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.
Topic 1: Computational thinking for data analytics
Topic 2: Computational Models
Topic 3: Data structures and algorithms
Topic 4: Abstraction
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||analyze problems and determine the appropriate solution|
|2||assess the suitability of data structures and algorithms for use in computational thinking|
|3||develop programs that use existing algorithms to solve problems|
|4||design and develop algorithms to solve problems using appropriate data structures.|
On completion of this unit, students should be able to:
- analyze problems and determine the appropriate solution
- assess the suitability of data structures and algorithms for use in computational thinking
- develop programs that use existing algorithms to solve problems
- design and develop algorithms to solve problems using appropriate data structures.
- Prescribed text information is not currently available.
Teaching and assessment
Commonwealth Supported courses
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