About this course
This course goes beyond basic AI prompting and focuses on practical workplace and business use. Learners understand how modern AI works, how to write effective prompts and how to verify results, protect sensitive information and use AI responsibly. The course applies AI to documents, presentations, Excel and data analysis, marketing, sales and CRM, customer service, operations, projects, finance, HR, management research and decision support. Learners also explore no-code automation, AI assistants and agent-style workflows. The final capstone asks learners to identify a real business process, redesign it with appropriate AI and automation, measure expected value and present an improvement plan.
What you will learn
- Explain key AI concepts, strengths, limitations and risks. - Write clearer prompts and improve results through iterative prompting. - Verify AI outputs and use sensitive information more responsibly. - Apply AI to writing, documents, presentations, spreadsheets and data analysis. - Use AI to support marketing, sales, customer service and business operations. - Apply AI appropriately in finance, HR, management, research and planning. - Map repetitive processes and design simple no-code automations. - Understand AI assistants, agents, human approval and workflow controls. - Design a practical AI and automation business-improvement solution.
Course contents
Section 1
Module 1: AI Foundations for Work & Business
- Lesson 1.1: What Artificial Intelligence Is - and What It Is Notlesson
- Lesson 1.2: Generative AI, Large Language Models & Modern AI Assistantslesson
- Lesson 1.3: AI Capabilities: Text, Images, Audio, Data, Search & Reasoninglesson
- Lesson 1.4: How AI Is Used Across Marketing, Sales, Service, Finance, HR & Operationslesson
- Lesson 1.5: Strengths, Limitations & Why AI Can Be Wronglesson
- Lesson 1.6: Choosing the Right AI Tool for the Tasklesson
- Lesson 1.7: Human Judgment, Review & Accountability in AI-Assisted Worklesson
Section 2
Module 2: Prompting & Working Effectively with AI
- Lesson 2.1: Anatomy of a Good Prompt: Goal, Context, Task & Outputlesson
- Lesson 2.2: Giving Constraints, Examples, Tone, Audience & Formatting Instructionslesson
- Lesson 2.3: Breaking Large Problems into Smaller AI-Assisted Stepslesson
- Lesson 2.4: Iterative Prompting: Ask, Review, Improve & Refinelesson
- Lesson 2.5: Using Roles, Scenarios & Perspectives to Improve Resultslesson
- Lesson 2.6: Asking AI to Critique, Compare & Improve Its Own Outputlesson
- Lesson 2.7: Reusable Prompt Templates for Common Workplace Taskslesson
- Lesson 2.8: Working with Files, Images, Tables & Structured Informationlesson
Section 3
Module 3: Safe, Responsible & Reliable AI Use
- Lesson 3.1: Hallucinations, Errors & Why Verification Matterslesson
- Lesson 3.2: Fact-Checking AI Responses & Verifying Sourceslesson
- Lesson 3.3: Privacy, Confidential Information & Sensitive Business Datalesson
- Lesson 3.4: Bias, Fairness & Responsible Decision Supportlesson
- Lesson 3.5: Copyright, Attribution & Responsible Content Uselesson
- Lesson 3.6: Deepfakes, Synthetic Content & Authenticity Riskslesson
- Lesson 3.7: When Not to Use AI and When Human Expertise Is Requiredlesson
- Lesson 3.8: Creating Practical AI Use Guidelines for a Team or Organizationlesson
Section 4
Module 4: AI for Writing, Documents, Presentations & Communication
- Lesson 4.1: Drafting and Improving Emails, Letters & Messageslesson
