Advanced Prompt Engineering
Advanced Prompt Engineering teaches you to write prompts as specifications that work on the next hundred inputs, not just the one in front of you. You'll structure prompts with sections, delimiters, output schemas, examples, and guardrails, then break hard tasks into checkable steps with reasoning, critique loops, and scored options. Finally, you'll turn prompts into team systems: chains with human checkpoints, test sets and rubrics, versioned libraries, and layered defenses against invention and prompt injection.
Course details
Duration
1h 00m 50s
Lectures
15
Video
1 hour
Quizzes
1
Level
Beginner
Course Description
A prompt that works once for you is a habit. A prompt that works every time, for anyone on your team, is a tool. This course teaches the discipline that gets you from one to the other: structure the prompt, decompose the task, test the result, and share the asset.
What you'll learn
- Writing specifications instead of requests, and diagnosing a weak prompt by its missing part
- Sections, delimiters, explicit output schemas, and few-shot examples chosen for coverage
- Guardrails against invention: source-bound rules, fixed refusals, and missing-information fallbacks
- Reasoning prompts, task decomposition, critique-and-revise loops, and scored comparisons
- Prompt chains with human checkpoints, test sets, rubrics, and versioned team libraries
- Defending production prompts against drift, format breakage, and prompt injection
Who it's for
Professionals who already use AI assistants regularly and now write prompts that colleagues reuse, or that run on many inputs. No coding required.
15 short video lessons in three modules: Structure and Control; Reasoning and Decomposition; and Prompt Systems for Teams.
Module 1: Structure and Control
-
1.1 The Fundamentals, FastTask, context, format, constraints — a one-lesson refresher before the advanced material, with the mindset shift that makes the rest work.
In this lesson:
- Restate the four-part prompt structure
- Adopt the engineering mindset: prompts as specifications, not requests
- Diagnose a weak prompt by which part is missing
-
1.2 Structured Prompts
Sections, delimiters, and explicit output schemas — getting output you can parse, paste, or feed to the next step.
In this lesson:
- Organize a prompt into labeled sections with delimiters
- Specify an output schema the model will follow
- Explain why structure improves reliability on varied inputs
-
1.3 Examples That Teach the Pattern
Few-shot prompting: choosing examples, ordering them, and when they backfire.
In this lesson:
- Add input–output examples to a prompt to teach a pattern
- Choose and order examples for coverage
- Recognize when examples hurt more than help
-
1.4 Constraints and Guardrails in the Prompt
What to include, what to refuse, how to handle missing information — "say 'not found' rather than guess."
In this lesson:
- Write constraints that prevent invention and scope creep
- Define refusal and fallback behavior explicitly
- Handle missing information with a stated behavior instead of a guess
-
1.5 Controlling Length, Tone, and Certainty
Precise instructions for register, hedging, confidence labels, and citations — the dials that make output fit its use.
In this lesson:
- Control length with numbers, not adjectives
- Specify tone and register precisely
- Require confidence labels and citations in the output
Module 2: Reasoning and Decomposition
-
2.1 Asking for the Reasoning
Step-by-step and show-your-assumptions techniques — when they help, and when they add noise.
In this lesson:
- Elicit step-by-step reasoning before an answer
- Surface the assumptions behind an output
- Judge when reasoning prompts help and when they just add length
-
2.2 Decomposing Hard Tasks
Outline, then sections; analyze, then recommend — the prompt sequence for complex work.
In this lesson:
- Break a complex task into a sequence of single-purpose prompts
- Carry context forward between steps without losing it
- Recognize tasks that fail as one prompt and succeed as several
-
2.3 Self-Critique and Revision Loops
Asking the model to critique and improve its own output, with a stopping rule that prevents endless polishing.
In this lesson:
- Run a critique-then-revise loop with explicit criteria
- Set a stopping rule for the loop
- Recognize when self-critique produces real improvement versus cosmetic change
-
2.4 Comparing Alternatives
Generating options, scoring them against criteria, and choosing with the reasoning visible.
