Introduces students to computational thinking for data analytics. Students will learn to assess the suitability of different data structures and algorithms for data analytics and to design and implement algorithms.
1. Introduction to computational thinking and problem formulation
2. Big Data Types and Data Structures
3. Algorithms for Big Data
4. Introducing Computational Models
5. Computational Models and Simple Visualisation
6. Automation and Evaluation
Unit Learning Outcomes express learning achievement in terms of what a student should know, understand and be able to do on completion of a unit. These outcomes are aligned with the graduate attributes. The unit learning outcomes and graduate attributes are also the basis of evaluating prior learning.
|On completion of this unit, students should be able to:|
|1||analyse problems and related data to determine an appropriate solution|
|2||use suitable data structures and algorithms for solving a problem|
|3||design and develop algorithms and computational models to solve problems|
|4||apply evaluation techniques in order to determine appropriate solutions to a problem|
On completion of this unit, students should be able to:
- analyse problems and related data to determine an appropriate solution
- use suitable data structures and algorithms for solving a problem
- design and develop algorithms and computational models to solve problems
- apply evaluation techniques in order to determine appropriate solutions to a problem
- Prescribed text information is not currently available.
Teaching and assessment
Commonwealth Supported courses
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