Semester 2, 2023 Online | |
Units : | 1 |
School or Department : | School of Mathematics, Physics & Computing |
Grading basis : | Graded |
Course fee schedule : | /current-students/administration/fees/fee-schedules |
Staffing
Course Coordinator:
Overview
Computational thinking is a core skill across many cross disciplinary fields. Future professionals in management roles as well as data analysts need to understand fundamental computational approaches to problem solving. The topics in this course are intended to introduce students not merely to the coding of computer programs, but algorithmic thinking, data management, the methodology of computer programming, and the principles of good program design including modularity, encapsulation and abstraction. The Python language is used because of its extensive application libraries and its effectiveness and popularity as a modern programming language.
This course covers fundamental computational problem solving concepts, tools and methodologies. Students will learn how to select an appropriate data type and apply the most appropriate technical processes for a given computational problem. They will also learn how to develop modular code which conforms to the basic principles and practices of software engineering.
Course learning outcomes
On successful completion of this course students should be able to:
- Effectively conduct program designs including modularity, encapsulation and abstraction;
- Differentiate between available data types and demonstrate their appropriate problem application;
- Apply available libraries to solve problems.
Topics
Description | Weighting(%) | |
---|---|---|
1. | Overview of Python syntax, semantics and control structures | 10.00 |
2. | Functions | 20.00 |
3. | Programming with objects | 5.00 |
4. | Data structures | 25.00 |
5. | File I/O | 10.00 |
6. | Libraries | 15.00 |
7. | Principles and practices of software engineering | 10.00 |
8. | Ethics of software engineering | 5.00 |
Text and materials required to be purchased or accessed
(Download from: Permission is granted to copy, distribute, transmit and adapt this work under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.)
Student workload expectations
To do well in this subject, students are expected to commit approximately 10 hours per week including class contact hours, independent study, and all assessment tasks. If you are undertaking additional activities, which may include placements and residential schools, the weekly workload hours may vary.
Assessment details
Description | Group Assessment |
Weighting (%) | Course learning outcomes |
---|---|---|---|
Tech and/or scntific artefact 1 | No | 20 | 1,2,3 |
Tech and/or scntific artefact 2 | No | 30 | 1,2,3 |
Time limited online examinatn | No | 50 | 1,2 |