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AI Prompt Engineering Mastery: Prompts, Workflows and Beyond

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Design powerful prompts, solve complex problems, build workflows, and use ethical guardrails for reliable results.
4.3
4.3/5
(75) Ratings
1,142 students
Created by Piet @ Learnya Skills
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What you'll learn

  • Apply a structured framework to turn vague AI prompts into clear, high‑quality instructions for real work tasks.
  • Design effective prompts using role, context, examples, and output format to reliably control AI responses.
  • Use advanced techniques like chain‑of‑thought, multi‑turn dialogue, and decomposition to solve complex problems with AI.
  • Build and maintain a personal prompt library and templates that speed up recurring tasks across your own workflows.
  • Create AI‑enhanced workflows for tasks like research, writing, analysis, or planning and compare before/after time and quality.
  • Define and use personalized AI “assistants” with consistent roles, styles, and response patterns for your domain.
  • Identify and mitigate AI bias, privacy risks, and unsafe outputs using ethical prompt design and testing checklists.
  • Evaluate AI models and prompts with clear quality metrics, then refine them using systematic testing and feedback loops.
This course includes:
44 total mins on-demand video
0 articles
5 downloadable resources
5 lessons
Full lifetime access
Access on mobile and TV
Certificate of completion
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Course content

Requirements

  • This course is designed to be accessible and practical. You do not need a technical or coding background. Learners should have: Basic computer and internet skills Comfortable using web apps, copy–paste, typing, and managing documents. Access to at least one modern AI tool e.g. ChatGPT, Claude, Gemini, Copilot, or a similar chat‑based AI assistant. Regular or intended AI use You already use AI occasionally or plan to use it for work, study, or projects. Good written English Able to read and write clear instructions in English. Helpful but not required: Experience with knowledge work (writing, analysis, teaching, planning, coding, content creation) will make examples feel immediately relevant. No math, programming, or prior prompt engineering knowledge is required. This course starts from foundations and builds up step‑by‑step.

Description

This course contains the use of artificial intelligence

You already know that short, vague prompts give you short, vague answers. In this free course, you turn that guesswork into a clear, repeatable prompt engineering system you can trust in your day‑to‑day work. You learn how modern language models interpret your prompts, how to shape their responses on purpose, and how to turn individual prompts into full workflows that save you time and improve quality.

You start with foundations: how models process text, why clarity, context, constraints, and consistency matter, and how to transform weak prompts into strong ones using a simple design framework.

You then move into essential techniques, where you structure prompts with roles, audience, output formats, and examples, and begin building reusable templates and a personal prompt library tailored to your tasks.

Next, you step into advanced problem solving. You use chain‑of‑thought reasoning, multi‑step dialogues, task decomposition, and prompt debugging to handle complex, high‑stakes work across writing, analysis, coding, and creative projects. You see exactly how to make reasoning visible, fix poor outputs, and adapt prompts to different domains.

From there, you focus on productivity. You turn isolated prompts into end‑to‑end workflows, design simple AI‑assisted collaborators for your role, and integrate prompts into everyday activities like research, planning, documentation, teaching, and content creation. You track time saved and quality gains so you can show real impact, not just interesting experiments.

Finally, you embed ethics and responsibility into your practice. You learn practical ways to reduce bias and unsafe outputs, protect privacy in your prompts, test workflows for reliability, and keep your approach up to date as tools and techniques evolve.

By the end of this free, practical course, you will be able to design stronger prompts, build reliable workflows, and use powerful tools with confidence and integrity in your real work.

Who this course is for:

  • This course is designed for motivated professionals and educators who already use (or want to use) AI tools like ChatGPT, Claude, Gemini, or Copilot and now want to get serious, reliable, and ethical results from them. You’ll get the most value if you are: Knowledge workers and professionals Analysts, consultants, managers, ops specialists, HR, and general “office athletes” who want to use AI for writing, research, planning, documentation, and decision support—without wasting time on hit‑or‑miss prompts. Educators, trainers, and learning designers Teachers, lecturers, facilitators, and instructional designers who want to integrate AI into lesson design, content creation, assessment ideas, and learner support, while keeping quality and ethics front and center. Content creators and marketers Writers, bloggers, social media managers, and marketing professionals who need structured prompts, reusable templates, and prompt libraries to produce on‑brand, high‑quality content faster. Developers, data/BI analysts, and technical professionals People who work with code, data, documentation, or technical research and want to use AI for scaffolding, explanation, refactoring, analysis, and idea generation—without losing control over quality. Team leads and change agents Managers, project leads, and internal champions who are responsible for bringing AI into their team’s workflows and want a clear, ethical, and repeatable approach to doing that. You are a good fit if: You are comfortable with basic digital tools and can write clear sentences in English. You already use AI sometimes or are ready to start using it regularly for real work. You care about quality, consistency, and ethics, not just flashy AI demos. This course is not designed for: People looking for AI model building or deep machine learning theory. Those who want a purely technical coding course in Python, ML, or data science. If you want to turn AI from a “black box that sometimes works” into a reliable partner embedded in your daily workflows, this course is built specifically for you.
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