Curriculum Summary
Every module. Every lesson. A transparent look at the full arc of study across all three tiers — from applied foundations to master-practitioner capstones.
Tier 1 · AI Foundations Tier 2 · AI Professional Tier 3 · AI Master Practitioner Tier 1
AI Foundations 1 Month Intensive
Modules 3
Lessons 10
Duration 7h 40m Module 1 — AI Fundamentals Build a rock-solid mental model of AI: what it is, how it evolved, and the modern landscape of narrow, generative, multimodal, and agentic systems.
Lesson 1 — Welcome to Platinum AI Academy Reading 10m Lesson 2 — What is Artificial Intelligence? Reading 35m Lesson 3 — A Brief History of Artificial Intelligence Reading 30m Lesson 4 — Understanding Modern AI Reading 45m Module 2 — Working with Large Language Models Go under the hood of LLMs, master prompt engineering fundamentals, and learn to pick the right model for the job.
Lesson 5 — Introduction to Large Language Models Reading 45m Lesson 6 — Prompt Engineering Foundations Reading 1h Lesson 7 — Choosing the Right AI Model Reading 40m Module 3 — AI for Productivity Apply AI to real workflows, adopt responsible-use habits, and complete a capstone that solves a real personal or workplace problem.
Lesson 8 — AI in Your Daily Workflow Reading 1h Lesson 9 — Responsible AI & Ethics Reading 45m Lesson 10 — Capstone Practice Project Reading 1h 30m Module 1 — Advanced Prompt Engineering Move from ad-hoc prompting to reliable, reusable prompt systems: frameworks, reasoning control, chaining and team prompt libraries.
Lesson 1 — The Psychology of AI Communication Reading 35m Lesson 2 — Structured Prompt Frameworks Reading 40m Lesson 3 — Chain-of-Thought Prompting Reading 40m Lesson 4 — Multi-Step Prompting Reading 40m Lesson 5 — Few-Shot & Zero-Shot Learning Reading 35m Lesson 6 — Prompt Chaining Reading 40m Lesson 7 — Prompt Libraries Reading 35m Lesson 8 — Practical Workshop — Advanced Prompt Challenge Reading 50m Module 2 — AI Workflow Automation Map real business processes, design AI workflows around them, and optimise for reliability, cost and human oversight.
Lesson 1 — Understanding AI Workflows Reading 35m Lesson 2 — Mapping Business Processes Reading 40m Lesson 3 — Automation Design Principles Reading 40m Lesson 4 — Building Repeatable Workflows Reading 40m Lesson 5 — Workflow Optimisation Reading 35m Lesson 6 — Automation Best Practices Reading 35m Lesson 7 — Practical Workflow Lab Reading 50m Lesson 8 — Case Studies in Workflow Automation Reading 40m Module 3 — No-Code AI Automation Build working automations across Zapier, Make.com, n8n, Power Automate and Google Workspace without writing code.
Lesson 1 — Introduction to No-Code AI Reading 35m Lesson 2 — Zapier AI Reading 35m Lesson 3 — Make.com Reading 35m Lesson 4 — n8n Reading 40m Lesson 5 — Microsoft Power Automate Reading 35m Lesson 6 — Google Workspace AI Reading 35m Lesson 7 — Integrating Applications Reading 40m Lesson 8 — Practical Automation Project Reading 50m Module 4 — AI Agents & Multi-Agent Systems Understand agent architecture, memory, tool calling and safety — then build your first working agent.
Lesson 1 — What are AI Agents? Reading 35m Lesson 2 — Agent Architecture Reading 40m Lesson 3 — Memory Systems Reading 40m Lesson 4 — Tool Calling Reading 40m Lesson 5 — Multi-Agent Collaboration Reading 40m Lesson 6 — Agent Safety Reading 40m Lesson 7 — Autonomous Workflows Reading 35m Lesson 8 — Build Your First AI Agent Reading 50m Module 5 — Custom GPTs & AI Assistants Design, instruct, test and publish custom AI assistants with knowledge bases and defined personas for real business use.
Lesson 1 — Designing Custom GPTs Reading 35m Lesson 2 — Instruction Engineering Reading 40m Lesson 3 — AI Personas Reading 35m Lesson 4 — Knowledge Bases Reading 40m Lesson 5 — Conversation Design Reading 35m Lesson 6 — Testing Your Assistant Reading 40m Lesson 7 — Publishing & Deployment Reading 35m Lesson 8 — Business Applications & Build Project Reading 50m Module 6 — AI for Business Operations Apply AI across finance, HR, procurement, operations, support and decision-making — with governance built in.
