:
- Understand the fundamentals of AI Guardrails and their importance in ethical AI development.
- Retrieval Augmented Generation: Learn about RAG, Vector store
- User Input Guardrails : Learn about prompt injections, user input moderations (hate, violence etc) and ways to detect user input violations
- Hallucination: Learn about Hallucination and detecting Hallucination using Open Source model from Hugging Face
- Evaluators - Faithfulness Evaluator(LLM-As-A-Judge), SAS Evaluator, Context Relevance Evaluator and RAGAS Evalauator
- Haystack Framework: Introduction to Haystack pipeline
- Guardrails on AWS Bedrock : Learn to configure, deploy and run Guardrails on AWS Bedrock
- Explore Real World Guardrails Models using Huggingface and Colab Notebooks
- Learn architecture and gain insight on open source frameworks like GuardrailsAI and NemoGuardrails with real-world AI projects.
- Learn to implement AI Guardrails and Nemo Framework in AI projects to prevent bias, ensure privacy, and enhance security.
77% of enterprises faced Generative AI breaches last year (IBM 2025). This hands-on course teaches you to deploy production guardrails against prompt injection, hallucinations, and cyber attacks using Llama Guard 3, AWS Bedrock, and CrewAI. Master open-source frameworks like GuardrailsAI, Nemo Guardrails, and Haystack to secure real AI applications.
What You'll Learn:
1. GUARDRAIL FRAMEWORKS
Nemo Guardrails: Production-grade dialog management & intent filtering
GuardrailsAI: RAIL specs, validator policies, output structuring
AWS Bedrock Guardrails: Enterprise content policy configuration
Haystack Evaluators: RAG faithfulness/SAS metrics
Llama Guard 3: Multimodal (vision+text) jailbreak detection
2. SECURITY TESTING TOOLS
Garak: Red Teaming to scan LLM vulnerability (encoding/XFilteration/profanity)
CrewAI + OWASP ZAP: Scan Web Vulnerabilities with AI-powered web penetration testing
Prompt-Guard: Real-time injection attack blocking
3. PLATFORMS & MODELS
AWS Bedrock: Cloud-based guardrail deployment
Hugging Face: Access to phi3/prompt-guard models
Phi-3.5-vision-instruct: Multimodal safety enforcement
phi3-hallucination-judge: Hallucination scoring engine
FastRAG: Secure retrieval-augmented generation pipelines
Below is the course details
1. Input Security Guardrails
Nemo Guardrails: Dialog management for intent-based filtering
Llama Guard 3: Vision-text hybrid moderation (NSFW/jailbreak detection)
Prompt-Guard: Real-time injection blocking
2. Output Validation Systems
phi3-hallucination-judge: Quantify truthfulness scores
GuardrailsAI Validators: Enforce PII/deny-topic policies
LLM-as-Judge Fallbacks: Context relevancy checks
3. Vulnerability Scanning
Garak Probes:
Encoding attacks
XFilteration exploits
Profanity detection
4. AI-Powered Cybersecurity
CrewAI Penetration testing:
Web vulnerability scanning
ZAP Proxy automation
Multi-agent threat hunting
5. Enterprise Platform Guardrails
AWS Bedrock:
Content policy configuration
Multimodal image guardrails
Nemo Production Deployment:
Intent classification workflows
Custom validator integration
6. RAG Security & Evaluation
Haystack Framework:
Pipeline construction
SAS/faithfulness metrics
GuardrailsAI RAIL Specs:
Output structure validation
On-fail remediation policies
7. Multimodal Agentic Safety
ReAct Architecture: Multi-hop reasoning
Phi-3.5-vision-instruct:
Nutritional analysis case study
Compliance checks
KEY HANDS-ON PROJECTS
Nemo Intent Firewall: Block restricted queries in production chatbots
GuardrailsAI HIPAA Enforcer: PII redaction & deny-topic policies
CrewAI Web Vulnerability Scanner: Automated XSS/SQLi detection
Multimodal Jailbreak Detector: NSFW/image attack prevention
RAG Audit Dashboard: SAS scoring for retrieval faithfulness
Who Should Enroll:
This course is ideal for AI developers, data scientists, business leaders, and enthusiasts eager to enhance their understanding of ethical AI practices quickly. Whether you aim to apply ethical considerations to current projects or seek to broaden your knowledge of AI safety measures, this course will equip you with the insights needed for responsible AI development.
Join Us:
Embrace the opportunity to shape the future of AI by embedding ethical considerations and safety measures into the fabric of AI technologies. Enroll in "AI Guardrails: Ensuring Ethical and Safe AI Deployments" and take a significant step towards responsible and safe AI deployment.
