Lesson library
Practical AI lessons for real life
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🌱 Free course · 8 lessons
Your First Week with AI
Never used an AI assistant? Seven short days from opening the tool for the first time to a ten-minute daily habit — built for people who feel the office moving without them.
1. Day 1: You are not behind
Most colleagues are improvising too — the gap is a habit, not a talent
2. Day 1: Open a tool and calibrate it
Your first conversation should be about something you already know — so you can see what the tool is
3. Day 2: Your first genuinely useful task
Summarising something long that you already read is the safest first win
4. Day 3: Brief it like a colleague
Bad answers usually mean a bad brief — context, task, and format fix most of them
5. Day 4: What never goes in the box
Passwords, ID numbers, and client secrets stay out — and work content belongs in work-approved tools
6. Day 5: Draft with it, never ship it
AI writes the first draft; you own every name, number, and promise that leaves your outbox
7. Day 6: Why it sounds confident when it is wrong
Fluency is not accuracy — trust transformations of your material, verify claims from its memory
8. Day 7: Your daily ten minutes
A tiny daily routine on two recurring tasks beats occasional heroics — and decides who stays ahead
🧭 Free course · 12 lessons
AI at Work Foundations
What AI tools can and cannot do, when to trust them, and how to get useful answers on the first try.
1. What AI actually is (and is not)
An LLM predicts plausible text from patterns; it is not a database of facts
2. Your first real prompt: context, task, format
A useful prompt states the context, the task, and the output format
3. When to trust the answer
Verify anything the model recalled on its own; trust transformations of material you supplied
4. Give it a role
Assigning the model a role focuses its expertise and tone on your situation
5. Show, don't tell: examples beat descriptions
One or two examples of the output you want beat paragraphs of description
6. The critique loop: make it improve its own work
Asking the model to critique and revise its own output reliably raises quality
7. Ask better follow-up questions
The first answer is a starting point; targeted follow-ups that name what to change beat starting over
8. Make AI ask you questions first
When your request is fuzzy, tell the AI to ask you questions before it answers
9. Use your own facts first
Supply the facts yourself and ask the model to do the language work, not the recall
10. Check before you send
Run a quick verification pass over numbers, claims, and tone before forwarding AI-assisted work
11. Private, sensitive, or safe to paste?
Classify information as public, internal, or confidential before putting it into AI
12. Your personal AI task map
Choose where to use AI by mapping your tasks on value/frequency against risk
💬 Premium course · 10 lessons
Claude Mastery
Projects, file analysis, drafting workflows, and artifacts — turn Claude into your sharpest colleague.
1. Projects: stop re-explaining yourself
A Project stores instructions and reference files so every new chat starts already briefed
2. Put your documents to work
Upload files and demand quoted evidence so answers stay grounded in the document
3. Blank page to usable draft in three prompts
Brief, draft, critique: a repeatable three-prompt writing workflow
4. Artifacts: when chat becomes a thing
Ask for an artifact when the output is a standalone thing you will reuse, not a reply
5. Meetings into minutes (and actions)
A transcript plus a strict output format turns meetings into decisions, actions, and owners
6. Safe, private, professional
Treat pasted content as leaving the building: minimize, anonymize, verify
7. Long documents without getting lost
Map-first reading: outline the document before asking detailed questions
8. Build a reusable project instruction
Standing instructions cover role, context, style, sources, and boundaries
9. Compare two documents
Ask for differences, conflicts, omissions, and decision impact — not a vague summary
10. Turn an artifact into a working template
Artifacts become reusable when slots, instructions, and examples are frozen
🧩 Premium course · 12 lessons
Prompting Patterns
Six repeatable patterns that work in any AI tool — decompose big jobs, make it interview you, compare options, and steer without starting over.
