Aims

The aims of the course are to:

• Introduce the principles behind algorithm and data structure design and evaluation.
• Cover key topics including elementary and advanced data structures, including sorting algorithms, graph algorithms, and so on.
• Provide an understanding of how to translate algorithms into code for selected engineering problems through coding-focused computerised examples papers.

Objectives

As specific objectives, by the end of the course students should be able to:

• Analyse the computational efficiency of algorithms.
• Re-implement and debug algorithms.
• Correctly choose a suitable algorithmic solution and set of data structures for a computational problem.
• Understand the theoretical and practical advantages and disadvantages of various algorithmic approaches and established solutions.
• Devise and implement new algorithms and data structures, or modify existing algorithms and data structures, to solve previously unencountered tasks.

Content

• Part 1: Fundamentals of Algorithms and Data Structures (7L + 1 Example Class)
  • Interpreting and writing pseudocode, demonstrating correctness, arriving at tight/lower/upper bounds of running time/storage, and solving computational problems using a repertoire of data structures and algorithmic approaches.
• Part 2: Algorithms and Data Structures in Engineering (7L + 1 Example Class)
  • Translating pseudocode into code, debug implementations of algorithms and data structures, apply algorithms and data structures to solve a range of frequent engineering problems, such as finding shortest paths, resource allocation, and scheduling.