Supercharge your data workflows with AI. 15 practical tutorials on using prompt engineering for data cleaning, EDA, machine learning, SQL, visualisation, and more.
Welcome to Section 5. Whether you spend your days cleaning messy CSVs, building machine learning pipelines, or translating model results for stakeholders, AI can accelerate almost every step — if you know how to ask. This section shows you exactly how to prompt AI to become your best pair programmer and analytical thinking partner.
Topics 1–9 work best in order — each one introduces a technique that the next topic builds on. Topics 10–15 are more modular; if you work primarily on statistical work or NLP, jump to those directly. Throughout, every topic includes realistic column names and dataset shapes so you can paste the prompts straight into your own work with minimal editing.
Tip: Keep a Jupyter notebook open while you read. After each strong prompt example, paste it into your AI tool of choice, swap in your own dataset columns, and run the generated code immediately. The best way to internalise these patterns is to see real output from your own data.
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