3.6Leadership & EntrepreneurshipSession 3 · Deep Learning & Applied Machine Learning

Design thinking and entrepreneurship

10classes30htotalTH1 · PR1 · PNW1weighting per class

Class-by-class breakdown

10 classes

TH = theory · PR = practical · PNW = personal work. These are ministry weighting codes (not hours) used to split each class's minutes. Class length = course hours ÷ class count; the three time-boxes below always sum to that length.

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First 2 classes free with a referral 9 more with enrollment180 min per classTheory 60mPractical 60mPersonal Work 60m
1

Design Thinking for AI Agents — Building Tools People Trust

FreeTH1PR1PNW1

A Digital Marketing Strategist who designs AI agents around real user needs builds tools people trust — design thinking is the method.

Theory60m
  • The design thinking process: empathize, define, ideate, prototype, test
  • Why it's critical for GenAI: trust, hallucination, adoption
  • Real AI products shaped by design thinking
Practical60m
  • Map an AI agent product you use onto the 5 design-thinking stages
  • Identify where trust was won or lost
Personal Work60m
  • Write a one-paragraph take on why empathy comes before building an agent
  • Micro-task: submit your take
2

Empathize — Understanding the User's Real AI Problem

LockedTH1PR1PNW1

Locked class preview

A Data/Business Analyst who skips empathy builds an agent nobody asked for — interviews reveal the real problem AI should solve

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3

Define — Framing the Right Agentic-AI Problem

LockedTH1PR1PNW1

Locked class preview

An AI Integration Manager who frames the problem well saves weeks — a sharp problem statement focuses every later agent design choice

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4

Ideate — Generating AI Agent Concepts Fast

LockedTH1PR1PNW1

Locked class preview

An E-commerce Director who brainstorms 20 agent ideas finds better ones than the first — quantity breeds quality in ideation

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5

Prototype — Making AI Agents Tangible Without Coding

LockedTH1PR1PNW1

Locked class preview

A Project Manager who prototypes an agent cheaply tests before building — a no-code or prompt-only prototype reveals everything

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6

Test — Learning From Real Users (and Catching Hallucinations)

LockedTH1PR1PNW1

Locked class preview

A Data/Business Analyst who tests an agent with 5 users catches hallucinations and trust issues before launch — testing turns assumptions into evidence

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7

AI Agent Opportunities — Where to Actually Build

LockedTH1PR1PNW1

Locked class preview

An AI Integration Manager spots where an agent genuinely adds value — not every problem needs GenAI, and design thinking reveals which do

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8

The Lean Canvas — Mapping a Business Around Your AI Agent

LockedTH1PR1PNW1

Locked class preview

A Sales and Marketing Manager who builds a business around an agent uses the lean canvas — it forces honesty about the model

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9

Pitching Your AI Agent — Telling the Story

LockedTH1PR1PNW1

Locked class preview

A Project Manager who can't pitch a good agent sees it die — a clear pitch turns an AI idea into backing

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10

Present and Reflect — Your AI Agent Concept

LockedTH1PR1PNW1

Locked class preview

This ties the course together — an E-commerce Director presenting a validated agent concept proves the design thinking paid off

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