Lesson 1 — AI in Finance Reading 40m Lesson 2 — AI in HR Reading 40m Lesson 3 — AI in Procurement Reading 35m Lesson 4 — AI in Operations Reading 35m Lesson 5 — AI in Customer Support Reading 40m Lesson 6 — AI Decision Support Reading 40m Lesson 7 — AI Governance in Operations Reading 40m Lesson 8 — Business Case Studies Reading 40m Module 7 — AI for Marketing & Sales Use AI across the revenue funnel: strategy, copy, social, email, lead generation, sales automation, CRM and analytics.
Lesson 1 — AI Marketing Strategy Reading 35m Lesson 2 — AI Copywriting Reading 35m Lesson 3 — Social Media Automation Reading 35m Lesson 4 — AI Email Marketing Reading 35m Lesson 5 — AI Lead Generation Reading 40m Lesson 6 — Sales Automation Reading 35m Lesson 7 — CRM Integration Reading 35m Lesson 8 — Marketing Analytics & Campaign Project Reading 45m Module 8 — AI Research & Knowledge Management Run rigorous AI-assisted research, verify it, and turn organisational knowledge into a maintained, retrievable asset.
Lesson 1 — AI Research Techniques Reading 35m Lesson 2 — Deep Research Tools Reading 35m Lesson 3 — Organisational Knowledge Bases Reading 40m Lesson 4 — Fact Checking & Verification Reading 35m Lesson 5 — Data Extraction Reading 40m Lesson 6 — AI Summarisation Reading 35m Lesson 7 — Report Generation Reading 35m Lesson 8 — Research Automation Reading 35m Module 9 — AI Adoption & Enterprise Integration Take AI from pilots to organisation-wide capability: strategy, change management, governance, security, compliance, ROI and scale.
Lesson 1 — AI Adoption Strategy Reading 40m Lesson 2 — Change Management Reading 40m Lesson 3 — Enterprise AI Governance Reading 40m Lesson 4 — AI Policies Reading 35m Lesson 5 — AI Security Reading 40m Lesson 6 — Compliance Reading 35m Lesson 7 — ROI Measurement Reading 40m Lesson 8 — Scaling AI Across Organisations Reading 40m Module 10 — Enterprise AI Capstone Project Design, build and present a complete AI-powered business solution, assessed against the professional capstone rubric.
Lesson 1 — Capstone Brief & Project Selection Reading 45m Lesson 2 — Business Problem Statement Reading 40m Lesson 3 — Workflow Diagram & AI Architecture Reading 45m Lesson 4 — Prompt Library & Automation Design Reading 45m Lesson 5 — AI Governance Checklist Reading 40m Lesson 6 — ROI Analysis Reading 40m Lesson 7 — Reflection & Lessons Learned Reading 35m Lesson 8 — Capstone Submission & Presentation Reading 1h Enterprise AI Strategy & Value Architecture Translate executive ambition into a defensible AI portfolio: value modelling, capability mapping, build-vs-buy economics, and board-level narrative.
The Master Practitioner Mandate Reading 22m Value Architecture and the AI Portfolio Reading 26m Capability Mapping and Maturity Assessment Reading 30m Build, Buy, Partner and Platform Economics Reading 34m Business Cases That Survive Finance Review Reading 38m Target Operating Models for AI Reading 22m Executive Communication and Board Narrative Reading 26m AI Economics: Unit Cost and Margin Control Reading 30m Competitive Strategy and Defensibility Reading 34m Module 1 Synthesis: The Strategy Dossier Reading 38m Advanced LLM Systems Engineering Engineer reliable large-language-model systems: architecture patterns, structured outputs, evaluation harnesses, fine-tuning economics and latency design.
LLM System Architecture Patterns Reading 26m Prompt Engineering at System Scale Reading 30m Structured Output and Schema Enforcement Reading 34m Evaluation Harnesses and Golden Sets Reading 38m Fine-Tuning, Adapters and When Not To Reading 22m Latency, Streaming and Perceived Performance Reading 26m Reliability Patterns: Fallbacks and Circuit Breakers Reading 30m Multimodal Systems Engineering Reading 34m Security Engineering for LLM Applications Reading 38m Module 2 Synthesis: Production Design Review Reading 22m Retrieval, Knowledge & Context Architecture Design enterprise knowledge systems: ingestion, chunking, hybrid retrieval, reranking, grounding, citation integrity and freshness governance.
Enterprise Knowledge Architecture Reading 30m Ingestion Pipelines and Document Normalisation Reading 34m Chunking Strategies and Their Trade-offs Reading 38m Embeddings, Vector Stores and Index Design Reading 22m Hybrid Retrieval and Reranking Reading 26m Grounding, Citation Integrity and Refusal Reading 30m Access Control and Entitlement-Aware Retrieval Reading 34m Knowledge Freshness and Lifecycle Governance Reading 38m Retrieval Evaluation and Observability Reading 22m Module 3 Synthesis: Knowledge Platform Blueprint Reading 26m Autonomous Agents & Multi-Agent Orchestration Design, constrain and evaluate agentic systems: tool contracts, planning, memory, multi-agent topologies, human oversight and failure containment.