1. One job per prompt
Big bundled requests produce mush; a pipeline of small single-job prompts produces quality
2. Make it interview you
Telling the model to ask you questions first beats guessing what context it needs
3. Options first, then commit
Asking for three distinct versions with trade-offs beats accepting the first answer
4. Constraints are instructions too
Stating hard limits — length, banned content, must-keep facts — prevents the failures you cannot un-see
5. Steer with deltas, restart when stuck
Targeted change requests beat re-explaining, and a fresh chat beats a polluted one
6. Build your prompt library
A winning prompt with fill-in-the-blank slots is a tool your whole team can reuse
7. Success criteria before prompt wording
Define what good looks like before you ask the model to produce anything
8. Plan, do, check
Ask for a plan, execute one step, then verify against criteria before continuing
9. Extract, transform, apply
Turn messy input into structured output, then use that structure in the next prompt
10. Red-team your answer
Ask a second pass to find risks, assumptions, weak claims, and missing perspectives
11. Structured outputs: tables, JSON, checklists
Format is part of the task — specify columns, keys, or checklist items exactly
12. Prompt repair clinic
Diagnose weak prompts with a checklist: job, context, criteria, format, scope
🏪 Free course · 10 lessons
Small Business AI Foundations
Ten practical lessons for owners who need more customers, faster replies, better admin, clearer money, and safer AI habits.
1. AI for small business without the hype
AI is useful when it helps with cash, customers, consistency, and control
2. Find your hours back tasks
Start with frequent, annoying, low-risk tasks that a human can quickly check
3. Describe your customer clearly
Better customer understanding creates better marketing, replies, and offers
4. Turn one offer into many messages
One offer can become a poster, WhatsApp, caption, SMS, and short script
5. Social posts that do not sound fake
AI should draft useful content, but the owner must add proof and local detail
6. Customer replies for WhatsApp and email
Fast, polite, consistent replies save time and protect reputation
7. Ask for and respond to reviews
Reviews build trust; responses should be specific, calm, and human
8. Product and service descriptions
Clear descriptions reduce confusion and help people buy
9. Simple numbers in plain English
AI can explain sales, expenses, and cashflow if you give it the facts
10. AI safety for small businesses
Do not paste private customer data, passwords, card details, or sensitive business information
📈 Premium course · 16 lessons
Small Business Growth & Operations System
A Pro course for turning AI into repeatable workflows: marketing calendars, offers, follow-ups, quotes, cashflow reviews, SOPs, and owner playbooks.
1. Build your business command centre
Keep business facts, offers, prices, policies, and tone in one reusable brief
2. The customer journey map
Map how strangers become repeat customers
3. Create a 30-day marketing calendar
Marketing becomes easier when themes, offers, and channels are planned
4. Write offers people understand
Good offers say who it is for, what they get, why now, and what to do
5. Local business content engine
Turn real shop moments into posts: before-after, FAQ, customer story, behind the scenes
6. WhatsApp sales follow-up
Most sales need reminders, not pressure
7. Customer complaint recovery
A calm complaint response can save reputation and reveal operational problems
8. Quote and proposal builder
A quote should make scope, price, timing, exclusions, and next step clear
9. Supplier comparison without spreadsheets
AI can compare offers if you provide the facts and criteria
10. Pricing sanity check
AI can help think through costs, margin, positioning, and customer value
11. Weekly cashflow conversation
Owners need a weekly habit to understand money in, money out, and risks
12. Stock and inventory notes
AI can help spot fast movers, slow movers, and reorder risks from simple notes
13. SOPs from how we do it
Turn owner knowledge into repeatable staff instructions
14. Staff training cards
Small teams need clear, short, repeatable training
15. Monthly owner review
Review customers, cash, operations, risks, and next experiments
16. Your small-business AI playbook
Save the best workflows as reusable templates
💼 Free course · 10 lessons
AI Career Foundations
Ten practical lessons for job seekers and workers who need proof-based CVs, stronger applications, better interviews, and safer job-search habits.
1. AI is changing work, but you still matter
AI changes tasks, not just job titles; human judgment still matters
2. Build your proof bank
Collect real examples before writing a CV
3. Decode a job ad
Job ads contain hidden priorities: tasks, tools, traits, and evidence
4. CVs without lying
Use AI to sharpen truth, not invent experience
5. Cover letters people might actually read
A good letter connects proof to the employer problem
6. Interview stories with structure
Use STAR or CAR to turn experience into clear answers
7. LinkedIn and profile basics
Your profile should say what you do, who you help, and what proof you have
8. Learn the skill gap
Compare your current proof to target roles
9. Avoid fake jobs and application traps
Job seekers are fraud targets; verify before sharing documents or paying fees
10. Your 7-day job search routine
A repeatable routine beats panic applying
🚀 Premium course · 16 lessons
Career & Income Accelerator
A Pro course for building a serious career system: target roles, evidence inventory, tailored CVs, portfolio samples, interview practice, and monthly reviews.
