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

1-Month Intensive — Beginner to AI-Powered Professional

Modules
8
Lessons
53
Duration
34h 50m
  1. Module

    01

    Module 1 — AI Fundamentals

    Build a strong foundation in what AI is, where it came from and how modern AI systems work.

    • Lesson 1 — Welcome to Platinum AI AcademyReading10m
    • Lesson 2 — What Is Artificial Intelligence?Reading35m
    • Lesson 3 — A Brief History of AIReading30m
    • Lesson 4 — Understanding Modern AIReading45m
    • Lesson 5 — How AI Learns and Produces AnswersReading40m
  2. Module

    02

    Module 2 — Generative AI & Large Language Models

    Understand the technology behind modern AI assistants — and why AI output is never automatically fact.

    • Lesson 6 — What Is Generative AI?Reading35m
    • Lesson 7 — Introduction to Large Language Models (LLMs)Reading45m
    • Lesson 8 — Tokens, Context Windows & AI MemoryReading35m
    • Lesson 9 — How Chatbots Generate ResponsesReading30m
    • Lesson 10 — Strengths and Limitations of LLMsReading35m
    • Lesson 11 — Hallucinations, Accuracy & AI ReliabilityReading40m
  3. Module

    03

    Module 3 — The Modern AI Toolkit

    Learn to select and use the major AI platforms: ChatGPT, Gemini, Claude and Perplexity.

    • Lesson 12 — ChatGPT: Capabilities & Practical UseReading40m
    • Lesson 13 — Google Gemini: Capabilities & Practical UseReading35m
    • Lesson 14 — Claude: Capabilities & Practical UseReading35m
    • Lesson 15 — Perplexity: AI-Powered ResearchReading35m
    • Lesson 16 — Comparing AI Models & ToolsReading40m
    • Lesson 17 — Choosing the Right AI Tool for the JobReading40m
  4. Module

    04

    Module 4 — Prompt Engineering Mastery

    Move from casual AI chatting to deliberate, structured, testable prompting.

    • Lesson 18 — What Makes a Good Prompt?Reading30m
    • Lesson 19 — The Anatomy of an Effective PromptReading40m
    • Lesson 20 — Zero-Shot & Few-Shot PromptingReading35m
    • Lesson 21 — Step-by-Step & Structured PromptingReading40m
    • Lesson 22 — Prompting for Writing & Content CreationReading35m
    • Lesson 23 — Prompting for Research & AnalysisReading40m
    • Lesson 24 — Prompting for Business & Workplace TasksReading40m
    • Lesson 25 — Improving & Testing PromptsReading40m
    • Practical Prompt ChallengeReading1h
  5. Module

    05

    Module 5 — AI for Productivity & Knowledge Work

    Use AI to save time and raise the quality of everyday professional work.

    • Lesson 26 — AI in Your Daily WorkflowReading40m
    • Lesson 27 — AI for Writing, Editing & CommunicationReading40m
    • Lesson 28 — AI for Research & Information SummarisationReading45m
    • Lesson 29 — AI for Meetings, Notes & Action ItemsReading35m
    • Lesson 30 — AI for Data Analysis & Decision SupportReading45m
    • Lesson 31 — AI for Presentations & DocumentsReading35m
    • Lesson 32 — Building Your Personal AI Productivity SystemReading45m
  6. Module

    06

    Module 6 — AI Workflows & No-Code Automation

    Connect AI to real workflows without writing code, with humans in the loop.

    • Lesson 33 — What Is an AI Workflow?Reading30m
    • Lesson 34 — From Manual Process to AI WorkflowReading40m
    • Lesson 35 — Introduction to No-Code AI AutomationReading40m
    • Lesson 36 — AI + Forms + Documents + SpreadsheetsReading40m
    • Lesson 37 — Human-in-the-Loop AutomationReading35m
    • Lesson 38 — Designing Your First AI WorkflowReading45m
    • Practical Exercise — Build an AI WorkflowReading1h
  7. Module

    07

    Module 7 — Responsible AI, Ethics & Digital Safety

    Use AI responsibly, safely, legally and professionally.

