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📄 Week 1 Day 1 — Introduction to AI
📄 Week 1 Day 2 — Prompts & Code
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📄 Week 1 Day 1 — Introduction to AI

Week 1 Day 1 — Introduction to AI

Welcome! Today you'll get hands-on with AI tools and start building intuition for how they work.

Exercise 1

Ask AI Something You're Curious About

Open ChatGPT, Claude, or Gemini and ask it a genuine question. Try one of these starters, or make up your own:

Why does the sky change color at sunset?

What would happen if humans could photosynthesize like plants?

Explain quantum entanglement like I'm 12 years old.

Notice: How long is the answer? Does it feel confident? Does it hedge? Does it ask you anything back?

What you'll see: Answers are long and confident-sounding even for genuinely uncertain topics. AI rarely says "I don't know" — it fills in gaps with plausible-sounding text. It almost never asks a clarifying question back unless you tell it to. That confidence without uncertainty is the main thing to internalize on day one.

💡 Tip: AI works best when your question is specific. "Tell me about history" is hard — "What caused the fall of the Roman Empire in 3 bullet points?" is easy.

Exercise 2

Ask AI to Write Something for You

Try this prompt to get a short professional bio:

Write a 2-sentence professional bio for someone who is learning cloud computing and wants to transition into tech. Make it confident and forward-looking.

Read the output. Then try the prompt → output → feedback loop:

Read what it gave you.
Identify one thing you'd change (too formal? too short?).
Tell the AI: "Make it less formal and add a line about my interest in cybersecurity."
Compare version 1 vs version 2. What changed?

🔁 This loop — prompt → read → refine — is the core skill of working with AI. You rarely get perfection on the first try, and that's fine.

Exercise 3

Ask AI Something It Can't Answer

Try one of these and observe what happens:

What is the exact temperature outside my house right now?

What did I eat for breakfast this morning?

Will my team win the game tomorrow?

Notice how AI handles the limits of its knowledge. Does it refuse? Make something up? Offer a workaround? Understanding these failure modes makes you a smarter user.

What you'll see: For real-time questions (temperature, breakfast) AI will usually say it doesn't have access to live data — that's the correct response. For the sports prediction it'll often make a probabilistic guess anyway. The pattern: AI knows what it can't know, but doesn't always stop itself from answering anyway. Always ask yourself "could it actually know this?"

Exercise 4

Prediction Game

Part A — Finish the sentence: Predict what AI will say, then check.

"The most important invention of the 20th century was…"
"If I could have any superpower, I would choose…"
"The best way to learn something new is to…"

What you'll see: AI's completions trend toward the statistically common answer — "the internet," "flight," or "the printing press" for #1; something like "fly" or "teleportation" for #2. Run the same prompt three times: you'll get different wording each time, sometimes different answers entirely. This is the temperature (randomness) built into the model. It's not a bug — it's intentional so responses don't feel robotic.

Part B — Break it on purpose: Try to get AI to produce something weird or wrong.

Write a recipe for a cake made entirely of rocks. Be very specific about baking times.

What you'll see: AI will almost certainly play along — it'll invent "granite flour," "limestone extract," and a bake time like "350°F for 45 minutes." It won't refuse, it'll just comply creatively. This reveals that AI is a pattern-completion engine, not a logic checker. It doesn't stop to ask "wait, can you actually eat rocks?" That's your job.

Exercise 5

AI Can Code

Click the link below to open a live, working web app — built by asking AI to write the code:

🔗 https://simple-hello--fundlush1.replit.app/

You didn't write any of that code. An AI did — from a plain-English description. That's where this course is headed.

💡 By the end of this course, you'll be giving AI instructions like these and understanding what comes back.

Week 1 · Day 1

📄 Week 1 Day 2 — Prompts & Code

Week 1 Day 2 — Prompts & Code

🔬 Lab 1: Prompt Makeover

For each prompt below, compare the vague version to the improved version and study what changed.

