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  • Welcome to AI Training
  • Course: AI 101
    • Generative AI vs. Machine Learning AI
    • How Generative AI Works: The Basics Explained
    • How Generative AI will impact Business
    • The First Wave: Exploring AI-Powered Tools
    • The Second Wave: AI Enhancements in Business Apps
    • The Third Wave: AI Agents That Do the Work
    • AI Security 101: Best Practices & Pitfalls
    • Mastering AI Prompting: Unlocking AI’s Potential
  • Course: Building AI Agents
    • Lesson 1.1 – From Software to Agents
    • Lesson 1.2 – How AI Agents Work
    • Lesson 1.3 – Use Cases that Win
    • Lesson 2.1 – Define a Strategic Use Case
    • Lesson 2.2 – Set Clear Success Criteria
    • Lesson 2.3 – Requirements & Risk Planning
    • Lesson 3.1: What is 'AI-Ready' Data?
    • Lesson 3.2 – Data Transformation with raia Academy
    • Lesson 3.3 – Building and Optimizing the Vector Store
    • Lesson 4.1 – Integration Planning 101
    • Lesson 4.2 – Building Workflows for AI Agents
    • Lesson 4.3 – User Interface Selection for AI Agents
    • Lesson 5.1 – Building a Testing Strategy
    • Lesson 5.2 – Human Feedback with raia Copilot
    • Lesson 5.3 – Automated Testing with raia Academy Simulator
    • Lesson 6.1 – Designing a Beta Testing Program
    • Lesson 6.2 – Training your Team on AI
    • Lesson 6.3: Scaling Your AI Agent Program
    • Lesson 7.1 – Launching Safely and Strategically
    • Lesson 7.2 – Measuring Business Impact
    • Lesson 7.3 – Scaling Your Agent Ecosystem
  • Course: Agentic Design
    • What Makes an AI System an Agent?
    • Prompt Chaining
    • Routing
    • Parallelization
    • Reflection
    • Tools & Functions
    • Planning
    • Multi-Agent Collaboration
    • Memory Management
    • Learning and Adaptation
    • Model Context Protocol (MCP)
    • Goal Setting & Monitoring
    • Exception Handling & Recovery
    • Human-in-the-Loop (HITL)
    • Knowledge Retrieval (RAG)
    • Inter-Agent Communication (A2A)
    • Resource-Aware Optimization
    • Reasoning Techniques
    • Guardrails & Safety
    • Evaluation & Monitoring
    • Prioritization
    • Exploration & Discovery
    • Advanced Prompting Techniques
    • FAQ
    • Module 5: Evaluation & Testing
  • How to Train an AI Agent
    • Module 1: Foundations of Advanced Agent Training
      • Module 1: Video Overview
      • Lesson 1.1 — The Role of Instructional Prompts in Agent Autonomy
      • Lesson 1.2 — Anatomy of a High-Quality Instructional Prompt
      • Lesson 1.3 — From Prompting to Orchestration
    • Module 2: Designing Powerful Instructional Prompts
      • Module 2: Video Overview
      • Lesson 2.1 — Setting Objectives and Guardrails
      • Lesson 2.2 — Embedding Strategy, Not Just Instructions
      • Lesson 2.3 — Multi-Role & Multi-Intent Prompting
      • Lesson 2.4 — Persona, Voice & Consistency
      • Lesson 2.5 — Modular & Hierarchical Prompting
      • Lesson 2.6 — Testing & Iterating Instructional Prompts
    • Module 3: Preparing Data for the Vector Store
      • Module 3 - Video Overview
      • Lesson 3.1 — Principles of Vectorization & Embeddings
      • Lesson 3.2 — Data Hygiene & Optimization
      • Lesson 3.3 — Chunking & Segmentation Strategies
      • Lesson 3.4 — Metadata as a Compass
      • Lesson 3.5 — Cross-Source Normalization
      • Lesson 3.6 — Versioning, Expiry & Embedding Refresh Cycles
      • Best Practices - Vector Store
    • Module 4: Routing & Intent Mapping
      • Module 4 - Video Overview
      • Lesson 4.1 — What is Routing and Why It Matters
      • Lesson 4.2 — Intent Taxonomy Design
      • Lesson 4.3 — Mapping Intents to Data Sources
      • Lesson 4.4 — Conflict Resolution & Fallbacks
      • Lesson 4.5 — Confidence Thresholds & Escalation Logic
      • Lesson 4.6 — Hybrid Retrieval (Keyword + Vector)
      • Lesson 4.7 — Intent Drift Detection
    • Module 5: Evaluation & Testing
      • Module 5: Video Overview
      • Lesson 5.1 — Creating Ground Truth QA Sets
      • Lesson 5.2 — Measuring Accuracy, Consistency & Confidence
      • Lesson 5.3 — Red Teaming & Adversarial Prompt Testing
      • Lesson 5.4 — Hallucination Metrics & Reduction Strategies
      • Lesson 5.5 — A/B Testing Instructional Prompts
    • Module 6: Scalability & Maintenance
      • Module 6: Video Overview
      • Lesson 6.1 — Modular Agent Design for Scale
      • Lesson 6.2 — Observability & Logging Best Practices
      • Lesson 6.3 — Continuous Improvement Loops (Feedback → Training)
      • Lesson 6.4 — Multi-Agent Orchestration
      • Lesson 6.5 — HITL (Human-in-the-Loop) Escalation Workflows
    • Module 7: Advanced Applications
      • Lesson 7.1 — Context Window Management & Optimization
      • Lesson 7.2 — Chain-of-Thought Encouragement & Reasoning Patterns
      • Lesson 7.3 — Security & Data Sensitivity (PII, compliance)
      • Lesson 7.4 — Domain-Specific Optimization
      • Lesson 7.5 — Integrating 3rd Party Data Sources & APIs
    • Sample Prompt - Support Agent
    • Sample Prompt - Sales Agent
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  1. How to Train an AI Agent
  2. Module 3: Preparing Data for the Vector Store

Module 3 - Video Overview

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