1. Choose a realistic target role
Better applications start with a clear target
2. Your career evidence inventory
Collect proof from work, school, volunteering, family business, projects, and life
3. Translate experience into employer language
Employers buy outcomes, not duties
4. Build a master CV
One strong master CV feeds tailored versions
5. Tailor a CV to a job ad
Match relevant proof to the role without keyword stuffing or lying
6. Write human cover notes
Short, specific messages beat generic AI letters
7. Build a work-sample portfolio
Proof can be created through sample work, not only past jobs
8. Networking without begging
Good outreach asks for advice, information, or a small next step
9. Interview practice with AI
AI can simulate interviews, but you must answer from real stories
10. Difficult interview questions
Prepare for gaps, failures, salary, conflict, and weaknesses
11. Salary and offer conversations
Prepare calmly using value, market context, and priorities
12. Your 30-day skill sprint
Learn one valuable skill through small daily proof-building tasks
13. Use AI once you get the job
AI can help you onboard, summarize, plan, and communicate
14. Freelance or side-income basics
A small service offer can create experience and income
15. Your career dashboard
Track applications, conversations, interviews, skills, and follow-ups
16. Monthly career review
Review evidence, gaps, applications, and next moves
⚖️ Free course · 12 lessons
AI Legal Research Foundations
A free safety-first course for non-lawyers: legal information versus advice, SOURCE method, jurisdiction, source verification, lawyer briefs, and red flags.
1. Legal information is not legal advice
AI can explain legal information, but it cannot replace a lawyer's judgment
2. The SOURCE method
Research starts with facts, jurisdiction, official sources, validation, and escalation
3. What law applies where?
Jurisdiction matters: South African law is not US, UK, or Australian law
4. Find the legal issue, not just the emotion
“This is unfair” must become a legal research question
5. Use AI to build a legal research plan
AI is useful for planning searches and keywords, not as the final authority
6. Sources of law in plain English
Constitution, Acts, regulations, by-laws, cases, court rules, contracts, and policies are different sources
7. Cases and precedents in plain English
A case matters because of the rule it decides, not because it sounds similar
8. Never trust a case until you verify it
Check the case exists, citation, court, date, paragraph, and proposition
9. Read legislation without panic
Definitions, scope, exceptions, commencement, amendments, and regulations matter
10. Ask AI to explain a case you provide
Paste the real judgment and ask for issue, rule, facts, outcome, and caveats
11. Build a legal question for a lawyer
The best use of AI may be preparing a clear attorney brief
12. When to stop researching and get help
Deadlines, court papers, threats, arrests, eviction, custody, and money claims need human help
🇿🇦 Premium course · 16 lessons
South African Legal Research with AI
A Pro course for careful South Africa-grounded research using primary sources, court hierarchy, SAFLII, LawLibrary, legislation, cases, and authority tables.
1. The South African legal source map
Know where to look: Constitution, Acts, regulations, gazettes, cases, rules, regulators
2. Court hierarchy and precedent
Authority depends on court level, issue, and whether a decision binds or persuades
3. Use SAFLII safely
Search, open, read, and cite South African cases from primary sources
4. Use LawLibrary safely
Search judgments, legislation, gazettes, and recent legal materials
5. Legislation currentness
Acts change; check amendments, commencement, regulations, and version dates
6. Read a judgment like a researcher
Identify facts, issue, rule, reasoning, order, and paragraphs worth citing
7. Ratio, obiter, and outcome
Not every sentence in a judgment is the legal rule
8. Binding vs persuasive authority
Higher courts bind; similar, lower, or foreign decisions may persuade but need caution
9. The authority table
Every legal claim must connect to a source, paragraph, and verification status
10. Validate an AI legal answer
Break AI output into claims and verify each claim independently
11. Statutes plus cases
Legislation gives the rule; cases show how courts interpret and apply it
12. Foreign law traps
UK, US, Australian, and EU law may be useful background, but not South African authority
13. Legal research memo
A good memo states question, sources, answer, uncertainty, and next steps
14. Preparing for attorney consultation
Give the lawyer facts, documents, questions, risks, and what you already checked
15. Research for disputes before court
Organize facts, documents, evidence, timelines, and possible legal routes
16. Final project: verified research pack
Demonstrate safe legal research without giving yourself legal advice
📄 Premium course · 12 lessons
Legal Research for Small Businesses and Teams
A Pro/Team course for contracts, supplier disputes, debt, labour, POPIA, consumer complaints, leases, risk registers, and attorney-ready briefs.
