
Overview
To enable non-technical teams to embed AI directly into daily business workflows, improving productivity, quality, and consistency, while establishing measurable ROI and a foundation for automation and scaling.
Skills Covered
By the end of this course, participants will be able to:
- Apply AI tools to real workplace workflows (no coding)
- Build reusable prompts, templates, and prompt libraries
- Use AI for document intelligence and research
- Perform basic data analysis and visualisation using AI-assisted tools
- Design team-based AI workflows with review and quality controls
- Implement 3–5 AI-enabled workflows with measurable ROI
Prerequisites
There are no prerequisites required to attend this course.
Target Audience
- Business Users
- Operations Teams
- Knowledge Workers
- Analysts
- Managers

Module 1: AI Practitioner Mindset: From Tools to Workflows
- AI beyond chat: embedding into work
- Productivity vs quality trade-offs
- Where AI fits in business processes
- Examples of AI-enabled workflows across departments
Outcome:
Participants think in workflows, not prompts
Module 2: AI-Driven Workflow Productivity
- AI for:
- Meeting notes and action items
- Reports and executive summaries
- Proposals and business cases
- SOPs and internal documentation
- Structuring prompts for repeatable outputs
- Human-in-the-loop best practices
Hands-On:
Create AI-assisted meeting notes and reports
Module 3: Document Intelligence with AI
- Working with PDFs and long documents
- Extracting key insights and comparisons
- Cross-document Q&A
- Policy, contract, and guideline analysis
- Using NotebookLM for document-based intelligence
Hands-On:
Q&A and summarisation over multiple documents
Module 4: Designing Reusable Prompts & Templates
- Prompt patterns for business tasks
- Creating reusable prompt templates
- Building a personal and team prompt library
- Versioning and prompt improvement
Hands-On:
Create a reusable prompt template for team use
Module 5: AI-Assisted Data Analysis & Visualisation (No Coding)
- Using Excel with Copilot:
- Natural language queries
- Formula generation
- Trend and insight detection
- Google Sheets with Gemini:
- Data exploration
- Charts and summaries
- Interpreting AI-generated insights responsibly
Hands-On:
Analyze a business dataset using AI-assisted spreadsheets
Module 6: Team-Based AI Workflows & Knowledge Sharing
- Shared knowledge bases and document repositories
- Consistency and quality control
- Review loops and approval workflows
- Avoiding “AI silos” within teams
Hands-On:
Design a shared team AI workflow
Module 7: Introductory Automation Concepts (No-Code)
- Understanding automation logic (trigger → action)
- Example flow:
- Form → Sheet → AI processing → Email → Dashboard
- Where AI fits in automation
- When to automate vs when not to
Demo:
Simple end-to-end automation workflow
Module 8: ROI Tracking, Scaling & Next Steps
- Measuring time saved and quality improvement
- Defining success metrics
- Scaling workflows across teams
Roadmap from AI Practitioner → Automation → AI Builder

Exam & Certification
This course is not associated with any Certification.
Training & Certification Guide
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