Overview

Navigate the intersection of innovation and ethics in the dynamic field of Artificial Intelligence with our intensive course, "AI Guardrails: Secure GenAI Applications" This course is meticulously crafted to provide learners with a condensed, yet profound understanding of the ethical frameworks necessary to guide AI technologies safely. This course will explore different ways to achieve Guardrails against malicious human interaction with LLM. In the course we will explore various techniques - platforms(AWS Bedrock), models(prompt injection, topical moderation, hallucination) and frameworks (GuardrailsAI, Nemo, Haystack) to achieve GenAI Guardrails. We are still working on Cyber Guardrails and it is not included. The course will not cover DS concepts like fine tuning models to achieve AI Guardrails. What You'll Learn:Foundations of AI Ethics: An overview of the ethical considerations critical to AI development, including fairness, privacy, and accountability.Security: Learn to apply security using model based approach for human access to LLMIdentifying and Implementing AI Guardrails: Learn through concise lectures and interactive scenarios how to establish and enforce guardrails that prevent AI misuse and ensure its alignment with human valuesReal-World Applications: Examine case studies that underscore the consequences of neglecting AI guardrails and the steps taken to mitigate such risksPractical Tools: Gain insights into the tools, frameworks and methodologies for assessing AI systems, identifying potential risks, and ensuring that AI operates within ethical boundariesUser Input Guardrail: Use Open Source Models from Llama 3.1 family (like Prompt-Guard and Llama Guard 3) to detect Prompt Injection and Content moderationLLM Response Guardrails: Use Open Source fine tuned models like phi3-hallucination-judge and hallucination-evaluation-model focused on Hallucination detection and Answer Relevancy Prompt based Guardrail: Techniques like LLM-As-A-Judge, Context RelevancyScan LLM Vulnerabilities: Explore and do Hands On with Open Source tool Garak to find vulnerabilities on LLMAI Agents: Penetration Testing with GenAI Multi-Agent - Learn about AI Agents and do a Hand On to scan Web Vulnerabilities for Cyber Security Penetration Testing using Open Source framework, CrewAI.Multimodal Nutritional AI Agent - We will use Open Source components like Haystack, FastRag, HuggingFace with Multimodel modal Phi-3.5-vision-instruct to run multi Agentic use case. We will also cover multi agentic Tools with Multi-Hop and ReAct Prompt.Guardrails on AWS Bedrock Platform: Learn how to configure, deploy and run Guardrails using AWS BedrockHaystack Framework: Introduction to Haystack pipelineEvaluators: Learn to Evaluate RAG pipelines using metric driven evaluationCourse Highlights:Focused Curriculum: Dive into the essentials of AI ethics and guardrails, tailored for immediate application.Hands-On Learning: Participate in engaging exercises that simulate real-world challenges, designed to fit within the course's compact format.Expert Guidance: Benefit from the distilled wisdom of industry leaders and ethicists, sharing actionable strategies for ethical AI governance.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.

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