1. Legal research for business owners
Research helps you ask better questions; it does not replace legal advice
2. Contract clauses in plain English
Use AI to explain clauses, risks, obligations, and missing terms
3. Before you sign
Build a contract review checklist: parties, price, scope, duration, breach, cancellation, liability
4. Supplier and client disputes
Turn a dispute into timeline, documents, legal questions, and possible routes
5. Debt collection basics
Understand invoices, demand letters, prescription, proof, and escalation
6. Employment issue research
Separate facts, policy, contract, labour law, and CCMA route
7. POPIA and data privacy research
Identify personal information, purpose, consent, safeguards, and incident response questions
8. Consumer complaints and refunds
Research customer rights, warranties, returns, and ombud routes
9. Leases and property obligations
Extract rent, breach, repairs, cancellation, deposits, and notice terms
10. Legal risk register
Turn recurring legal risks into a business review habit
11. Attorney-ready business brief
Reduce lawyer time by preparing facts, documents, questions, and source links
12. Team AI legal research policy
Set rules for what staff may research, paste, draft, and escalate
🛡️ Free course · 10 lessons
AI Fraud Awareness Foundations
Free prevention: spot AI-powered scams before you click, pay, share, approve, or panic.
1. Why scams look real now
AI removes old warning signs like bad grammar and ugly design
2. The PAUSE rule
Stop before you click, pay, share, approve, or panic
3. Fake bank emails and SMSs
Phishing and smishing push fake links, sites, and login pages
4. Fake calls and voice clones
A familiar voice or bank official is not proof
5. WhatsApp scams and fake support agents
Fraudsters move victims into private chats where pressure increases
6. Fake investment ads and celebrity deepfakes
Unrealistic returns plus public-figure endorsement is a danger pattern
7. OTPs, PINs, passwords, and push approvals
The words in the approval matter — do not approve what you did not initiate
8. Fake apps and remote access
Fraudsters use security apps, screen sharing, and remote tools to take control
9. SIM swaps, device theft, and notification gaps
Loss of signal, new device alerts, and missing notifications are evidence
10. Your personal fraud safety plan
Prevention works best when rules are decided before panic
⏱️ Free course · 10 lessons
If Money Is Gone — The First 24 Hours
Free emergency course: limit damage, preserve evidence, and start your case file in the first day.
1. The first 10 minutes
Stop further loss before investigating
2. Call the bank safely
Use official channels, not numbers from messages
3. Freeze, block, reset
Cards, profiles, devices, passwords, beneficiaries, and limits may need immediate action
4. Start the fraud timeline
Memory fades; write facts while they are fresh
5. Preserve screenshots and messages
Evidence must be saved before apps, scammers, or banks remove it
6. Report to SAPS
A police report creates a CAS number and official record
7. Protect your identity
A banking scam may also mean personal information is compromised
8. Log the formal bank complaint
The NFO usually comes after the bank complaint process
9. Do not contaminate the evidence
Guessing, deleting, editing, or inventing facts hurts credibility
10. First 24-hour review
Convert panic into a clear case file
🔍 Premium course · 12 lessons
Bank Fraud Investigation for Non-Technical People
Pro course: test the bank’s rejection with timelines, records, and the PROVE framework.
1. The dispute frame
Most disputes turn on negligence, authorisation, and control failure
2. Build the master timeline
A timeline is the spine of the case
3. Map the disputed transactions
Each transaction needs amount, time, channel, destination, approval method, and report time
4. Device and SIM chain
New devices, SIM swaps, and signal loss matter
5. OTP and push-approval audit
OTP used is not enough — what did it say and what was approved?
