FIT2085 - Fundamentals of algorithms for engineers

Overview

This unit introduces you to core problem-solving, analytical skills, and methodologies useful for developing flexible, robust, and maintainable software. In doing this, it covers a range of conceptual levels, from fundamental algorithms and data structures, down to their efficient implementation as well as complexity. Topics include data types, data structures, … For more content click the Read More button below.

This unit introduces you to core problem-solving, analytical skills, and methodologies useful for developing flexible, robust, and maintainable software. In doing this, it covers a range of conceptual levels, from fundamental algorithms and data structures, down to their efficient implementation as well as complexity. Topics include data types, data structures, algorithms, algorithmic complexity, recursion, and their practical applications.

Offerings

S1-01-CLAYTON-ON-CAMPUS

S1-01-MALAYSIA-ON-CAMPUS

S2-01-CLAYTON-ON-CAMPUS

S2-01-MALAYSIA-ON-CAMPUS

Requisites

Prohibition

Prerequisite

Contacts

Chief Examiner(s)

Associate Professor Markus Wagner

Unit Coordinator(s)

Dr Muhammad Fermi Pasha

Yasmeen George

Brendon Taylor

Notes

Optional Peer Assisted Study Sessions (PASS) run in this unit.

Teaching approach

Peer assisted learning

Assessment

1 - Assignment 1

2 - Assignment 2

3 - Assignment 3

4 - Weekly Quizzes

Scheduled and non-scheduled teaching activities

Applied sessions

Workshops

Workload requirements

Workload

Learning resources

Recommended resources

For algorithms and data structures:

B. Miller and D. Ranum - Problem solving with algorithms and data structures using Python.
M.T. Goodrich, R. Tamassia, M.H. Goldwasser - Data Structures and Algorithms in Python
Thomas Cormen, Charles Leiserson, Ronald Rivest, and Clifford Stein - Introduction to Algorithms

For Python:

Dive into Python 3: http://getpython3.com/diveintopython3/
Python 3 tutorial: http://docs.python.org/3/tutorial/
Interactive Python: http://interactivepython.org/runestone/static/thinkcspy/index.html
Algorithms in Python: http://interactivepython.org/runestone/static/pythonds/index.html

Technology resources

Availability in areas of study

Software engineering