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Prompt Engineering for AI Mastery

Prompt Engineering for AI Mastery

Strong prompting skills for clear and reliable AI output
Created byAsibeh Tenager
Last updated 12/2025
English

What you'll learn

  • Understand how AI language models work and how prompts shape their behavior
  • Create effective prompts for a wide range of practical tasks
  • Use advanced prompting techniques to improve accuracy and solve complex problems
  • Build real AI workflows, templates, and projects they can use in daily work

Course content

2 sections • 8 lectures • 46m total length

  • Introduction to Generative AI4:51

    By the end of this lecture, you will be able to define Generative AI, understand the core mechanism of Large Language Models (LLMs), and appreciate the non-deterministic nature of their output.

  • Why Prompt Engineering Matters8:13

    By the end of this lesson, you will be able to:

    • Understand why prompt quality directly shapes the accuracy and relevance of AI outputs

    • Identify the common reasons weak prompts fail

    • Explain how a clear structure improves an AI model’s focus and reliability

    • Apply the prompt-engineer mindset to build consistency through iteration and refinement

  • The Anatomy of an Effective Prompt7:53

    By the end of this lesson, you’ll be able to:

    • Recognize the elements that make a prompt effective

    • Use the Core Four Framework for any AI task

    • Remove ambiguity by adding the right context

    • Shape the model’s tone, depth, and style through persona

    • Guide the output format so it matches what you need

    • Transform vague prompts into strong, structured ones

  • Summary0:51
  • Section 1 — End-of-Section Quiz

Requirements

  • Basic computer skills
  • Curiosity about AI and how it works
  • Access to an AI tool such as ChatGPT, Claude, Gemini, or similar
  • Some experience with writing, coding, or problem-solving(Optional)

Description

This course provides a clear introduction to the principles and practice of prompt engineering. It aims to help learners understand how large language models interpret instructions and how careful prompting can improve the clarity, accuracy, and consistency of AI-generated output.

We start by looking at the basics of generative AI and the factors that affect model behavior. Then, the course presents the Core Four framework: Instruction, Context, Persona, and Format. This framework is a practical way to design effective prompts for various tasks.

Learners will examine examples of weak and strong prompts, revise them through guided steps, and use techniques like Chain-of-Thought reasoning and few-shot prompting. The course also covers prompt templates, refining prompts, and applying prompts in real-world scenarios, such as coding help, text generation, summarization, and creative projects across multiple domains.

Throughout the course, short exercises and demonstrations show how slight changes in wording can greatly influence model output. By the end, learners will understand how to create purposeful prompts and use them effectively in academic, professional, and technical settings.

This course provides a solid yet approachable foundation for anyone looking to work with AI more precisely and informed, offering practical skills that support confident, adaptable, and sustainable practice.

Who this course is for:

  • Beginners curious about AI
  • Professionals who want to boost productivity
  • Creators and business owners
  • Students and career changers entering the AI field

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