6. Beneficiary and limit changes
Fraud often requires adding beneficiaries or changing limits
7. Bank alerts and notifications
Map alerts: active, inactive, sent, failed, or delayed
8. Fraud holds and block failures
What happened after the bank detected risk or you reported?
9. Inter-bank recovery attempts
The sending bank recovery process can be decisive
10. Read the bank rejection letter
Split the bank response into claims that need proof
11. Find contradictions
Compare bank claims against logs, timelines, and notifications
12. Case theory without exaggeration
Your theory should be factual, not emotional
📋 Premium course · 10 lessons
Data Requests, POPIA, PAIA, and Bank Records
Pro course: request the right bank records lawfully and clearly.
1. What records can prove
Records show timing, authorisation, control decisions, and bank response
2. POPIA access requests
Ask for personal information and account records under POPIA
3. PAIA requests
Use PAIA where records are needed to exercise or protect rights
4. Ask narrowly, not wildly
Better requests are specific, dated, and connected to the dispute
5. Call recordings and transcripts
Calls can prove what was reported, promised, or misrepresented
6. Login, device, and session records
Test whether activity matches your normal behaviour
7. OTP, push, and 3D Secure records
Approval records can prove or weaken a case
8. Notification delivery records
Missing or misleading alerts can matter
9. Fraud, block, and recovery records
The bank response after notice is often decisive
10. Handling refusals and partial records
Ask for summaries or reasons when full data is refused
📨 Premium course · 12 lessons
Build the Bank Complaint and NFO Pack
Pro course: affidavits, complaint letters, rejection responses, and NFO escalation.
1. Complaint anatomy
Strong complaints have facts, evidence, issue, bank failure, remedy, and records requested
2. Your affidavit with AI
AI can organise facts, but you must verify every line before swearing
3. Disputed-transaction schedule
One table should show every disputed transaction clearly
4. Responding to you were negligent
Separate admitted facts, disputed facts, and missing bank evidence
5. Responding to you authorised it
Test authorisation against OTP content, device records, and context
6. Responding to your device was compromised
Ask for device registration, session history, and notification evidence
7. Responding to the OTP was used
Ask what the OTP said, where it went, and what transaction it approved
8. Responding to we tried to recover funds
Ask when, how, and to whom the recovery request was made
9. Responding to voluntary payment
APP cases are hard — focus on deception, advice, or process failure if evidence exists
10. The NFO escalation pack
The NFO needs a clear file, not a messy story
11. Remedy and outcome
Ask clearly for refund, fee reversal, correction, or explanation
12. Final review: attorney, NFO, or court?
Some cases need legal advice, urgent action, or court procedure
🏢 Premium course · 12 lessons
Small Business and Workplace Bank Fraud Defence
Team course: invoice fraud, supplier changes, dual approvals, and business NFO packs.
1. Business email compromise
Fraudsters redirect payments through fake invoices or changed bank details
2. Supplier bank-detail changes
Never change bank details from email alone
3. Dual approvals and payment limits
Controls should slow down high-risk payments
4. Director, CFO, and manager impersonation
Authority plus urgency is a fraud pattern
5. Bank advice and reliance
If a bank employee gives payment advice, record and confirm it in writing
6. Evidence after a business payment scam
Preserve emails, headers, invoices, payment logs, and bank calls
7. Inter-bank recall and recovery
Recovery depends on timing, available funds, and beneficiary consent
8. POPIA breach assessment
Some fraud events may involve personal information compromise
9. Staff statements
Staff need factual statements, not blame essays
10. Business NFO pack
Build a complaint with authority, mandate, and loss records
11. After-action review
Turn the incident into better controls
12. Team fraud playbook
A playbook prevents repeat mistakes
🛠️ Free course · 8 lessons
Vibe Coding Foundations
Build your first app with AI — from a small idea and brief to prototype, review, and production readiness.