    • Lesson 39 — Responsible AI & EthicsReading40m
    • Lesson 40 — AI Bias & FairnessReading35m
    • Lesson 41 — Privacy & Personal DataReading40m
    • Lesson 42 — Confidential Information & AI ToolsReading35m
    • Lesson 43 — Copyright, Intellectual Property & AIReading35m
    • Lesson 44 — Misinformation, Deepfakes & AI ManipulationReading35m
    • Lesson 45 — Human Oversight & Responsible Decision-MakingReading35m
  8. Module

    08

    Module 8 — AI Practitioner Foundations & Capstone

    Consolidate everything and prove practical AI competency through the capstone.

    • Lesson 46 — Evaluating AI OutputsReading35m
    • Lesson 47 — Fact-Checking & AI-Assisted ResearchReading40m
    • Lesson 48 — Building Your Personal AI ToolkitReading35m
    • Lesson 49 — From AI User to AI-Powered ProfessionalReading35m
    • Lesson 50 — Capstone Project PreparationReading30m
    • Capstone Project — AI-Powered Productivity WorkflowReading2h

$99 · 2 months

Enroll in Tier 1

Tier 2

AI Professional

Tier 2 — design, automate and deploy AI-powered business solutions

Modules
10
Lessons
80
Duration
52h
  1. Module

    01

    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 CommunicationReading35m
    • Lesson 2 — Structured Prompt FrameworksReading40m
    • Lesson 3 — Chain-of-Thought PromptingReading40m
    • Lesson 4 — Multi-Step PromptingReading40m
    • Lesson 5 — Few-Shot & Zero-Shot LearningReading35m
    • Lesson 6 — Prompt ChainingReading40m
    • Lesson 7 — Prompt LibrariesReading35m
    • Lesson 8 — Practical Workshop — Advanced Prompt ChallengeReading50m
  2. Module

    02

    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 WorkflowsReading35m
    • Lesson 2 — Mapping Business ProcessesReading40m
    • Lesson 3 — Automation Design PrinciplesReading40m
    • Lesson 4 — Building Repeatable WorkflowsReading40m
    • Lesson 5 — Workflow OptimisationReading35m
    • Lesson 6 — Automation Best PracticesReading35m
    • Lesson 7 — Practical Workflow LabReading50m
    • Lesson 8 — Case Studies in Workflow AutomationReading40m
  3. Module

    03

    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 AIReading35m
    • Lesson 2 — Zapier AIReading35m
    • Lesson 3 — Make.comReading35m
    • Lesson 4 — n8nReading40m
    • Lesson 5 — Microsoft Power AutomateReading35m
    • Lesson 6 — Google Workspace AIReading35m
    • Lesson 7 — Integrating ApplicationsReading40m
    • Lesson 8 — Practical Automation ProjectReading50m
  4. Module

    04

    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?Reading35m
    • Lesson 2 — Agent ArchitectureReading40m
    • Lesson 3 — Memory SystemsReading40m
    • Lesson 4 — Tool CallingReading40m
    • Lesson 5 — Multi-Agent CollaborationReading40m
    • Lesson 6 — Agent SafetyReading40m
    • Lesson 7 — Autonomous WorkflowsReading35m
    • Lesson 8 — Build Your First AI AgentReading50m
  5. Module

    05

    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 GPTsReading35m
    • Lesson 2 — Instruction EngineeringReading40m
    • Lesson 3 — AI PersonasReading35m
    • Lesson 4 — Knowledge BasesReading40m
    • Lesson 5 — Conversation DesignReading35m
    • Lesson 6 — Testing Your AssistantReading40m
    • Lesson 7 — Publishing & DeploymentReading35m
    • Lesson 8 — Business Applications & Build ProjectReading50m
  6. Module

    06

    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 FinanceReading40m
    • Lesson 2 — AI in HRReading40m
    • Lesson 3 — AI in ProcurementReading35m
    • Lesson 4 — AI in OperationsReading35m
    • Lesson 5 — AI in Customer SupportReading40m
    • Lesson 6 — AI Decision SupportReading40m
    • Lesson 7 — AI Governance in OperationsReading40m
    • Lesson 8 — Business Case StudiesReading40m
  7. Module

