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Prompt Engineering Basics is now open for enrollment.

Learn to write clear, effective prompts and get consistently better results from generative AI. Six hands-on sessions, real exercises, and a portfolio you leave with — built for professionals, students, and teams just getting started with AI.

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Prompt Engineering Basics is our first course open for enrollment. More courses are rolling out from the same curriculum.

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Prompt Engineering Basics

Write effective prompts and get better results from AI.

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Featured course

Prompt Engineering Basics

A beginner-level course for professionals, students, educators, content creators, and anyone beginning to work with generative AI.

Level Beginner
Duration 6 sessions × 2 hrs (12 hrs)
Format Instructor-led + hands-on
Audience Professionals & teams
What you'll learn

Learning objectives

By the end of the course, participants will be able to:

✓Explain what prompt engineering is and why it matters.
✓Understand how generative AI and large language models respond to prompts.
✓Write clear, specific, and effective prompts.
✓Use roles, context, constraints, examples, and output formats.
✓Apply common prompting techniques such as zero-shot and few-shot prompting.
✓Improve weak prompts through systematic iteration.
✓Identify hallucinations, ambiguity, and other common AI-output problems.
✓Create reusable prompts for everyday professional tasks.
✓Apply basic responsible-AI and privacy principles when prompting.
Session by session

Course outline & schedule

Session Topic Key concepts Practical activity
01 Introduction to Generative AI & Prompt Engineering What is generative AI? LLM basics, prompts vs. instructions, how AI interprets requests Compare vague vs. effective prompts
02 Anatomy of a Good Prompt Task, context, role, constraints, audience, tone, output format Build prompts using a prompt framework
03 Prompting Techniques Zero-shot, few-shot, role prompting, delimiters, step-by-step reasoning, structured outputs Solve the same task using different techniques
04 Prompt Improvement & Iteration Common prompt failures, ambiguity, missing context, refining prompts, evaluating outputs "Fix the prompt" workshop
05 Practical Prompt Engineering Writing, summarization, analysis, brainstorming, research assistance, data extraction Create prompts for real-world scenarios
06 Advanced Basics, Responsible AI & Final Project Prompt chains, reusable templates, hallucinations, verification, privacy, bias, responsible use Build and present a mini prompt library

Recommended teaching principle: the course runs approximately 30% theory and 70% hands-on practice.

Capstone

Final project

Personal Prompt Toolkit

Participants leave with a working toolkit of 5–10 reusable prompts relevant to their own work or studies — a portfolio piece, not just a certificate.

  1. Purpose — what task does it solve?
  2. Prompt — the actual instruction.
  3. Context — what information must be provided?
  4. Expected output — what should the AI produce?
  5. Example output
  6. Improvement notes — how could the prompt be refined?
Grading

Assessment

Participation and exercises 20%
Prompt improvement exercises 20%
Practical assignments 20%
Final Personal Prompt Toolkit 40%
Seats are limited — secure yours now and start writing better prompts in your very next session.
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