Technical
10 Modules
Enrolling Now
Applied Agentic AI for Digital Transformation (Under Development)
A technical course for building grounded, tool-using, stateful, observable, and production-ready AI systems.
Who This Course Is For
Engineers and technical builders implementing AI systems in real environments.
What You Will Learn
- check_circle Build practical capability in Physics of Agentic AI
- check_circle Build practical capability in The Unified Data Brain
- check_circle Build practical capability in RAG Systems & Hybrid Retrieval
- check_circle Build practical capability in GraphRAG & Multi-Hop Reasoning
- check_circle Build practical capability in Web Data, Open Data & Social Media Ingestion
engineering
$599.00
Full Access
One-time payment · Lifetime access
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This course includes
- 10 structured learning modules
- 56 lessons
- 10 module quizzes
- Applied exercises and labs
- Progress tracking dashboard
Course Curriculum
10 modules designed as a logical progression for applied outcomes.
PostgreSQL as the Agentic Backbone
Vector Embeddings & HNSW Indexes
Hybrid Search: BM25 + Semantic Combined
JSONB State & Text-to-SQL with Claude
Module Summary
Module LAB Exercise
The RAG Pipeline Architecture
Chunking Strategies & Document Processing
Reranking & RAGAS Evaluation
The Complete Knowledge Assistant
Module Summary
Module LAB Exercise
The Limits of Vector Search — The Dot-Connecting Problem
Graph Fundamentals & Apache AGE Setup
Hybrid GraphRAG — Vector + Graph Traversal Combined
The Dot-Connector — End-to-End Multi-Hop System
Module Summary
Module LAB Exercise
Government Open Data APIs & Responsible Web Scraping
Social Media APIs, RSS Feeds & Real-Time Data
Ethics, Legal Compliance & Data Quality Controls
The Full Ingestion Pipeline: Fetch → Clean → Embed → Store
Module Summary
Module LAB Exercise
Function Calling, Tool Schemas & the ReAct Pattern
When Multi-Agent? Topologies & the Org Chart Approach
The Supervisor Agent — Decompose, Delegate, Validate
Specialist Roles — Analyst, Librarian, Monitor & Strategist
Module Summary
Module LAB Exercise
The Four Memory Types — Episodic, Semantic, Procedural & Structural
The Scribe Agent — Session Summarisation & the Episodic Journal
Semantic Memory — Persisting Approved Business Rules
Cross-Session Resume, Context Builder & GDPR Controls
Module Summary
Module LAB Exercise
The Trust Problem — Why Fluency Isn't Enough
The Guardian — PII Masking, DLP & Policy Gates
The Validator Agent — Logic, Math & Hallucination Checks
Human-in-the-Loop, RBAC & the Complete Trust Architecture
Module Summary
The Observability Gap — Tracing, Logging & Metrics for Agentic Systems
Evaluation at Scale — Extending RAGAS & LLM-as-Judge Pipelines
Cost & Latency Engineering — Token Budgets, Caching & Model Selection
Prompt Versioning, Regression Guards & the LLMOps Pipeline
Module Summary
The Feedback Loop — Capturing Implicit and Explicit Production Signals
The Proposal Generator — Drafting System Improvements from Failure Patterns
The Promotion Pipeline — Test, Approve, Deploy, Monitor
All Five Pillars: Complete Integration & the Capstone Brief
Module Summary
Your Instructor
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DENAgenticAI
AI Strategy & Professional Education
Developed by professionals with deep experience in AI strategy, Agentic AI, data engineering, and enterprise deployment. The curriculum bridges AI hype and real organizational impact.
Ready to Lead AI with Confidence?
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