Home › Courses › Prompt Engineering Mastery

Prompt Engineering Mastery

Get dramatically better results from any AI, for work or your side hustle

10 phases. 47 lessons. 47 practice reps. 4 projects. No code, no math, no jargon left unexplained. Learn the craft of talking to AI — ChatGPT, Claude, Gemini, Midjourney, Sora, Cursor, GitHub Copilot — through plain English, real before/after examples, and hands-on practice on your own real tasks. You finish with a prompt portfolio you can show anyone.

10 phases · 47 lessons · 47 practice reps · 4 projects

No prerequisites — this is a starting track.

Outcomes you will have by the end

• Prompt Makeover Portfolio — 5 real prompts you used badly, rewritten and tested, with before/after documentation showing exactly what changed and why the new version works better.
• AI Research Partner Workflow — A documented, repeatable process for researching a real decision using AI — prompts, outputs, verification steps, and the final decision you reached.
• Visual Campaign with Style Guide — A consistent set of AI images or a short video produced from a style guide you wrote and tested yourself. Shows you can control visual output, not just get lucky.
• Personal Prompt Library & Case Study — A polished, categorized library of your best prompts plus one full before/after case study you could show in a job interview or use as a freelance work sample.
• 47 Practice Reps on Real Tasks — Every lesson includes a practice rep where you apply the technique to your own real work — not a canned exercise. You build the muscle memory of someone who actually uses this daily.
• AI Fluency That Shows Up Everywhere — Not a certificate that says you watched videos — a portfolio of real before/after work that proves you can get dramatically better output from any AI tool.

What you will be able to do

Prompt Engineering · AI Fluency · ChatGPT · Claude · Gemini · Cursor · GitHub Copilot · Image/Video Prompting · AI Workflows

Every phase, every lesson, every project

• How AI Actually Reads Your Words (4 lessons) — free — Mental model of how AI processes text, tokens and context windows, temperature, anatomy of a great prompt, zero-shot vs few-shot
  • The Prediction Engine Mental Model
  • Tokens, Context Windows & Temperature
  • Anatomy of a Great Prompt
  • Telling vs. Showing: Zero-Shot and Few-Shot
• The Core Prompting Toolkit (5 lessons) — free — Being specific, giving context, role/persona prompting, few-shot examples, output format, positive instructions, iteration, breaking big asks into steps, asking AI to clarify before answering
  • Be Specific, Give Context
  • Role & Persona Prompting
  • Show Examples, Ask for a Format
  • Iterate, Break It Up, Ask It to Clarify
  • Project 1: Prompt Makeover Portfolio
• Thinking & Reasoning Techniques (5 lessons) — Chain-of-thought, reasoning models vs standard chat models, multiple approaches, self-critique, devil's advocate, cross-model comparison
  • Chain-of-Thought: Show Your Work
  • Reasoning Models vs. Standard Chat Models
  • Multiple Approaches & Self-Critique
  • Devil's Advocate & Stress-Testing
  • Cross-Model Comparison
• Writing & Content With AI (5 lessons) — Drafting vs editing prompts, tone and voice control, avoiding AI voice, long-document work, personalizing at scale, editing prompts with writing samples
  • Drafting vs. Editing Prompts
  • Tone & Voice Control
  • Avoiding 'AI Voice'
  • Long-Document Work: Summarize, Outline, Restructure
  • Personalizing Content at Scale
• Research, Analysis & Decision-Making (5 lessons) — Summarizing and extracting structured info, comparing options with structured prompts, AI as thinking partner, spotting hallucinations, web-connected AI tools, turning messy info into clean output
  • Summarizing & Extracting Structured Info
  • Comparing Options with Structured Prompts
  • AI as a Thinking Partner
  • Spotting Hallucinations & Using Web-Connected AI
  • Project 2: AI Research Partner Workflow
• Building & Coding With AI (No-Code Friendly) (4 lessons) — Vibe coding, describing what you want built, plan-first-then-build habit, debugging by pasting errors, agents vs chat, standing context files, AI coding assistants (Cursor, GitHub Copilot), @-mention context pointing, .cursorrules and project instructions, inline edit vs agent mode, constraints and acceptance criteria
  • Describing What You Want Built
  • Plan First, Then Build
  • Debugging by Pasting Errors
  • Standing Context Files
• Image, Video & Voice Prompting (5 lessons) — Image prompt anatomy (subject, composition, lighting, style, mood), video prompt anatomy (subject, action, environment, camera, style, duration), negative prompts, style consistency, voice/audio generation, multi-tool pipelines
  • Image Prompt Anatomy
  • Video Prompt Anatomy
  • Negative Prompts & Style Consistency
  • Voice, Audio & Multi-Tool Pipelines
  • Project 3: Visual Campaign
• Building Your Own AI Tools (4 lessons) — Custom GPTs, Claude Projects, Gemini Gems, personal system prompts, reusable prompt templates, prompt library organization, chaining prompts into workflows
  • Custom GPTs, Claude Projects & Gemini Gems
  • Personal & Team System Prompts
  • Reusable Prompt Templates
  • Prompt Library & Workflow Chaining
• Traps, Judgment & Staying Current (5 lessons) — Hallucinations and why they happen, over-trusting AI in high-stakes situations, bias in AI output, what never to paste into a prompt, prompt injection basics, 10-minute tool evaluation framework
  • Why Hallucinations Happen
  • What Never to Paste & When Not to Trust AI
  • Bias in AI Output
  • Prompt Injection Basics
  • The 10-Minute Tool Evaluation Framework
• Turning the Skill Into Career Value (5 lessons) — AI fluency in job postings, building a prompt portfolio, freelancing and consulting rates, teaching/consulting for teams, staying current without burning out
  • AI Fluency in Job Postings & Interviews
  • Building Your Prompt Portfolio
  • Freelancing & Consulting: Rates and Gigs
  • Teaching & Team Playbooks
  • Staying Current & Capstone: Personal Prompt Library & Case Study

