Practical Prompt Engineering (Beginner)
Wednesday, August 19th, 2026
This course is a practical introduction to prompt engineering. It is designed for learners at a beginner level who want to move from scattered knowledge to a clear, usable understanding they can apply straight away.
Across 5 lessons you will work through the core ideas step by step, with short exercises after each section so you can check your understanding as you go rather than at the very end.
What you’ll cover:
- How Language Models Respond to Input
- Structure, Context and Constraints
- Few-Shot and Role Prompting
- Chaining and Tool Use
- Evaluating and Iterating on Prompts
By the end you should be comfortable enough with prompt engineering to keep learning on your own, and to apply what you have covered in a real data context. No prior specialist background is assumed beyond basic familiarity with the subject area.
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Data Visualization and Storytelling
Wednesday, August 19th, 2026
This course is a practical introduction to data visualisation. It is designed for learners at a advanced level who want to move from scattered knowledge to a clear, usable understanding they can apply straight away.
Across 5 lessons you will work through the core ideas step by step, with short exercises after each section so you can check your understanding as you go rather than at the very end.
What you’ll cover:
- Choosing the Right Chart Type
- Colour, Scale and Honest Axes
- Designing for Your Audience
- Building a Narrative With Data
- Presenting Findings That Stick
By the end you should be comfortable enough with data visualisation to keep learning on your own, and to apply what you have covered in a real data context. No prior specialist background is assumed beyond basic familiarity with the subject area.
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Machine Learning Foundations
Wednesday, August 19th, 2026
This course is a practical introduction to machine learning. It is designed for learners at a intermediate level who want to move from scattered knowledge to a clear, usable understanding they can apply straight away.
Across 5 lessons you will work through the core ideas step by step, with short exercises after each section so you can check your understanding as you go rather than at the very end.
What you’ll cover:
- Supervised Versus Unsupervised Learning
- Features, Labels and Splits
- Training Your First Model
- Evaluating Model Performance
- Overfitting and Regularisation
By the end you should be comfortable enough with machine learning to keep learning on your own, and to apply what you have covered in a real data context. No prior specialist background is assumed beyond basic familiarity with the subject area.
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SQL for Business Analysts (Beginner)
Wednesday, August 19th, 2026
This course is a practical introduction to SQL. It is designed for learners at a beginner level who want to move from scattered knowledge to a clear, usable understanding they can apply straight away.
Across 5 lessons you will work through the core ideas step by step, with short exercises after each section so you can check your understanding as you go rather than at the very end.
What you’ll cover:
- How Relational Databases Think
- SELECT, WHERE and ORDER BY
- Joining Tables Together
- Aggregation and Grouping
- Subqueries and Common Table Expressions
By the end you should be comfortable enough with SQL to keep learning on your own, and to apply what you have covered in a real data context. No prior specialist background is assumed beyond basic familiarity with the subject area.
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Data Analysis with Spreadsheets
Wednesday, August 19th, 2026
This course is a practical introduction to spreadsheet data analysis. It is designed for learners at a advanced level who want to move from scattered knowledge to a clear, usable understanding they can apply straight away.
Across 5 lessons you will work through the core ideas step by step, with short exercises after each section so you can check your understanding as you go rather than at the very end.
What you’ll cover:
- Structuring Data for Analysis
- Essential Formulas and Functions
- Pivot Tables and Summaries
- Cleaning Messy Data
- Building a Reporting Dashboard
By the end you should be comfortable enough with spreadsheet data analysis to keep learning on your own, and to apply what you have covered in a real data context. No prior specialist background is assumed beyond basic familiarity with the subject area.
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