Agentic Systems: Capability and Risk Reading 34m Tool Contracts and Action Safety Reading 38m Planning, Decomposition and Reflection Reading 22m Agent Memory and State Management Reading 26m Multi-Agent Topologies Reading 30m Human-in-the-Loop and Oversight Design Reading 34m Agent Evaluation and Trajectory Analysis Reading 38m Cost, Loop and Runaway Containment Reading 22m Agent Security and Adversarial Robustness Reading 26m Module 4 Synthesis: Agent Deployment Standard Reading 30m MLOps, LLMOps & Production Reliability Operate AI in production: CI/CD for models and prompts, observability, drift, incident response, cost control and reliability engineering.
From Prototype to Production Discipline Reading 38m CI/CD for Models, Prompts and Datasets Reading 22m Observability: Traces, Metrics and Feedback Reading 26m Drift, Degradation and Continuous Evaluation Reading 30m Deployment Strategies and Safe Rollout Reading 34m Incident Response for AI Systems Reading 38m Cost Engineering and Capacity Planning Reading 22m Reliability Engineering and SLOs Reading 26m Platform Engineering for AI Teams Reading 30m Module 5 Synthesis: Operational Readiness Review Reading 34m AI Governance, Risk & Regulatory Compliance Build governance that regulators and boards accept: risk taxonomies, model inventories, EU AI Act and data-protection alignment, assurance and audit evidence.
The AI Governance Landscape Reading 22m Model Inventory and Lifecycle Control Reading 26m Risk Assessment and Control Design Reading 30m Data Protection, Privacy and Cross-Border Flows Reading 34m Documentation, Transparency and Model Cards Reading 38m Third-Party and Vendor AI Risk Reading 22m Assurance, Audit and Evidence Management Reading 26m Bias, Fairness and Disparate Impact Testing Reading 30m Governance Operating Rhythm Reading 34m Module 6 Synthesis: Governance Framework Pack Reading 38m Responsible AI, Safety & Red-Teaming Operationalise responsible AI: harm taxonomies, safety layers, red-teaming programmes, content controls, human dignity and incident learning.
From Principles to Practice Reading 26m Harm Taxonomies and Threat Modelling Reading 30m Safety Layers and Content Controls Reading 34m Red-Teaming Programmes Reading 38m Hallucination Management and Truthfulness Reading 22m Human Oversight, Dignity and Contestability Reading 26m Accessibility, Inclusion and Localisation Reading 30m Safety Monitoring and Incident Learning Reading 34m Communicating Limitations to Users Reading 38m Module 7 Synthesis: Responsible AI Assurance Report Reading 22m AI Product Leadership & Change Management Lead AI products and the human change around them: discovery, UX for probabilistic systems, adoption, workforce transition and benefit realisation.
AI Product Discovery Reading 30m Designing for Probabilistic Systems Reading 34m Metrics for AI Products Reading 38m Pricing and Packaging AI Capabilities Reading 22m Adoption Strategy and Behaviour Change Reading 26m Workforce Transition and Reskilling Reading 30m Stakeholder Management and Coalition Building Reading 34m Benefit Realisation and Value Tracking Reading 38m Scaling from Pilot to Enterprise Reading 22m Module 8 Synthesis: AI Product and Change Plan Reading 26m Advanced Data Architecture & Platform Economics Engineer the data foundation AI depends on: contracts, quality, lineage, feature and vector infrastructure, streaming, and platform cost design.
Data Foundations for AI at Scale Reading 34m Data Contracts and Ownership Reading 38m Data Quality Engineering Reading 22m Lineage, Cataloguing and Discoverability Reading 26m Feature Stores and Reusable Signals Reading 30m Vector Infrastructure at Enterprise Scale Reading 34m Streaming, Real-Time and Event Architecture Reading 38m Privacy Engineering and Synthetic Data Reading 22m Platform Economics and Chargeback Reading 26m Module 9 Synthesis: Data Platform Roadmap Reading 30m AI Transformation, Leadership & Capstone Readiness Lead enterprise-wide AI transformation and prepare the executive capstone: operating design, culture, ecosystem, and the final master examination.
Designing an AI Transformation Programme Reading 38m Leading Technical Teams and Talent Strategy Reading 22m Culture, Literacy and Enterprise Enablement Reading 26m Partnerships, Ecosystem and Regional Context Reading 30m Frontier Watch and Strategic Adaptation Reading 34m Executive Decision-Making Under Uncertainty Reading 38m Capstone Framing: Problem and Scope Reading 22m Capstone Method: Architecture and Evidence Reading 26m Capstone Delivery: Executive Presentation Reading 30m Master Practitioner Synthesis and Final Examination Reading 34m