Prompt A — Calculator

BAD PROMPT

Make a calculator

BAD OUTPUT (typical)

Here's a simple calculator in Python: def add(a, b): return a + b def subtract(a, b): return a - b # etc.

IMPROVED PROMPT

Write a single-page web calculator using HTML, CSS, and JavaScript. It should look like a classic desktop calculator with buttons for 0–9, +, −, ×, ÷, =, and Clear. Style it with a dark background and large readable buttons. No external libraries.

IMPROVED OUTPUT (typical)

Here's a complete HTML file with an inline CSS grid layout, click handlers for each button, and a display area that updates live. Clear resets to "0", operators chain correctly…

WHAT CHANGED

+ Specified output format (single-page HTML)
+ Listed exact features needed (0–9, ops, Clear)
+ Described visual requirements (dark bg, large buttons)
+ Added constraint (no external libraries)
− Removed ambiguity about language and interface

Stretch Goal — 3-Iteration Table

Iteration	Prompt Change	Result Improvement
1	Added "HTML/CSS/JS, no libraries"	Got a working file instead of snippets
2	Added "grid layout, Win95 aesthetic"	Styled buttons, beveled borders, gray palette
3	Added "keyboard support, chained ops"	Keydown events added, operator logic fixed

Prompt B — Resume

BAD PROMPT

Help me with my resume

BAD OUTPUT (typical)

Sure! Here are some tips for a strong resume: • Use action verbs like "led," "built," and "managed" • Keep it to one page • Tailor it to each job description • Include measurable achievements Would you like help with a specific section?

IMPROVED PROMPT

I'm a cloud engineer and full-stack developer with 8+ years of experience across independent consulting, agency work, and venture-backed startups. I founded Samwise Development (consultancy, 2022–present), contracted at Google IO via Left Field Labs, co-founded Distributron (reached YCombinator interview) and Treetz (indie game studio, team of 6), built Safety+ for Coca-Cola, and started my career at 1SEO Digital Agency and PSU's DARPA-funded Applied Research Lab. Stack: React, Vue, TypeScript, Python, PHP/Laravel, Tailwind, AWS, Azure, GCP, Cloudflare, Docker, Kubernetes, Linux, CI/CD. Certs: CompTIA A+, LPI Linux Essentials. Write a one-page resume optimized for senior contract and consulting roles, emphasizing technical breadth, entrepreneurial track record, and measurable impact. Use bullet points.

IMPROVED OUTPUT (example)

Penn Cameron Porterfield — Cloud Engineer & Full Stack Developer fundlush@proton.me · pcporterfield.pages.dev · github.com/melonmelonz Samwise Development — Founder & Consultant (2022–Present) • Full-stack and cloud infrastructure delivery for clients across industries Google IO — Contract Full Stack Developer (2021–2022) • Production pages via Left Field Labs; Preact + Jinja/Python + Tailwind Distributron — Co-founder & Developer (2020–2021) • Alcohol delivery startup; reached YCombinator interview. Vue, JAMstack Treetz — Co-founder, Indie Game Dev (2019–2020) • Unity mobile game; led team of 6 from concept to production Skills: React · Vue · TypeScript · Python · PHP/Laravel · Tailwind AWS · Azure · GCP · Cloudflare · Docker · Kubernetes · CI/CD CompTIA A+ · LPI Linux Essentials WGU B.S. Network & Cloud Engineering (In Progress) · Penn State 2009–2013

WHAT CHANGED

+ Provided real background (years, companies, stack)
+ Named the target role type (senior contract/consulting)
+ Specified tone and format (bullet points, one page)
+ Called out specific emphasis (breadth, entrepreneurial track record, impact)
− Removed the open-ended ask that produced generic tips

Prompt C — Quiz

BAD PROMPT

Give me a quiz

BAD OUTPUT (typical)

Sure! Here's a general knowledge quiz: 1. What is the capital of France? 2. Who wrote Romeo and Juliet? 3. What is 7 × 8?

