Review and coursework completion

This week’s topics

Review and coursework completion

1. Reviewing the learning outcomes
2. Completing and checking coursework against the criteria
3. Self-assessment

What you will be able to do

• 1.1 Describe a data structure.
• 1.2 Explain a range of linear and non-linear data structures.
• 1.3 Analyse the impact of the choice of data structure on algorithmic performance.
• 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.
• 2.3 Explain the difference between P and NP.
• 2.4 Evaluate open problems in problem classification and the impacts of future technologies on the difficulty in solving different classes algorithms.
• 3.1 Use recursion and memoisation as tools to design solutions to problems.
• 3.2 Describe a range of sort, search, and pathfinding algorithms.
• 3.3 Explain the trade-off between memory and computational complexity in algorithmic design.
• 3.4 Critically analyse algorithmic paradigms such as the greedy approach and divide and conquer approach.
• 3.5 Evaluate sort, search, and pathfinding algorithms in terms of their space and time complexity.
• 4.1 Explain how to write pseudo-code for algorithmic design.
• 4.2 Implement pseudocode in a programming language.
• 4.3 Evaluate the correctness and speed of an algorithm.
• 4.4 Use debugging to correct errors in algorithmic implementation.

Activity

Guided review of every criterion; coursework completion clinic and peer review.

Study materials

Further resources

• College Success, 7.6: Metacognition · PDF · OpenStax College Success (2020, updated 2023), 7.6: judging your own learning for self-assessment, pp. 216–218 · for registered students