1. What vibe coding actually is
AI writes code; you own decisions, scope, testing, and verification
2. Your first app idea: small, useful, safe
First apps should be narrow, low-risk, and testable in a week
3. The app brief
A one-page brief names user, problem, workflow, data, and success
4. Prototype before production
Use fast prototypes to test ideas before committing to a full codebase
5. The feature card
Scope one feature with acceptance criteria, constraints, and tests
6. GitHub without fear
GitHub is your app history and safety net — not something only engineers touch
7. Review AI code when you cannot code yet
Review behaviour, changed files, screenshots, tests, and risks — not syntax line by line
8. What makes an app production-ready
Production means real users, safe data, auth, testing, hosting, and ops — not just a demo
🚀 Premium course · 4 lessons
Vibe Coding Builder
Your first production app path — mindset, prototype, workbench setup, and app shell.
1. App Builder Mindset
You are the product owner; AI is the fast builder you direct and verify
2. Prototype with Codex Sites
Use Codex Sites for fast demos before committing to a full repository
3. Your AI Coding Workbench
Map your tools: repo, editor, agents, deploy CLI — each with a clear job
4. Build the App Shell
Scaffold landing page, dashboard, navigation, and empty/error states before features pile up
⚖️ Premium course · 8 lessons
AI Safety & Professional Judgment
Classify risk, handle data safely, spot false confidence, and build team guardrails — not one lesson, a habit.
1. The AI risk ladder
Low-risk language work differs from high-risk decisions about people, money, and law
2. Data classification before prompting
Decide what can be pasted, anonymized, summarized, or withheld
3. Hallucinations and false confidence
AI can sound certain while being wrong — tone is not evidence
4. Bias, fairness, and missing perspectives
Ask who may be harmed or overlooked before acting on AI output
5. Legal, medical, HR, and financial boundaries
AI can assist preparation but cannot replace accountable professionals
6. The human sign-off checklist
Build a short review process before using AI output on medium and high-risk tasks
7. Disclosure and audit trails
Some work needs transparency about AI use and traceability of decisions
8. Team rules for AI use
A simple one-page team policy beats vague fear or unlimited paste
📄 Premium course · 8 lessons
Documents & Research
Source-first habits: evidence chains, decision briefs, contradictions, and number verification.
1. Source-first research
AI output is only as good as its evidence chain
2. Ask for claims, evidence, and confidence
Separate answer, evidence, and uncertainty in one structured response
3. Summarize without losing the important bits
Purpose-specific summaries beat generic shorter versions
4. Find contradictions and gaps
Documents disagree and omit facts — ask AI to surface conflicts explicitly
5. Turn documents into decision briefs
A decision brief gives recommendation, reasons, risks, and next action
6. Numbers, tables, and totals
Treat numbers as high-risk — extract then verify separately
7. Research questions vs writing questions
Research needs source discipline; writing can be more creative within bounds
8. Build a source pack
Collect the few documents AI needs before asking — checklist for your job
✍️ Premium course · 8 lessons
AI for Writing & Communication
Write for the reader: executive summaries, difficult emails, memos, proposals, and voice guides.
1. Write for the reader, not yourself
Audience changes structure, tone, and detail level
2. Executive summaries that actually help
Lead with decision, implication, and next action — not background history
3. Difficult emails without sounding robotic
Firm, clear, human tone — state facts, boundary, and next step
4. Turn notes into a memo
Raw notes need grouping, hierarchy, and explicit gaps
5. Proposals and pitches
Problem, outcome, proof, cost, next step — in that order
6. Edit for clarity
Cut, simplify, and reorganize — preserve meaning and numbers
7. Brand and voice without cringe
Use examples and banned phrases to control style
8. Feedback without defensiveness
Use AI to separate emotion from useful signal and action items
📅 Premium course · 8 lessons
Meetings, Admin & Operations
Save hours weekly: meeting actions, SOPs, checklists, support macros, reports, and handovers.
1. Meeting notes into action
Extract decisions, actions, owners, dates, and open questions — mark unknowns UNSTATED
2. SOPs from messy know-how
Turn how we do it into numbered steps with checks and escalation
3. Checklists that prevent mistakes
Catch failure points before send or launch — not list obvious tasks
4. Customer replies and support macros
Standardize helpful replies without robotic tone — slots for personalization
5. Cleaning messy spreadsheet text
Normalize labels categories and descriptions with rules you verify
6. Weekly report in 10 minutes
Fixed structure plus recurring inputs beats blank-page reporting
7. Handover notes
Scattered context into next-person clarity: status, decisions, risks, contacts
8. Process improvement assistant
Ask AI to find bottlenecks risks and simplifications in a process description
📊 Premium course · 8 lessons
AI for Excel, Sheets, and Numbers
Spreadsheet judgment: clean text, ask business questions, summarize tables, formulas, pivots, anomalies, charts, verify totals.