    07

    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 StrategyReading35m
    • Lesson 2 — AI CopywritingReading35m
    • Lesson 3 — Social Media AutomationReading35m
    • Lesson 4 — AI Email MarketingReading35m
    • Lesson 5 — AI Lead GenerationReading40m
    • Lesson 6 — Sales AutomationReading35m
    • Lesson 7 — CRM IntegrationReading35m
    • Lesson 8 — Marketing Analytics & Campaign ProjectReading45m
  8. Module

    08

    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 TechniquesReading35m
    • Lesson 2 — Deep Research ToolsReading35m
    • Lesson 3 — Organisational Knowledge BasesReading40m
    • Lesson 4 — Fact Checking & VerificationReading35m
    • Lesson 5 — Data ExtractionReading40m
    • Lesson 6 — AI SummarisationReading35m
    • Lesson 7 — Report GenerationReading35m
    • Lesson 8 — Research AutomationReading35m
  9. Module

    09

    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 StrategyReading40m
    • Lesson 2 — Change ManagementReading40m
    • Lesson 3 — Enterprise AI GovernanceReading40m
    • Lesson 4 — AI PoliciesReading35m
    • Lesson 5 — AI SecurityReading40m
    • Lesson 6 — ComplianceReading35m
    • Lesson 7 — ROI MeasurementReading40m
    • Lesson 8 — Scaling AI Across OrganisationsReading40m
  10. Module

    10

    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 SelectionReading45m
    • Lesson 2 — Business Problem StatementReading40m
    • Lesson 3 — Workflow Diagram & AI ArchitectureReading45m
    • Lesson 4 — Prompt Library & Automation DesignReading45m
    • Lesson 5 — AI Governance ChecklistReading40m
    • Lesson 6 — ROI AnalysisReading40m
    • Lesson 7 — Reflection & Lessons LearnedReading35m
    • Lesson 8 — Capstone Submission & PresentationReading1h

$299 · 2 months

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Tier 3

AI Master Practitioner

The flagship three-month programme for AI architects, transformation leaders and executives.

Modules
10
Lessons
100
Duration
50h
  1. Module

    01

    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 MandateReading22m
    • Value Architecture and the AI PortfolioReading26m
    • Capability Mapping and Maturity AssessmentReading30m
    • Build, Buy, Partner and Platform EconomicsReading34m
    • Business Cases That Survive Finance ReviewReading38m
    • Target Operating Models for AIReading22m
    • Executive Communication and Board NarrativeReading26m
    • AI Economics: Unit Cost and Margin ControlReading30m
    • Competitive Strategy and DefensibilityReading34m
    • Module 1 Synthesis: The Strategy DossierReading38m
  2. Module

    02

    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 PatternsReading26m
    • Prompt Engineering at System ScaleReading30m
    • Structured Output and Schema EnforcementReading34m
    • Evaluation Harnesses and Golden SetsReading38m
    • Fine-Tuning, Adapters and When Not ToReading22m
    • Latency, Streaming and Perceived PerformanceReading26m
    • Reliability Patterns: Fallbacks and Circuit BreakersReading30m
    • Multimodal Systems EngineeringReading34m
    • Security Engineering for LLM ApplicationsReading38m
    • Module 2 Synthesis: Production Design ReviewReading22m
  3. Module

    03

    Retrieval, Knowledge & Context Architecture

    Design enterprise knowledge systems: ingestion, chunking, hybrid retrieval, reranking, grounding, citation integrity and freshness governance.