IMPROVED PROMPT

Create a 5-question multiple-choice quiz about cloud computing fundamentals for someone with 6 months of experience. Include one question about S3, one about IAM, and one about the difference between IaaS and PaaS. Format each question with (A) (B) (C) (D) choices and put the answer key at the bottom.

WHAT CHANGED

+ Defined audience (6 months cloud experience)
+ Specified topic domain and exact subtopics
+ Requested a format (multiple choice, A–D)
+ Asked for answer key placement

💻 Lab 2: Reading Code

You don't need to know how to write code to read it. Let's practice.

Step 1 — Look at this program

name = input("What is your name? ")
color = input("What is your favorite color? ")
print(f"Hello, {name}! {color} is a great color.")

Before reading the explanation — what do you think this program does? Write your guess.

Step 2 — Line by line

Line 1: Asks the user to type their name. The answer is stored in a box called name.
Line 2: Asks for a favorite color. Stored in color.
Line 3: Combines both answers into a sentence and displays it.

The f"..." syntax means "fill in the blanks" — the {name} and {color} get replaced with whatever the user typed.

Step 3 — Q&A with AI

Paste that code into ChatGPT and ask:

Explain this Python code to me line by line, like I've never programmed before.

Then ask a follow-up:

What would happen if I removed the f before the quote on line 3?

Test the prediction. AI should say the {name} and {color} would print literally instead of being replaced.

Step 4 — Modify it

Ask AI to add a third question:

Add a third input that asks for the user's favorite food, then include it in the final printed sentence.

Copy the output, run it, verify it works. You just modified a program using plain English.

🤝 Peer Activity: Prompt Partners

Task Cards

Pair up. Each person picks one task and writes two prompts: a vague one and a specific one. Then swap and run each other's prompts. Compare results.

🎂 Write a recipe for a birthday cake
✉️ Write an email to a professor asking for an extension
📖 Explain a concept from your field to a 10-year-old
📝 Summarize a news article in exactly 3 sentences

💡 Discussion question: Which partner's improved prompt made the bigger difference? Why?

Debrief — Diana's Answer

Diana tried: "Write an email to a professor asking for an extension."

The AI gave a generic template. Then she improved it:

Write a polite email to my computer science professor asking for a 3-day extension on my programming assignment. My grandmother passed away last week and I've been traveling. I want to sound respectful and professional but also genuine, not over-apologetic.

Result: A specific, warm, appropriately toned email that Diana said she "would actually send."

Key insight: The more context you give, the more useful the output. AI doesn't know your situation — you have to tell it.

🔧 Code Reading + Modification Lab

Read each program, figure out what it does, then use AI to modify it.

Exercise 1 — Tip Calculator

bill = float(input("Enter bill amount: $"))
tip_pct = float(input("Tip percentage (e.g. 20): "))
tip = bill * (tip_pct / 100)
total = bill + tip
print(f"Tip: ${tip:.2f} | Total: ${total:.2f}")

Read it: What does :.2f do? (Hint: look at the output format.)

Modify it: Ask AI to split the total evenly between 2, 3, or 4 people. The program should ask "How many people?" and show each person's share.

Exercise 2 — Temperature Converter

temp_f = float(input("Enter temperature in Fahrenheit: "))
temp_c = (temp_f - 32) * 5 / 9
print(f"{temp_f}°F = {temp_c:.1f}°C")

Read it: What formula is being used? Does it match what you learned in school?

Modify it: Ask AI to also convert to Kelvin (K = C + 273.15) and display all three values.

Exercise 3 — Compliment Generator

import random

compliments = [
  "You're crushing it today.",
  "Your curiosity is contagious.",
  "You make hard things look easy.",
  "The world is better with you in it.",
  "You ask the best questions."
]

name = input("What's your name? ")
print(f"{name}, {random.choice(compliments)}")

Read it: What does random.choice() do? What would happen if the list had only one item?

Modify it: Ask AI to add 5 more compliments to the list and make it ask "Want another one? (yes/no)" after the first compliment, looping until the user says no.

Week 1 · Day 2