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.
Navigate the intersection of innovation and ethics in the dynamic field of Artificial Intelligence with our intensive course, "AI Guardrails: Secure GenAIApplications" 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 GenAIGuardrails.
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 AIGuardrails.
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 LLM
Identifying 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 values
Real-World Applications: Examine case studies that underscore the consequences of neglecting AI guardrails and the steps taken to mitigate such risks
Practical Tools: Gain insights into the tools, frameworks and methodologies for assessing AI systems, identifying potential risks, and ensuring that AI operates within ethical boundaries
User Input Guardrail: Use Open Source Models from Llama 3.1 family (like Prompt-Guard and Llama Guard 3) to detect Prompt Injection and Content moderation
LLM 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 Relevancy
Guardrails on AWS Bedrock Platform: Learn how to configure, deploy and run Guardrails using AWS Bedrock
Haystack Framework: Introduction to Haystack pipeline
Evaluators:Learn to Evaluate RAG pipelines using metric driven evaluation
Course 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.