The technologies you will use

ChatGPT · Claude · Gemini · Cursor · GitHub Copilot · Perplexity · Midjourney · Sora · Veo · Runway · ElevenLabs · Custom AI Assistants

Roles this course prepares you for

• Freelance Prompt/AI Workflow Consultant ($50–$400/hr (varies by experience)) — Help individuals and small teams get more out of AI tools. Sell before/after audits, reusable prompt systems, and workflow setups. Market rates range from ~$50/hr for beginners to $200–$400/hr for specialists building evaluation frameworks.
• Marketer / Content Lead ($60k–$140k base) — Use AI daily for copy, campaigns, and content at scale. The skill shows up as speed and consistency — producing on-brand output in half the time, not as a job title.
• Executive Assistant / Chief of Staff ($55k–$120k base) — Increasingly expected to run research, drafting, and scheduling logistics through AI tools fluently. The best EAs are 3x faster because they know how to prompt.
• Small Business Owner / Solo Founder (Varies (cost savings + revenue)) — Use AI to replace tasks you'd otherwise need to hire for — content, research, customer support drafts, marketing visuals, and basic no-code builds.
• Customer Support Lead ($50k–$95k base) — Build and maintain AI-assisted response workflows and macros. Train the team on prompting standards so everyone gets consistent output.
• Product Manager ($110k–$200k base) — Write prompts as part of specifying and evaluating AI features. Bridges toward Course 2's c2-01 for anyone who wants to go deeper into engineering.
• Teacher / Trainer ($45k–$80k base) — Use AI to build materials, and increasingly need to teach students how to prompt responsibly. This course gives you the vocabulary and the lesson plans.
• Job Seeker (Any Field) (Varies) — "AI fluency" appears on job postings across nearly every function now. This course gives you the portfolio that proves it — real before/after work, not a certificate that says you watched videos.

