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What can AI do for me?

A plain-English tour of how software and AI fit into real businesses. No coding.

~12 hrs34 lessons

What you'll be able to do

  • ✓Understand and work in the new AI paradigm
  • ✓Deepen technical skills

About this course

Built for the curious operator who wants to recognize where AI fits - and where it doesn't. Eight grounded business stories, four buckets of company size, and the working vocabulary you need to read a vendor pitch without nodding politely. No code. Theory, quizzes, and interactive puzzles only.

Curriculum

Computer Foundations

The shared vocabulary the rest of the course depends on. Software, the cloud, APIs, databases, frontend vs. backend, and what it means for a piece of software to go live.

7 lessons
▾
  • What a computer isTheory
  • What software isTheory
  • What an API isTheory
  • Where data livesTheory
  • Front and backTheory
  • Going liveTheory
  • Computer foundations capstoneTheory
AI Foundations

What people actually mean when they say machine learning, model, LLM, multi-modal, and so on. The honest cost and accuracy story. The two privacy rules that matter most.

7 lessons
▾
  • What AI actually isTheory
  • How models learn and answerTheory
  • What an LLM doesTheory
  • More than textTheory
  • What AI costs, what it cannot doTheory
  • Privacy and riskTheory
  • Evaluating an AI pitchTheory
Find Your Path

Three short lessons to figure out which business-size module to read next, what a typical AI project actually looks like from kickoff to rollout, and when you should buy off-the-shelf vs. commission something custom.

4 lessons
▾
  • Which module is for youTheory
  • The shape of an AI projectTheory
  • Buy vs buildTheory
  • Find your path capstoneTheory
Solutions for Entrepreneurs

Two narrative case studies for one-person businesses: a landscaping contractor drowning in lead emails, and an Etsy seller losing two hours a day to product descriptions. Each story sketches a realistic, modest AI solution.

3 lessons
▾
  • Rosa's lead inbox is winningTheory
  • The Etsy seller who gets his evenings backTheory
  • Solo solutions capstoneTheory
Solutions for Small Businesses

Two narrative case studies for businesses with roughly five to fifty people: a family honey company buried in repetitive customer-service email, and a veterinary clinic whose patient intake is scattered across paper and voicemail.

3 lessons
▾
  • The honey company that stops answering the same email 40 times a dayTheory
  • The vet clinic that stops dropping voicemailsTheory
  • Small business solutions capstoneTheory
Solutions for Medium Businesses

Two narrative case studies for organizations with roughly fifty to five hundred people. You're an individual contributor here - a marketer, an ops analyst - bringing a pitch to the team. Outdoor-gear search, and freight-dispatcher voice agents.

3 lessons
▾
  • The outdoor retailer whose search finds the wrong sockTheory
  • The freight dispatcher who stops drowning in callsTheory
  • Buying AI at ScaleTheory
Solutions for Large Businesses & Enterprises

Two narrative case studies in regulated, large-org environments. You're an individual contributor - a claims specialist, a clinical informaticist - who sees an obvious win. Insurance-claim summaries, and a private clinical-records assistant. Privacy and human-in-the-loop are central.

3 lessons
▾
  • The insurance adjusters who stop reading 200-page claim filesTheory
  • The hospital that runs its own AITheory
  • Large business solutions capstoneTheory
How to Evaluate an AI Proposal

Wrap-up. The four red flags that show up in nearly every bad pitch, the small set of questions worth asking before signing, and a short note on staying current.

4 lessons
▾
  • Four red flags in any AI proposalTheory
  • Five questions to put to any AI vendorTheory
  • Staying current without drowning in AI newsTheory
  • Evaluating an AI ProposalTheory
Free
  • ✓ 34 lessons across 12 hours
  • ✓ Self-paced