Who this course is for
Beginners, writers, analysts and team members who want a repeatable way to brief AI and evaluate its responses.
beginner · Self-paced course
Prompt Engineering Foundations
Write clearer prompts, evaluate results, and build reliable AI workflows.
Learn prompt engineering with clear instructions, context, examples and output checks. Study at your pace and earn a Kendr Academy completion certificate.
Free
Learn on your schedule.
Save your progress as you go.
About this course
Learn a repeatable method for turning an unclear request into a prompt that an AI can follow and you can evaluate. Each module combines short readings, expert videos, worked examples, and hands-on practice.
What you’ll be able to do
- Turn an outcome into a clear instruction and success criteria.
- Add context and examples without overwhelming the model.
- Evaluate outputs systematically and improve a prompt through testing.
- Design reusable prompts for research, writing, analysis, and team workflows.
What you need before you start
No coding or previous prompt engineering experience is required. Bring a writing, research or analysis task you want to improve.
Course syllabus
MODULE 01Start with a clear task
Understand what a prompt controls and turn intent into an instruction.
3 lessons + module assessment
- 1. What a prompt actually does
Learn the difference between a goal, an instruction, and the information the model needs.
7 minutes · Reading and practice - 2. The anatomy of a strong prompt
Use task, context, constraints, and output format as a reusable structure.
10 minutes · Reading and practice - 3. Define success before asking
Turn a vague preference into criteria you can inspect.
8 minutes · Reading and practice
MODULE 02Add the right context
Ground the model with evidence, examples, and a useful output contract.
3 lessons + module assessment
- 1. Context without clutter
Decide what the model needs and keep evidence distinct from instructions.
9 minutes · Reading and practice - 2. Teach with examples
Use demonstrations when instructions alone leave room for interpretation.
11 minutes · Reading and practice - 3. Design the output
Ask for a response that is easy to inspect and use in the next step.
9 minutes · Reading and practice
MODULE 03Test and improve
Move from a clever prompt to a reliable workflow through evaluation.
3 lessons + module assessment
- 1. Iterate with evidence
Change one thing at a time and compare results against fixed criteria.
10 minutes · Reading and practice - 2. Common failure modes
Recognize ambiguity, instruction conflict, weak evidence, and overfitting.
10 minutes · Reading and practice - 3. Capstone: build a prompt workflow
Combine the course method into a prompt you can test and reuse.
15 minutes · Reading and practice
Final assessment
Apply what you’ve learned to practical scenarios. Pass with 85% or higher after completing the required lessons and module assessments.
What you’ll practice
- Rewrite a vague request as a clear task with success criteria.
- Add source material, constraints and examples to a reusable prompt.
- Test outputs against a rubric and improve a prompt through iteration.
Follow the worked examples, complete the exercises and review your own work before attempting each assessment.
Free lesson preview: What a prompt actually does
What a prompt actually does
A prompt is the information available to a model when it produces its next response. It can contain a task, background information, examples, constraints, source material, and the conversation so far.
Prompting is specification
Treat a prompt as a small specification. You are describing an outcome clearly enough that another capable person could attempt it without guessing what you meant. A useful prompt answers four questions:
- What should be produced?
- Who is it for?
- What information should be used?
- What would make the result acceptable?
Compare “write about our launch” with “write a 120-word email for existing customers announcing offline mode; explain the benefit in the first sentence and end with a link to the release notes.” The second prompt reduces ambiguity while leaving room for good writing.
More words are not automatically better
Extra detail helps only when it changes the desired result. Remove background that does not affect the answer. Keep the task, relevant context, and evaluation criteria easy to find.
Before sending a prompt, ask: if the response were wrong, which missing instruction would explain the failure? Add that instruction rather than adding a long preamble.
Frequently asked questions
What will I learn in a prompt engineering course?
You will learn to specify a task, supply relevant context, use examples and output formats, and evaluate an AI response against explicit criteria. The course applies these techniques to practical writing, research and analysis tasks.
Do I need to know how to code?
No. The exercises focus on writing instructions and evaluating responses, so you can begin without programming experience.
How does this differ from a list of prompt templates?
The lessons explain why a prompt works and how to adapt and test it. You practice defining success criteria and revising a prompt when its output misses the task.
Is the course free and self-paced?
Yes. You can read the public syllabus without an account and enroll for free using your Kendr account. The course includes 9 lessons across 3 modules, with about 89 minutes of reading and practice, plus assessments. Your learning progress is saved to your account.
How do I earn a certificate?
Complete all required lessons, pass each required module assessment at 75% and the final assessment at 85%, meet the minimum study period of 1 calendar day(s), and claim your certificate with your full name and a verified email. Kendr Academy issues a downloadable course completion certificate with a public verification link. It does not confer professional accreditation.