    • Enterprise Knowledge ArchitectureReading30m
    • Ingestion Pipelines and Document NormalisationReading34m
    • Chunking Strategies and Their Trade-offsReading38m
    • Embeddings, Vector Stores and Index DesignReading22m
    • Hybrid Retrieval and RerankingReading26m
    • Grounding, Citation Integrity and RefusalReading30m
    • Access Control and Entitlement-Aware RetrievalReading34m
    • Knowledge Freshness and Lifecycle GovernanceReading38m
    • Retrieval Evaluation and ObservabilityReading22m
    • Module 3 Synthesis: Knowledge Platform BlueprintReading26m
  4. Module

    04

    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 RiskReading34m
    • Tool Contracts and Action SafetyReading38m
    • Planning, Decomposition and ReflectionReading22m
    • Agent Memory and State ManagementReading26m
    • Multi-Agent TopologiesReading30m
    • Human-in-the-Loop and Oversight DesignReading34m
    • Agent Evaluation and Trajectory AnalysisReading38m
    • Cost, Loop and Runaway ContainmentReading22m
    • Agent Security and Adversarial RobustnessReading26m
    • Module 4 Synthesis: Agent Deployment StandardReading30m
  5. Module

    05

    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 DisciplineReading38m
    • CI/CD for Models, Prompts and DatasetsReading22m
    • Observability: Traces, Metrics and FeedbackReading26m
    • Drift, Degradation and Continuous EvaluationReading30m
    • Deployment Strategies and Safe RolloutReading34m
    • Incident Response for AI SystemsReading38m
    • Cost Engineering and Capacity PlanningReading22m
    • Reliability Engineering and SLOsReading26m
    • Platform Engineering for AI TeamsReading30m
    • Module 5 Synthesis: Operational Readiness ReviewReading34m
  6. Module

    06

    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 LandscapeReading22m
    • Model Inventory and Lifecycle ControlReading26m
    • Risk Assessment and Control DesignReading30m
    • Data Protection, Privacy and Cross-Border FlowsReading34m
    • Documentation, Transparency and Model CardsReading38m
    • Third-Party and Vendor AI RiskReading22m
    • Assurance, Audit and Evidence ManagementReading26m
    • Bias, Fairness and Disparate Impact TestingReading30m
    • Governance Operating RhythmReading34m
    • Module 6 Synthesis: Governance Framework PackReading38m
  7. Module

    07

    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 PracticeReading26m
    • Harm Taxonomies and Threat ModellingReading30m
    • Safety Layers and Content ControlsReading34m
    • Red-Teaming ProgrammesReading38m
    • Hallucination Management and TruthfulnessReading22m
    • Human Oversight, Dignity and ContestabilityReading26m
    • Accessibility, Inclusion and LocalisationReading30m
    • Safety Monitoring and Incident LearningReading34m
    • Communicating Limitations to UsersReading38m
    • Module 7 Synthesis: Responsible AI Assurance ReportReading22m
  8. Module

    08

    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 DiscoveryReading30m
    • Designing for Probabilistic SystemsReading34m
    • Metrics for AI ProductsReading38m
    • Pricing and Packaging AI CapabilitiesReading22m
    • Adoption Strategy and Behaviour ChangeReading26m
    • Workforce Transition and ReskillingReading30m
    • Stakeholder Management and Coalition BuildingReading34m
    • Benefit Realisation and Value TrackingReading38m
    • Scaling from Pilot to EnterpriseReading22m
    • Module 8 Synthesis: AI Product and Change PlanReading26m
  9. Module

    09

    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 ScaleReading34m
    • Data Contracts and OwnershipReading38m
    • Data Quality EngineeringReading22m
    • Lineage, Cataloguing and DiscoverabilityReading26m
    • Feature Stores and Reusable SignalsReading30m
    • Vector Infrastructure at Enterprise ScaleReading34m
    • Streaming, Real-Time and Event ArchitectureReading38m
    • Privacy Engineering and Synthetic DataReading22m
    • Platform Economics and ChargebackReading26m
    • Module 9 Synthesis: Data Platform RoadmapReading30m
  10. Module

    10

    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 ProgrammeReading38m
    • Leading Technical Teams and Talent StrategyReading22m
    • Culture, Literacy and Enterprise EnablementReading26m
    • Partnerships, Ecosystem and Regional ContextReading30m
    • Frontier Watch and Strategic AdaptationReading34m
    • Executive Decision-Making Under UncertaintyReading38m
    • Capstone Framing: Problem and ScopeReading22m
    • Capstone Method: Architecture and EvidenceReading26m
    • Capstone Delivery: Executive PresentationReading30m
    • Master Practitioner Synthesis and Final ExaminationReading34m

$799 · 3 months

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