1. Clean messy spreadsheet text
Normalize categories names and dates with rules you approve before bulk apply
2. Ask better questions of numbers
Start with the business question not the formula
3. Summarise a table safely
Provide the table ask for insights and explicit caveats about missing data
4. Formula helper without fear
Explain formulas step-by-step and build them for your stated goal
5. Pivot-table thinking in plain English
Group compare count summarize — describe the pivot before clicking
6. Find anomalies
Spot outliers and suspicious entries — verify before acting
7. Chart choice
Pick chart type by the business question not the default button
8. Numbers verification
AI miscalculates — verify totals independently before decisions
🚀 Premium course · 12 lessons
ChatGPT & Codex Mastery
Get real work done with ChatGPT — projects, deep research, data analysis, and agents — then delegate your first small build to Codex without becoming a developer.
1. The ChatGPT map: modes matter more than models
Fast answers, thinking, deep research, and agent mode are different tools — picking the mode is the skill
2. Memory and custom instructions that work for you
Teach ChatGPT your role, formats, and standards once — and control what it remembers
3. Projects: one workspace per recurring job
A project bundles instructions, files, and memory so recurring work starts pre-briefed
4. Deep research: a cited brief while you make coffee
Deep research reads dozens of sources and returns a cited report — your job is scoping and verification
5. Canvas: draft documents side by side, not in the chat stream
Canvas separates the document from the conversation so you can edit surgically instead of regenerating
6. Data analysis: tables in, checked answers out
ChatGPT runs real Python on your uploaded data — powerful, and only trustworthy with spot checks
7. Agent mode with a safety harness
Agents click, browse, and complete multi-step tasks — supervision and boundaries are what make that safe
8. Scheduled tasks: AI on a weekly rhythm
ChatGPT can run recurring tasks unattended — worth it only for briefings, never for unchecked decisions
9. Your data: consumer ChatGPT vs work plans
Where you type decides where your words can go — plan type and settings are a professional duty
10. Codex: what it is and why non-developers should care
Codex is an agent that writes and runs code from a plain-language brief — the brief is your job
11. Your first Codex delegation: brief a tiny tool
A buildable brief has purpose, inputs, outputs, rules, and a test you can run without reading code
12. Codex automations, skills, and knowing when to hand over
Standing agents multiply both value and blast radius — start read-only, review rhythms, know the handover line
📎 Premium course · 10 lessons
Microsoft Copilot Mastery
Master Microsoft 365 Copilot where you already work — Word, Excel, Outlook, Teams, and PowerPoint — grounded in your own files and checked before anything ships.
1. The Copilot map: Chat, in-app Copilot, and agents
Copilot is three layers — Chat, in-app helpers, and agents — and web versus work grounding decides what it knows
2. Ground it in your work: files, people, and meetings
Referencing specific files, people, and meetings turns Copilot from a generic writer into YOUR analyst
3. Word: a first draft from your sources, not from vibes
Draft from referenced documents, edit by selection, and keep names, numbers, and commitments human-checked
4. Excel: ask your table a business question
Copilot analyses, explains formulas, and follows workbook rules — and you still spot-check the totals
5. Outlook: summarise threads, draft replies, keep your name on it
Thread summaries, prioritisation, and selection rewrites cut email hours — sending stays a human act
6. Teams meetings: recap, actions, and honest minutes
Meeting recap turns transcripts into decisions and owners — consent and correction stay human work
7. PowerPoint: a deck from a document, not from vibes
Decks built from a source document inherit real content — you own the narrative and every number on screen
8. Agent mode and productivity agents: supervise like a manager
Copilot agents take multi-step actions in your documents — checkpoints and review turn power into safety
9. Copilot Pages and your prompt library: make good prompts reusable
Pages turn chat answers into living team documents; a prompt library turns your best prompts into assets
10. Governance: what Copilot can see is what it can surface
Copilot inherits your permissions — oversharing, labels, and knowing when to escalate are part of using it well
🧭 Premium course · 10 lessons
AI for Managers & Team Leads
Your team is already using AI — with or without you. Set the ground rules, review AI-assisted work fairly, delegate across people and machines, and grow the skills without a training budget.