In this lesson:
- Generate genuinely different options rather than variations
- Score options against weighted criteria in a table
- Keep the final choice with a person, informed by the scoring
-
2.5 Handling Long Inputs
Chunking, summarizing in stages, and keeping instructions in view across a long session.
In this lesson:
- Chunk long inputs at natural boundaries and process them consistently
- Use staged summarization without losing detail
- Keep instructions effective across long conversations
Module 3: Prompt Systems for Teams
-
3.1 Prompt Chains and Workflows
Output of one prompt as input to the next — designing the chain, and where a human checks.
In this lesson:
- Design a multi-prompt chain with defined interfaces between steps
- Place human checkpoints where errors would compound
- Document a chain so someone else can run it
-
3.2 Testing Prompts
A small test set, a scoring rubric, and comparing versions before rolling one out.
In this lesson:
- Build a test set that covers typical, edge, and adversarial inputs
- Score prompt output with a rubric
- Compare two prompt versions on evidence instead of impression
-
3.3 Prompt Libraries and Templates
Naming, versioning, documenting, and retiring prompts a team shares.
In this lesson:
- Structure a shared prompt library with ownership and versions
- Write a prompt template with clear variables and a header
- Maintain the library: review, retire, and change control
-
3.4 Failure Modes and Robustness
Invention, drift, injection through pasted content — and the defensive patterns for each.
In this lesson:
- Name the four failure modes that affect production prompts
- Apply a defensive pattern to each
- Test for prompt injection with adversarial inputs
-
3.5 The Prompt Engineer's Practice
Structure, decompose, test, share — the checklist and your first team prompt; the finale.
In this lesson:
- Recall the four-part practice and the course's core patterns
- Apply the production-prompt checklist
- Complete Advanced Prompt Engineering
Advanced Prompt Engineering — Final Exam
Learn at your own pace
Study the materials at your convenience, you can always return to them to repeat
Certificate of completion
Complete every lesson and pass the final exam to earn a RiseCert certificate of completion you can download and share.
Your Name
Advanced Prompt Engineering
RISECERT
CERTIFICATE
For demonstrated knowledge and successful completion of all course requirements for:
MM.DD.YYYY
Certificate Date
Ready to get started?
Enroll in Advanced Prompt Engineering and earn your RiseCert certificate of completion.
Got Questions? We've Got Answers!
Answers to the most common questions about this course.
What is the Advanced Prompt Engineering course?
Advanced Prompt Engineering is a RiseCert online course that teaches you to build prompts other people can rely on: structured, tested, documented, and shared. It covers output schemas, examples, guardrails, reasoning and decomposition, prompt chains, test sets, prompt libraries, and injection defenses across 15 video lessons (about an hour) and a final exam.
Who should take an advanced prompt engineering course?
Professionals who already use AI assistants and now write prompts that colleagues reuse or that run on many inputs, such as classifying tickets, extracting invoice fields, or summarizing meetings. It suits team leads, analysts, operations staff, and anyone asked to make a team's AI use consistent. Every technique is taught in plain language with workplace examples.
What is prompt engineering, and how is it different from just asking AI a question?
Prompt engineering is the discipline of writing prompts as specifications rather than requests. A request like "help me summarize this" hopes the model guesses right. A specification states the task, context, output format, and constraints, including what to do when unsure, so the prompt works on the next hundred inputs, not just this one.
What is few-shot prompting?
Few-shot prompting means including a small number of input-output examples in a prompt so the model learns the pattern by imitation. Advanced Prompt Engineering recommends two to five examples in an identical format, chosen for coverage: a typical case, a tricky edge case, and an empty or "not found" case, with synthetic data and balanced labels.
How do you stop an AI prompt from making things up?
Write constraints that bind the model to its input. The course teaches source-bound rules (use only the supplied text), a stated fallback such as "not found" or null for missing values, quoting numbers exactly, and citing the input sentence behind each claim. Then test the rule with an input that is deliberately missing something.
What is prompt injection, and how can a prompt defend against it?