- Lesson 4.2: Rewriting for Tone, Clarity, Length & Audiencelesson
- Lesson 4.3: Summarizing Long Documents and Extracting Key Informationlesson
- Lesson 4.4: Creating Reports, Proposals, SOPs & Structured Documentslesson
- Lesson 4.5: Translation, Language Support & Multilingual Workflowslesson
- Lesson 4.6: Meeting Agendas, Minutes, Action Items & Follow-Uplesson
- Lesson 4.7: Turning Documents and Ideas into Presentation Outlineslesson
- Lesson 4.8: Improving Slide Messaging, Speaker Notes & Talking Pointslesson
- Lesson 4.9: Quality Control: Editing AI-Generated Content Before Uselesson
Section 5
Module 5: AI for Excel, Data & Business Analysis
- Lesson 5.1: Asking AI to Explain Data, Tables & Spreadsheet Problemslesson
- Lesson 5.2: Generating, Explaining & Debugging Excel Formulas with AIlesson
- Lesson 5.3: Cleaning, Categorizing & Structuring Business Datalesson
- Lesson 5.4: Identifying Trends, Patterns, Exceptions & Key Insightslesson
- Lesson 5.5: Creating Chart, Pivot & Dashboard Recommendationslesson
- Lesson 5.6: Turning Data into Plain-Language Management Summarieslesson
- Lesson 5.7: Scenario Analysis, Forecasting Support & What-If Questionslesson
- Lesson 5.8: Verifying AI Analysis Against the Original Datalesson
Section 6
Module 6: AI for Marketing & Content Strategy
- Lesson 6.1: Using AI for Market, Competitor & Customer Researchlesson
- Lesson 6.2: Developing Customer Personas, Segments & Audience Profileslesson
- Lesson 6.3: Generating Campaign Ideas, Themes & Marketing Planslesson
- Lesson 6.4: Writing Social Media Posts, Captions & Content Calendarslesson
- Lesson 6.5: Creating Advertising Copy, Promotional Messages & Calls-to-Actionlesson
- Lesson 6.6: AI for Email Marketing, Newsletters & Customer Campaignslesson
- Lesson 6.7: SEO, Keyword Ideas & Website Content Assistancelesson
- Lesson 6.8: Repurposing One Idea Across Multiple Channels and Formatslesson
- Lesson 6.9: Analyzing Marketing Performance & Generating Improvement Ideaslesson
Section 7
Module 7: AI for Sales, CRM & Customer Growth
- Lesson 7.1: Researching Prospects, Accounts & Customer Needslesson
- Lesson 7.2: AI-Assisted Lead Qualification & Prioritizationlesson
- Lesson 7.3: Creating Personalized Sales Outreach & Follow-Up Messageslesson
- Lesson 7.4: Preparing Sales Pitches, Quotations & Proposal Draftslesson
- Lesson 7.5: Preparing Responses to Questions, Objections & Competitor Comparisonslesson
- Lesson 7.6: Summarizing Sales Meetings, Calls & Next Actionslesson
- Lesson 7.7: Improving CRM Notes, Opportunity Management & Follow-Up Disciplinelesson
- Lesson 7.8: Upselling, Cross-Selling, Retention & Sales Forecast Supportlesson
Section 8
Module 8: AI for Customer Service & Customer Experience
- Lesson 8.1: AI-Assisted Customer Support & Response Draftinglesson
- Lesson 8.2: Building FAQs, Help Articles & Knowledge Baseslesson
- Lesson 8.3: Understanding Chatbots & AI Customer Assistantslesson
- Lesson 8.4: Classifying, Summarizing & Routing Customer Requestslesson
- Lesson 8.5: Complaint Analysis, De-Escalation Support & Response Improvementlesson
- Lesson 8.6: Customer Feedback, Reviews & Sentiment Analysislesson
- Lesson 8.7: Identifying Repeated Customer Problems & Service Improvement Opportunitieslesson
- Lesson 8.8: Human Escalation, Quality Control & When AI Should Stoplesson
Section 9
Module 9: AI for Business Operations, Projects & Administration
- Lesson 9.1: Identifying Repetitive Work and High-Value AI Opportunitieslesson