1. The manager's real AI job
Your job is standards and judgment for the team, not being its best prompter
2. Delegate to AI, to people, or to neither
Triage tasks by stakes and verifiability — not by what is technically possible
3. Reviewing AI-assisted work fairly
Review the substance and the inputs, not whether AI touched it
4. One page of team AI ground rules
Four sections — tools, never-paste, verification, disclosure — beat any forty-page policy
5. Run the team rhythm on decisions, not memory
AI recaps and action tracking give the team one honest record — if the manager curates it
6. Manager writing: feedback, updates, and the privacy trap
AI drafts your recurring communications — but people-content needs stripped inputs and human warmth
7. Data questions without the analyst queue
AI answers table questions in minutes — decisions still wait for one verified number
8. Judging AI tools and vendor claims
Four questions cut through any AI pitch: data, problem, proof, and exit
9. Upskill the team without a budget
Fifteen minutes a week of show-your-trick beats the training course nobody gets
10. What stays human on your watch
Accountability, sensitive conversations, and final judgment do not delegate — deciding that out loud is leadership
🎧 Premium course · 10 lessons
AI for Customer Support & Sales
Front-line AI that customers never regret: replies in your company voice, calm de-escalation drafts, clean handovers, sharper call prep, and follow-ups that remember the conversation.
1. Where AI helps the front line — and where it burns trust
AI compresses the writing and reading; the customer relationship stays handmade
2. Replies that sound like your company, not like AI
Two example replies teach the voice better than any tone adjective
3. The angry-customer reply
AI keeps the draft calm at scale — the promise-check and the sincerity stay yours
4. The clean handover: case summaries in ninety seconds
A structured case summary transfers a customer without making them repeat themselves
5. Turn solved tickets into team knowledge
Ten minutes after a hard-won solution, AI turns it into an article the whole team can reuse
6. Ten-minute research before the sales call
A structured research brief beats an hour of tab-hopping — with claims verified before you repeat them
7. Follow-ups that remember the conversation
Call notes in, personal follow-up out — with every commitment checked against what you actually said
8. Proposals in an afternoon, numbers checked twice
Assemble proposals from your real sources at AI speed — prices and promises verified by hand
9. Customer data is not AI fuel
The trust customers place in the front line creates duties no deadline suspends — strip, minimise, and use approved tools
10. Your front-line playbook
Assemble the course into a daily loop with saved prompts — and measure the minutes it buys
🔷 Premium course · 10 lessons
Gemini & Google Workspace Mastery
Master Gemini where your work already lives — Gmail, Docs, Sheets, Slides, and Meet — plus NotebookLM for grounded research and Gems for reusable assistants, checked before anything ships.
1. The Gemini map: chat, side panels, and your data
Gemini lives in three places, and what it knows depends on where you ask and what you reference
2. Gmail: digest threads, draft from bullets, read before send
Gemini summarises the thread and drafts the reply — the send stays a human act
3. Docs: first drafts from your own files
Help-me-write grounded in Drive files — with style matching — beats generation from nothing
4. Sheets: formulas explained, tables questioned, totals verified
Gemini writes and explains formulas and answers table questions — one spot-check makes it trustworthy
5. Slides: the deck comes from the document
Generate slides from a Doc that says something — you own the narrative and every number on screen
6. Meet: automatic notes, human-checked minutes
Take-notes-for-me turns meetings into records — consent and a correction pass keep the record honest
7. NotebookLM: answers only from sources you chose
Upload the documents; get cited answers from them and nothing else — verification is one click
8. Gems: brief once, reuse forever
A Gem is a saved assistant with your standing instructions — one per recurring job
9. Data boundaries: Gemini sees what you can see
Grounded AI inherits your permissions — surprises are oversharing bugs, and confidential stays labelled
10. Your Google-stack daily loop
Wire the nine skills into the day you already have — and know when to reach outside the stack
Reading is recognition. Practice is the skill.
Members use each idea against a real AI assistant, get feedback on the prompt, and see the lesson again before it disappears from memory.
Start practicing free