Courses
Study the Certificate in Generative AI for Business Productivity independently and earn a course completion certificate. The course also fulfils the membership learning requirement. Companies, schools and institutions can build tailored AI capability programmes on this curriculum.

Certificate course
- Course name
- Certificate in Generative AI for Business Productivity
- Scale
- 14 lessons across 5 stages; 98 learning hours
- Each lesson
- 7 learning hours per taught lesson: 2 hours of teaching, 2 of guided practice, 2 of self-study and a 1-hour assessment
- Who it is for
- Professionals with 3 to 5 years of industry experience and no coding background; focused on low-code tools
- How to study
- Public lesson notes support free self-study. Taught classes are offered through organisational programmes
- For membership
- Complete 7 required lessons (about 49 learning hours), pass the online assessment and submit a project
Course outline
The 7 lessons marked "Required" are mandatory for membership.
| Lesson | Course | For membership |
|---|---|---|
| Stage 1: Literacy and principles | ||
| Lesson 1 | Introduction to AI and Generative AIUnderstand AI developments and the enterprise application landscape. | Required |
| Lesson 2 | LLM Principles and Core TermsUnderstand how large models work and their limitations. | Required |
| Stage 2: Core skills | ||
| Lesson 3 | Prompt Engineering PracticeLearn prompt design methods for consistent, high-quality outputs. | Required |
| Lesson 4 | AI Tools and Low-Code PlatformsPractise with chat, image and video tools, including Dify and Coze. | |
| Lesson 5 | AI for Office ProductivityUse AI to improve documents, spreadsheets, emails, and meeting notes. | |
| Lesson 6 | Multimodal Content CreationCreate and combine images, video, audio and presentations. | |
| Stage 3: Advanced development | ||
| Lesson 7 | AI Knowledge Bases and RAGBuild a knowledge base that answers questions with traceable sources. | Required |
| Lesson 8 | AI Agent FundamentalsUnderstand AI agent components and build a task-focused agent. | Required |
| Lesson 9 | Advanced AI Agent DesignDesign multi-tool, multi-agent collaboration and automation. | |
| Stage 4: Quality and adoption | ||
| Lesson 10 | AI Output Evaluation and Quality ControlIdentify hallucinations, fact-check outputs, and validate results. | Required |
| Lesson 11 | AI Application DeliveryUse low-code tools to deliver an end-to-end business application. | |
| Lesson 12 | Data Privacy, Security, and ComplianceIdentify data risks and apply organisational security and compliance practices. | Required |
| Stage 5: Industry applications and project | ||
| Lesson 13 | Industry AI Application WorkshopAnalyse industry cases and apply lessons to new use cases. | |
| Lesson 14 | Capstone Project and ShowcaseDeliver and present a complete AI application or plan using the course skills. | |
Assessment and certification
Online assessment
Up to 40 questions; pass mark 80; two retakes.
Project assignment
Submit a skill, architecture proposal or basic web application.
Taking the assessment
After initial screening, membership applicants take the assessment and submit their project in the member centre. Study may begin alongside the application. Certificate-only learners can request assessment at ken@aaaec.org; organisational learners follow their programme's arrangements.
Course completion certificate
Successful learners receive a numbered chapter-issued course completion certificate. It confirms completion of the specified lessons, practical tasks and assessment. It is not a professional licence, occupational qualification or third-party employment endorsement.
AI programmes for organisations
Tailored courses, workshops and implementation support for businesses, schools and institutions, built on the certificate curriculum and adapted to your industry, audience and goals.
The project team will email you within 3 working days to arrange a 30-minute consultation on your needs and programme. Fees are quoted with the proposal.
Programme principles
Who it serves
AI literacy, responsible use and practical adoption for businesses, schools, industry associations and public institutions.
Formats
Public classes, co-designed institutional sessions, cost-sharing workshops and project-based guidance build shared understanding and practical skills.
Use of resources
Resources support curriculum development, speaker coordination, materials, venues, operations and certificate administration.
Governance
The chapter manages delivery. Any surplus supports public education, community activities and shared knowledge.
Learning records
Certificates record completed lessons, practical tasks and assessments, supporting institutional learning records and continued development.
Build a programme
Select an industry, audience and goal to explore a tailored plan.
General organisation: AI capability programme
Deliverables
- Course completion certificate
- AI opportunity list
- AI use-case sketch for your role
- AI capability boundary checklist
- Role prompt templates
- Prompt quality checklist
Core capabilities
Core content covers lessons 1 to 12 of the certificate course. See the course outline.
Common use cases
Internal Knowledge Search
Enable natural-language search across policies, SOPs, product information and project knowledge.
Report and Proposal Generation
Create reports, proposals, project reviews and client communications.
SOP Automation
Convert repetitive tasks into verifiable, traceable and automated workflows.
Finance and Admin Workflow Support
Support expenses, procurement, contract routing and internal notices.
Customer Service Knowledge Assistant
Produce customer-support answers from product information, service policies and FAQs.
General organisation: industry modules
Industry-specific courses
Organisation AI Application Workshop
Half day
Identify practical AI uses in cross-functional processes, knowledge resources, productivity and role-specific tasks.
AI Opportunities in Organisational Processes
Half day
Prioritise AI use cases by mapping frequent, time-intensive and high-risk cross-departmental processes.
Cross-functional Agent Workflow Design
Half day
Design controlled, multi-step AI agents for approvals, support, operations and internal services.
Organisational Knowledge Base Governance and Q&A
Half day
Create a maintainable organisational knowledge base from policies, processes, product information and project experience.
Organisational AI Policy and Adoption
2h
Define tool-use limits, approvals, internal champion roles and continuous learning processes.
Organisation AI Application Capstone
Project-based
Apply core AI capabilities to organisation use cases and present a plan, SOP or prototype.
Industry use cases
Department AI Assistant
Build a controlled internal assistant using departmental materials, SOPs and FAQs.
Policy Q&A and Employee Self-service
Help staff find HR, administration, finance and IT policies.
Scenario Adoption Support Plan
- Format
- 1-3 day scenario workshop + 2-week guided practice
- Schedule
- Built around 2-3 real business workflows
- Outcome
- Deliver scenario maps, process SOPs, AI prototypes, and evaluation criteria
Delivery process
- 01Output
Use-case discovery and prioritisation
Select real business workflows and assess value, difficulty, and risk.
Scenario opportunity list - 02Output
Process mapping and SOP design
Define inputs, outputs, owners, review points, and exception handling.
Process SOP - 03Output
Prototype building and human review
Build a demonstrable prototype with prompts, knowledge bases or AI agents.
AI application prototype - 04Output
Pilot guidance and evaluation
Guide teams through real-task pilots and record issues and improvements.
Pilot evaluation record - 05Output
Project review and wider adoption
Capture reusable materials for broader team adoption.
Retrospective materials and adoption recommendations