Overview

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Academic contacts

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Offerings

MURDOCH-S1-FACE2FACE-2025-ONGOING
MURDOCH-S1-ONLINEFLEX-2025-ONGOING
MURDOCH-S2-FACE2FACE-2025-ONGOING
MURDOCH-S2-ONLINEFLEX-2025-ONGOING

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Enrolment rules

Enrolment in a graduate IT course, or permission of the Academic Chair.

Other learning activities

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Learning activities

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Learning outcomes

1.

Understand core programming concepts such as abstraction and divide-and-conquer strategy and be able to break up a large problem into smaller sub-problems and express your solutions in algorithms.

2.

Use Python’s control structures and data representations to implement effective algorithms.

3.

Manipulate strings and data structures using built-in classes such as string, list, and dictionary for practical applications.

4.

Write modular programs using functions and importable modules for reusability and efficiency.

5.

Work with files and directories to read, write, and manage data.

6.

Debug and test Python programs systematically and apply exception handling to manage error and abnormal conditions.

7.

Understand object-oriented programming concepts and be able to create and use new classes in problem-solving.

8.

Process and analyse data using NumPy arrays for numerical computations and create meaningful data visualizations with Matplotlib to communicate analytical insights.

9.

Demonstrate best practices in Python programming, including documentation, readability, and IT professional ethnics.

Assessments

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Additional information

Unit content:

. Introduction and Computation · Branching and Iteration · Strings and String Manipulation · Functions  and Abstractions  · Tuples and Lists · Sets and Dictionaries .  Files and Directories · Testing, Debugging and Exception Handling · Class and Objects · NumPy Module and Ndarrays . Data Visualisation Using Matplotlib