Real-world algorithms with Python recap activities

Real-world algorithms is a classroom-ready 6 lesson Computing unit for end of Year 9 or start of Year 10. It recaps KS3 Python programming while introducing the algorithm techniques computer scientists use to solve real problems.

Across six big ideas, pupils explore greedy algorithms through a change-making problem then apply optimisation with the knapsack problem by improving a Python packing program. They learn how memoization speeds up code using a simple baking analogy and a cache activity then test a Python cache list with indexes and return values.

Pupils also model task dependencies using Directed Acyclic Graphs (DAGs) including fixing and extending a Python program. The final lessons link algorithmic growth to the online world then introduce the Monte Carlo method with real applications like ray tracing and weather forecasting.

Everything is fully planned and ready to teach with editable PowerPoints, lesson plans, worksheets plus supporting Python programs and spreadsheets.

LESSONS INCLUDED:

1. The greedy algorithm
2. Luggage and logistics (knapsack problem)
3. Smart choices and memory (cache and memoization)
4. Ordering dependent tasks (DAGs)
5. Virality and replication (exponential growth)
6. The Monte Carlo method
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WHO IS THIS FOR?
Ideal for end of Year 9 or start of Year 10, particularly if you want a low-prep unit that revisits core Python skills and builds confidence before GCSE Computer Science.

Pupils finish with a stronger grasp of computational thinking and a clearer sense of how different algorithm techniques optimise, save time and produce reliable estimates in complex situations.

BUY NOW
Ready to refresh Python and teach algorithms with real purpose? Buy Real-world algorithms today and walk into your next six lessons with everything planned, resourced and ready to go.

Non-specialist teaching computing? These complete, curriculum-aligned units are ready to pick up and teach with confidence, with clear explanations and everything organised so you’re not spending evenings teaching yourself first.