This week’s topics
Measuring complexity: Big O notation
- Measuring complexity: Big O and little o notation
- Loops, nested loops, recursion and memory usage
What you will be able to do
- 2.1 Demonstrate an ability to write Big O and little o notation to describe algorithmic complexity.
- 2.2 Explain the impact of algorithmic design choice on computational complexity for a variety of examples.
Activity
Start with this week’s 2 videos, then: Seminar, guided reading and a short written task: demonstrate an ability to write Big O and little o notation to describe algorithmic complexity.
Study materials
Videos
- Why My Teenage Code Was Terrible: Sorting Algorithms and Big O Notation · YouTube · Tom Scott · 10 min · for registered students
- Introduction to Big O Notation · YouTube · Neso Academy · 8 min · for registered students
Further resources
- Introduction to Computer Science, 3.3: Formal Properties of Algorithms · PDF · OpenStax Introduction to Computer Science (2024), 3.3: time complexity and comparing algorithms (a step up), pp. 104–109 · for registered students
Materials marked “for registered students” open in the student portal, which is set up as soon as you receive final acceptance.