Prompt injection happens when pasted content, such as an email, contains instructions the model follows as if they came from you. The course teaches layered defenses: delimit input and declare it data, add a scope rule with a fixed refusal, use a strict output schema, include adversarial test inputs, and put a person before any action.
How do you test a prompt before a team uses it?
Build a test set of 15 to 25 inputs, about half typical, a quarter edge cases, and a quarter adversarial, each with an expected output. Score every run with three to six binary rubric criteria such as format, correctness, grounding, scope, and length, then compare prompt versions on the scores and fix regressions before rollout.
Do I need coding skills or technical training to take this course?
No. Advanced Prompt Engineering requires no coding. It assumes you already use an AI assistant regularly and are comfortable writing basic prompts; the first lesson recaps the fundamentals quickly. Concepts such as JSON output schemas are explained with plain examples, and every technique can be applied in an ordinary chat assistant.
How is advanced prompt engineering different from basic prompting tips?
Basic tips help one person get a better answer once. This course is about prompts that run reliably across many inputs and many users: explicit schemas, fallbacks, decomposed workflows, critique loops with stopping rules, test sets and rubrics, version control, and defenses against drift and injection. The goal is a tested team tool, not a lucky result.
What will I be able to do after completing the course?
You'll be able to write structured prompts with schemas and guardrails, choose few-shot examples, decompose complex tasks, run critique-and-revise loops, and score alternatives. You'll also design prompt chains with human checkpoints, build test sets and rubrics, maintain a versioned prompt library, and apply a production-prompt checklist before anything goes live.
Which AI tools does the course teach?
The course is tool-neutral. The techniques, including structure, examples, constraints, decomposition, testing, and libraries, apply to the general-purpose AI assistants and chat tools most workplaces use, and no specific product is required or endorsed. Where a tool supports system or custom instructions, the course shows how to use them for standing rules.
Is the course content up to date?
Yes. Advanced Prompt Engineering focuses on durable practices rather than tricks tied to one model, and it plans for change: prompts carry versions and test sets, and the course teaches you to re-test every active prompt whenever the underlying AI model is updated, because behavior can shift silently between versions.
How long does the Advanced Prompt Engineering course take?
The course has about an hour of video across 15 lessons, plus a final exam. Lessons run about four minutes each and are organized into three modules: Structure and Control; Reasoning and Decomposition; and Prompt Systems for Teams. Most learners finish in one or two sittings.
Is the course online and self-paced?
Yes. Advanced Prompt Engineering is 100% online and self-paced, and your access does not expire. You can start, pause, and resume at any time on a computer, tablet, or phone with a modern web browser. There's nothing to install.
Is there a final exam?
Yes. The course ends with a 30-question multiple-choice final exam covering all three modules. You need a score of 80% or higher (24 of 30) to pass, and you can retake the exam as many times as you need. Finish all 15 lessons and pass the exam to complete the course.
Do I get a certificate of completion?
Yes. After you complete all 15 lessons and pass the final exam, you can download a RiseCert certificate of completion from your account. It is a course completion certificate, not a license, a professional certification, or a continuing education certificate.
Does the course count for continuing education (CE) credit?
No. Advanced Prompt Engineering is not currently approved or accredited for continuing education credit (CE, CPE, or CEU) by any state, licensing body, or professional association. If you need credit hours for a license or certification, take a course approved by the body that issues it.
Is this course technical, legal, or security advice?
No. The course is educational. It teaches prompt-design practices that make AI output more reliable and reduce risks like invention and prompt injection, but it can't guarantee results for any specific tool or use. Your employer's AI policy and data rules govern what you may share with AI tools and how prompts are used.
How much does the course cost, and can I enroll my team?
The course costs $99 per learner as a one-time purchase, with no subscription or recurring fees. To enroll a team or organization, contact RiseCert through the Contact Us page at risecert.org.
Can I get a refund?
No. All sales are final and no refunds are issued, per the RiseCert Terms of Use. Before you buy, review the course description, the lesson list, and these FAQs to confirm Advanced Prompt Engineering fits your needs, or contact RiseCert with questions through the Contact Us page at risecert.org.