What prompt engineering actually is in 2026

Prompt engineering is not a job title — it's a skill that shows up in almost every knowledge-worker role. The core practice is the same one this course teaches: state what you want clearly, give the AI enough context to be useful, show examples when words aren't enough, ask for a specific format, and iterate when the first answer isn't right. People who are good at this get dramatically better output from the same tools everyone else has access to. People who aren't leave huge amounts of quality on the table and don't even know it.

What you do every day

You write prompts for real tasks — emails, reports, content, research, visual assets. You iterate when the output isn't right, adjusting specificity, context, format, or examples until it is. You build reusable templates for tasks you do often. You use AI as a thinking partner for decisions, a research assistant for complex topics, and a drafting partner for content. You spot hallucinations before they cause problems. You stay current by spending 15 minutes a day scanning for new tools and techniques.

Why this skill matters now

AI fluency appears on job postings across nearly every function — marketing, ops, PM, support, consulting, design. Freelance prompt and AI workflow work ranges from $50/hr for beginners to $400/hr for specialists. The people who get hired, get promoted, and win clients are the ones who can demonstrate real before/after improvement, not the ones who list "ChatGPT" as a skill on their resume. This course builds the portfolio that proves it.

What this course is not

It is not an engineering course. There is no Python, no API calls, no model internals, no math. It is not a "100 ChatGPT prompts" listicle — it teaches the craft behind the prompts, so you can write your own for any task. And it is not a certificate mill — every practice rep and project produces something real you can show someone.

Common questions

Do I need to know how to code?

No. This course assumes nothing technical. If you can type into a chat box, you can start. There's no Python, no API calls, no terminal. Everything happens in ChatGPT, Claude, Gemini, Midjourney, or whatever AI tool you already use.

How is this different from the prompt engineering lessons in Course 2?

Course 2's c2-01-advanced-prompt-engineering teaches engineers to write prompts inside production LLM applications — system prompts in code, temperature parameters, structured JSON outputs for pipelines. This course teaches the same underlying craft to everyone who isn't going to open an API. Same skill, different audience: the 99% of people who use AI through a chat box.

Is "prompt engineer" even a real job anymore?

The standalone job title has largely folded into broader AI/product roles, but the skill shows up everywhere — marketing, ops, PM, support, consulting. This course doesn't pretend the job title exists. It teaches the skill and shows you where it actually shows up in the market, with real freelance rate data ($50–$400/hr depending on experience).

What tools do I need?

A free ChatGPT, Claude, or Gemini account is enough to start. Later phases reference Midjourney, Sora, and other tools, but every phase includes free-tier alternatives. Total tool cost to complete the course: $0–$20/month.

How long does this course take?

25–35 hours total. Most learners finish in 3–5 weeks at 5–7 hours per week. The unit of progress here is "a technique you now use," not "a system you built" — so it's intentionally lighter than the engineering courses.

Are there quizzes?

Minimal. This course is about doing, not testing. Every lesson has a Practice Rep where you apply the technique to your own real work — an actual email, an actual task, an actual image idea — and compare the before/after. The only measure of success is better output.

What if the tools change after I take the course?

The course explicitly teaches how to evaluate any new AI tool in 10 minutes and how to tell when a technique has gone stale. The core moves (be specific, give context, show examples, ask for a format) work everywhere and won't change. The tool-specific details are separated from the timeless principles so the course stays useful.

Can I take this alongside the engineering courses?

Yes. This course has no prerequisites and doesn't overlap with the engineering content. Many students take both — the engineering track for depth and this track for practical fluency in everyday AI use.

Key terms in this course

Prompt Engineering · Agent · Chain of Thought (CoT) · Perplexity · Prompt Injection · Temperature · Zero-Shot

Start the Prompt Engineering Mastery course

Create a free account — the opening phases of 24 of 30 courses are free, no credit card. Or see Pro pricing.

All courses · Pricing · About · FAQ · Glossary