- Lesson 9.2: Creating SOPs, Checklists, Policies & Work Instructionslesson
- Lesson 9.3: AI for Project Planning, Work Breakdown & Task Assignmentlesson
- Lesson 9.4: Creating Timelines, Milestones, Risk Lists & Status Updateslesson
- Lesson 9.5: Meeting Preparation, Minutes, Action Tracking & Follow-Uplesson
- Lesson 9.6: Procurement Research, Vendor Comparison & Evaluation Supportlesson
- Lesson 9.7: Inventory, Operations & Service Data Analysislesson
- Lesson 9.8: Identifying Bottlenecks, Delays, Waste & Process Problemslesson
- Lesson 9.9: Using AI for Continuous Process Improvementlesson
Section 10
Module 10: AI for Finance, HR & Management Support
- Lesson 10.1: AI for Budget Review, Expense Categorization & Variance Explanationslesson
- Lesson 10.2: Cash-Flow, Financial Report & Scenario Analysis Supportlesson
- Lesson 10.3: Drafting Job Descriptions & Recruitment Materialslesson
- Lesson 10.4: Interview Question Preparation & Candidate Review Supportlesson
- Lesson 10.5: Employee Onboarding, Training Plans & Internal Guidancelesson
- Lesson 10.6: Performance Review Drafting & Manager Communication Supportlesson
- Lesson 10.7: KPI Interpretation, Management Summaries & Executive Briefingslesson
- Lesson 10.8: Comparing Business Scenarios & Preparing Decision Optionslesson
- Lesson 10.9: Human Oversight in Financial, HR & Other High-Stakes Decisionslesson
Section 11
Module 11: AI for Research, Strategy & Decision Support
- Lesson 11.1: Asking Better Research Questions & Defining Evidence Needslesson
- Lesson 11.2: Search-Assisted AI vs. Model-Only Answerslesson
- Lesson 11.3: Market, Industry & Competitor Research with AIlesson
- Lesson 11.4: Comparing Multiple Sources & Identifying Disagreementslesson
- Lesson 11.5: SWOT, Scenario & Business-Opportunity Analysislesson
- Lesson 11.6: Extracting Information from Reports, PDFs, Tables & Policieslesson
- Lesson 11.7: Preparing Briefing Notes, Options & Decision Memoslesson
- Lesson 11.8: Citing Sources, Documenting Assumptions & Keeping Evidence Traceablelesson
Section 12
Module 12: Automation, AI Agents & Business Workflows
- Lesson 12.1: What Business Process Automation Is - Triggers, Actions, Conditions & Datalesson
- Lesson 12.2: Mapping a Manual Process Before Automating Itlesson
- Lesson 12.3: No-Code Automation Platforms & Integration Conceptslesson
- Lesson 12.4: Automating Forms, Email, Files & Spreadsheet Workflowslesson
- Lesson 12.5: Notifications, Approvals, Scheduling & Recurring Taskslesson
- Lesson 12.6: CRM, Customer Follow-Up & Marketing Automation Exampleslesson
- Lesson 12.7: AI Assistants vs. Automations vs. AI Agentslesson
- Lesson 12.8: Tools, Connectors, Knowledge Sources & Agentic Workflowslesson
- Lesson 12.9: Human-in-the-Loop Approvals, Security & Safe Automation Boundarieslesson
- Lesson 12.10: Testing, Monitoring, Error Handling & Measuring Business Valuelesson
Section 13
Module 13: Business Improvement Capstone
- Lesson 13.1: Selecting a Business Process or Workplace Problem to Improvelesson
- Lesson 13.2: Mapping the Current Workflow, Pain Points, Costs & Delayslesson
- Lesson 13.3: Identifying Where AI, Automation or Better Data Can Helplesson
- Lesson 13.4: Designing the Future Workflow with Human Review Pointslesson
- Lesson 13.5: Building or Prototyping Two to Three Practical AI-Assisted Workflowslesson
- Lesson 13.6: Measuring Time Saved, Quality Improvement, Risk & Expected Business Valuelesson
- Lesson 13.7: Presenting an AI & Automation Business Improvement Planlesson