Advanced Prompt Engineering for Everyone Course

Lesson 1 • Anatomy of a Well-Formed Prompt

Breaks a prompt into its functional components: instruction, context, input data, and output format. Establishes a shared vocabulary used throughout the course.

Lesson 2 • Common Prompt Failure Modes

Catalogs the most frequent causes of poor model output: ambiguity, over-constraint, and missing context. Teaches diagnostic thinking before introducing fixes.

Lesson 3 • Setting Up a Practice Environment

Guides learners through selecting and configuring a model interface for hands-on exercises. Ensures every student can test prompts immediately after each lesson.

Lesson 1 • Instruction Tuning and Formatting

Explores how formatting choices—lists, headers, JSON—shape model output structure. Teaches systematic formatting decisions tied to downstream use cases.

Lesson 2 • Zero-Shot Prompting Strategies

Teaches how to elicit accurate responses without examples by optimising instruction phrasing. Demonstrates when zero-shot is sufficient and when it falls short.

Lesson 3 • Iterative Prompt Refinement

Introduces a structured edit-test-evaluate loop for improving prompts systematically. Builds the habit of evidence-based iteration over intuitive guessing.

Lesson 4 • Role and Persona Prompting

Assigns expert personas to shift model tone, depth, and domain focus. Connects persona design to audience needs and task requirements.

Lesson 1 • Zero-Shot Chain-of-Thought Triggers

Demonstrates trigger phrases that activate reasoning without examples. Compares trigger effectiveness across task types using controlled experiments.

Lesson 2 • Few-Shot Chain-of-Thought Design

Builds annotated reasoning examples that teach the model a problem-solving pattern. Covers example diversity and step granularity for robust generalisation.

Lesson 3 • Self-Consistency and Voting Strategies

Generates multiple reasoning paths and aggregates answers to reduce variance. Applies majority-vote logic to improve reliability on high-stakes outputs.

Lesson 4 • Applying Reasoning Prompts to Real Tasks

Transfers CoT techniques to business analysis, troubleshooting, and decision support. Reinforces chapter skills through domain-specific practice scenarios.

Lesson 1 • Conditional and Branching Chains

Introduces logic gates that route workflow paths based on model output content. Enables adaptive pipelines that respond to variable inputs.

Lesson 2 • Workflow Orchestration Tools Overview

Surveys no-code and low-code tools for building and deploying prompt chains. Connects workflow design concepts to practical implementation environments.

Lesson 3 • Error Handling in Prompt Pipelines

Builds validation checkpoints and retry logic into multi-step workflows. Prevents silent failures from propagating through downstream chain steps.

Lesson 4 • Designing Sequential Prompt Chains

Teaches how to pass structured outputs from one prompt as inputs to the next. Covers data formatting contracts between chain steps.

Lesson 1 • Guardrails and Behavioural Constraints

Embeds safety, scope, and tone constraints directly into system prompts. Teaches constraint layering to prevent off-topic, harmful, or inconsistent outputs.

Lesson 2 • Memory Patterns for Long Sessions

Introduces external memory stores and in-prompt memory representations for extended interactions. Enables stateful behaviour beyond single-session context limits.

Lesson 3 • Injecting Dynamic Context

Covers techniques for inserting retrieved or computed data into prompts at runtime. Connects context injection to retrieval-augmented generation patterns.

Lesson 4 • Context Window Management Strategies

Teaches summarisation, truncation, and selective retention to fit long conversations into limited windows. Prevents context overflow from degrading response quality.

Lesson 1 • Automated Evaluation Techniques

Uses model-as-judge and rubric-based scoring to scale evaluation beyond manual review. Covers reliability and bias risks in automated scoring pipelines.

Lesson 2 • Defining Prompt Quality Metrics

Establishes measurable criteria for accuracy, relevance, format compliance, and tone. Replaces subjective judgement with quantifiable evaluation standards.

Lesson 3 • A/B Testing Prompt Variants

Runs controlled comparisons between prompt versions using consistent evaluation criteria. Teaches statistical thinking for interpreting small-sample prompt experiments.

Lesson 4 • Building a Prompt Test Suite

Designs a structured set of test cases covering edge cases, typical inputs, and adversarial examples. Enables repeatable benchmarking across prompt versions.

Lesson 1 • Prompts for Code Generation and Review

Designs prompts that produce correct, readable, and well-documented code across languages. Covers code review, refactoring, and test generation use cases.

Lesson 2 • Prompts for Customer-Facing Applications

Builds prompts for chatbots, support agents, and FAQ systems with strict tone and accuracy requirements. Addresses escalation logic and user trust considerations.

Lesson 3 • Prompts for Data Analysis and Reporting

Structures prompts to extract insights, generate hypotheses, and format analytical outputs. Integrates structured data inputs with interpretive instruction design.

Lesson 4 • Prompts for Content and Writing Tasks

Applies persona, format, and style constraints to generate on-brand written content. Covers editing, summarisation, and tone transformation use cases.

Lesson 1 • Collaborating on Prompts Across Teams

Introduces shared editing, commenting, and approval processes for cross-functional prompt work. Aligns technical and non-technical stakeholders on prompt design decisions.

Lesson 2 • Monitoring Prompts in Production

Tracks live prompt performance using output sampling, user feedback, and drift detection. Enables proactive maintenance before quality degradation affects users.

Lesson 3 • Prompt Governance and Quality Standards

Establishes review workflows, ownership policies, and quality gates for production prompts. Prevents unreviewed prompts from reaching end users in critical systems.

Lesson 4 • Building a Prompt Library

Designs a structured repository for storing, tagging, and retrieving reusable prompt templates. Reduces duplication and accelerates deployment across teams.