AI Fundamentals 7 The origins and evolution of AI Key Concepts and Terminology Traditional AI (ML) vs Foundational models (Gen AI) AI vs. ML vs. Deep Learning vs. Generative AI Introduction To Generative AI Synthetic Data Computer Vision
Generative AI 13 LLMs and Foundational Models Foundation models 101 Architecture for LLM Applications (Emerging) Prompt Engineering Tokens and Optimization Retrieval Augmented Generation (RAG) Four Types Of RAG (from Microsoft) Mixture of Experts (MoE) Model Inference Small Language Models
AI Agents 7 Types of Agents Agent uses and examples AI Agents Agentic workflow Intelligent Automation with AI Agents AI agent challenges Agentic RAG
Applying AI 5 Continuum for Applied AI 11 ways to apply Gen AI AI-led automation Chatbots Microsoft 365 Co-Pilot
Technologies and Tools 6 Top 3 AI Tools by Category LLM app dev tools Current LLM Landscape ChatGPT Enterprise OpenAI Playground Vector Databases
AI Strategies 4 5-Steps to Identifying Winning AI Opportunities How To Identify & Prioritize AI Opportunities Create a compelling business case Mastering Data Management for Business: A Comprehensive Guide
Risks & Security 5 Risks of AI 4 Top AI Risks Right Now AI – Security Risk Checklist AI Security Frameworks Hallucinations and other risks
AI Safety 4 Explainable AI AI Alignment Ethical Considerations And Strategies Handling Sensitive Information with AI
AI Governance 6 AI Center of Excellence The regulatory landscape for AI Current compliance situation AI CoE checklist Data governance: ensuring data integrity and accessibility Crafting AI Policies for Transparency and Bias Mitigation
Prompt Engineering 4 Chain of Thought Prompting Effective Guide To Prompting One-Shot Prompting Self-Consistency Prompting
LLM Evaluation 3 Practical LLM Evaluation Techniques Methods and Frameworks for LLM Evaluation LLM Evaluation Explained
