Build a practical understanding of artificial intelligence and learn how to use it thoughtfully in work and study. This beginner-friendly course explains AI, machine learning and generative AI in plain language before introducing hands-on techniques for prompting, communication, creative planning, structured data extraction and workflow design.
Across ten modules, you will practise using public or fictional information, compare outputs with their source material and improve prompts using clear quality criteria. You will also learn the basics of model evaluation, recognize misleading results and plan safeguards for privacy, bias and unreliable outputs.
The course concludes with a small capstone project: design an AI-assisted solution, test it against realistic and difficult inputs, document its limitations and present the result. Coding is optional; the focus is on understanding, practical application and human review.
Proposed learning format: 30 hours of guided lessons, demonstrations, exercises and project work. Assessment uses module knowledge checks, practical deliverables and the final project. Learners should have access to a computer, a spreadsheet application and an institution-approved AI assistant. Tool availability and any paid account requirements must be confirmed by the training provider.
What You Will Learn:
1. Distinguish AI, machine learning, deep learning and generative AI.
2. Explain basic language-model behaviour and recognize unsupported outputs.
3. Write and improve prompts using task, context, constraints and output format.
4. Draft and review emails, summaries, study plans and creative briefs.
5. Extract structured records and verify completeness, data types and totals.
6. Distinguish classification, regression and clustering and interpret basic evaluation measures.
7. Design AI-assisted workflows with validation, exceptions and human approval.
8. Identify privacy, bias, security and reliability risks and propose controls.
9. Build, test and present a small AI-assisted capstone solution.
Key Outcomes
Target Audience
Students, graduates, working professionals, educators, administrative teams, content creators and small-business teams seeking a practical introduction to AI. Suitable for learners without a programming background.
Prerequisites
Basic computer and internet skills; ability to read and write in English; access to a computer, internet connection and spreadsheet application. No previous AI experience or coding knowledge is required. Practical exercises need an AI assistant approved by the training provider; use public or fictional data.
Course Syllabus
1. Understanding Artificial Intelligence (2 hours)
2. How Generative AI and Language Models Work (3 hours)
3. Prompt Design and Iterative Improvement (4 hours)
4. AI for Communication, Research and Learning (3 hours)
5. AI-Assisted Content and Creative Planning (3 hours)
6. Working with Data and Structured Outputs (3 hours)
7. Machine Learning and Model Evaluation (3 hours)
8. Designing Reliable AI Workflows (3 hours)
9. Responsible AI, Privacy and Human Oversight (2 hours)
10. Capstone: Build and Review an AI-Assisted Solution (4 hours)
Total: 30 hours, including practical exercises and a capstone project.
Frequently Asked Questions
This course is designed for students, graduates, educators, professionals and business teams who want a practical introduction to AI. No previous AI experience is required.
No. The core exercises use prompts, documents, spreadsheets and workflow planning. Coding is optional for the final project.
You will learn AI fundamentals, generative AI, prompt design, communication and content workflows, data extraction, basic machine-learning evaluation, responsible use and project testing.
The proposed course contains 30 learning hours across ten modules, including practical exercises and a four-hour capstone module. The training provider will confirm the timetable and access period.
The course is planned for online delivery. The training provider will confirm the session schedule, platform and whether recordings or self-paced access are included.
You need a computer, internet connection, spreadsheet application and an AI assistant approved by the training provider. Confirm any account or subscription costs before enrolment.
You will create a prompt library, review meeting notes, plan a content campaign, verify extracted invoice data, evaluate a sample classifier and design an AI-assisted workflow.
Choose a document-summary assistant, course-content assistant or enquiry-classification workflow. Submit a brief, prompts or workflow, test cases, outputs, risk checks and a short demonstration.
The proposed approach uses module knowledge checks, practical deliverables and a final project. The capstone rubric covers problem definition, design, output quality, testing, responsible use and presentation. Final pass criteria must be confirmed by the provider.
Certificate availability and completion requirements have not been confirmed. Please check with the training provider before enrolment.
Use public or fictional data for the exercises. Use real business information only when organizational policy, permissions and the selected tool permit it; minimize personal and confidential details.
This course develops foundational knowledge and practical AI literacy. It is an introduction rather than a complete AI engineering programme; advanced development requires further study and programming practice.
Fees, start dates and enrolment details will be confirmed by the training provider. These details are intentionally left unset in this course draft.
