You’re Using AI Wrong (and How to Fix It)

How to Stop Wasting Time with AI and Start Getting Results

What you'll learn
- Understand how language models like ChatGPT and GPT-4 generate responses using token prediction, probability, and model settings like temperature.
- Think like the model to craft effective prompts and influence AI behavior with greater control and precision.
- Apply advanced prompt engineering techniques, including chain-of-thought reasoning, context management, and system prompt manipulation, to get better, more cons
- Diagnose and fix poor AI outputs by identifying hallucinations, drift, bias, and other common failure modes—and intelligently repairing prompts.
- Use AI effectively across real-world tasks like content creation, data analysis, and code generation, with minimal supervision.
- Collaborate with AI systems in a human-in-the-loop workflow, knowing when to lead, when to intervene, and how to guide the model during execution.
- Develop an AI-first mindset that moves beyond trial and error—toward intentional, structured, and strategic interaction.
- Access reusable prompt templates, debugging checklists, and expert resources to continue growing beyond the course.

Requirements
- A basic curiosity about how AI works, no technical background needed
- Comfort using tools like ChatGPT, Claude, or Gemini (even casually)
- A willingness to experiment and improve through hands-on practice
- No coding required, just clear thinking and a bit of patience

Description
Most people use AI like a search engine — then wonder why the answers are vague, wrong, or just plain weird.

This course teaches you how to use AI the right way — with strategy, structure, and intention. You’ll learn how to write better prompts, debug broken outputs, guide the model’s reasoning, and collaborate like a pro. Whether you're creating content, analyzing data, coding tools, or automating workflows, you'll stop guessing and start engineering smarter interactions.

We go beyond the basics. You’ll explore real-world tactics like chain-of-thought prompting, red teaming, prompt repair, and human-in-the-loop workflows. You’ll learn how to avoid AI hallucinations, spot hidden bias, and build systems that blend human judgment with AI speed.

You’ll also get hands-on practice with interactive assignments, downloadable tools, and ready-to-use prompt templates you can apply immediately. Whether you’re a beginner or an experienced user, this course meets you where you are — and levels you up fast.

If you’ve ever asked an AI for help and gotten a generic, useless, or risky response — this course will show you exactly why that happened, and how to fix it. You’ll start thinking like a model engineer — someone who doesn’t just use AI, but shapes it.

By the end, you’ll be confident designing AI interactions that actually work — and trusted as the person in the room whoknows how to use AI right.

Who this course is for:
- You’ve used ChatGPT, Claude, Gemini, or any AI chatbot and felt frustrated with vague, repetitive, or wrong answers.
- You’re a content creator, marketer, writer, or freelancer who wants AI to generate clearer, more tailored, and higher-quality content.
- You’re a professional or team member using AI in your workflow—from drafting emails to analyzing data—and want more accuracy and reliability.
- You’re a teacher, coach, or communicator who explains or demonstrates AI and wants to make it behave more consistently and transparently.
- You’re a developer, product manager, or tech enthusiast curious about how prompting really works under the hood—without diving into complex code.
- You’re tired of trial-and-error prompting and want to understand how to guide AI intentionally and intelligently.
- You want to learn how to “think like the model” so you can get exactly what you need, faster and with less guesswork.
- You’re building AI products or workflows and need to troubleshoot poor results, hallucinations, or unpredictable behavior.
- You’ve never formally studied AI, but you’re ready to go beyond surface-level tips and learn how AI actually “thinks” and why it fails.
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