Practical Prompt Engineering & AI Tools for Productivity

Course outline and learning expectations

This is a tutor-led course. The outline shows what your tutor will cover; teaching materials and examinations are provided directly to enrolled students.

What you will learn

• Explain in plain language what large language models are and identify their main strengths and limitations
• Write effective prompts using clear goals, context, constraints, examples and output formats
• Use AI tools to support research, writing, studying and routine business tasks
• Review AI-generated content for factual errors, hallucinations, bias, unsuitable tone and missing context
• Protect personal and confidential information and apply responsible human review to AI-assisted work
• Use AI for coding explanations and debugging support while testing and verifying suggested code
• Create reusable prompt templates for recurring tasks
• Develop a personal or small-business AI toolkit containing tested prompt templates

Modules

1. 1

   Understanding Large Language Models

   Explain large language models in plain language and recognise what they can and cannot reliably do

   Generative AI and LLM basicsHow prompts and outputs workCommon AI tool categoriesStrengths and limitationsHuman judgement and oversight
2. 2

   Writing Effective Prompts

   Create clear prompts using purpose, context, examples, constraints and output instructions

   Defining the task and audienceAdding relevant contextSetting role and toneUsing examplesSpecifying format and lengthTesting and refining prompts
3. 3

   AI for Research, Writing and Studying

   Use AI to organise ideas, improve drafts and support learning without replacing source checking or original thinking

   Research questions and search planningSummarising learner-provided materialOutlining and draftingEditing for clarity and toneStudy notes and practice questionsSource verification and citation checks
4. 4

   AI for Business Productivity

   Apply AI to common business communication and marketing tasks relevant to African organisations and small enterprises

   Professional emailsCustomer service repliesMarketing copySocial media contentProduct and service descriptionsTour itinerary and quotation draftsReview and approval workflows
5. 5

   Using AI for Coding Help Responsibly

   Use AI for beginner coding explanations and troubleshooting while testing outputs and protecting sensitive information

   Explaining code in plain languageGenerating small code examplesReading error messagesDebugging step by stepTesting suggested codeSecurity and privacy cautionsKnowing when expert review is needed
6. 6

   Spotting AI Mistakes and Risks

   Identify hallucinations, bias and over-trust, then apply practical checks before using AI outputs

   What hallucinations look likeChecking facts and sourcesBias and representationOutdated or incomplete informationPrivacy and confidential dataCopyright and academic integrityHuman accountability
7. 7

   Building Reusable Prompt Templates

   Turn successful prompts into structured templates for recurring personal, study and business tasks

   Template componentsVariables and placeholdersPrompt checklistsVersioning and improvementTask-specific prompt librariesTesting across different AI tools
8. 8

   Capstone — Personal or Business AI Toolkit

   Create and test a practical collection of reusable prompts for a learner-selected personal, study or small-business context

   Selecting recurring tasksDesigning prompt templatesTesting and revising outputsAdding verification and privacy checksOrganising the toolkitPresenting the final prompt pack