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Unit of Study ISYS1006 - Introduction to Computing for Data Analytics (2023)

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Unit Snapshot

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Unit description

Introduces students to computing for data analytics and the role it plays in problem-solving. Students will learn to break down problems into steps that can be performed by machines to solve problems and accomplish goals.    

Unit content

Topic 1: Introduction to data analytics

Topic 2: Four types of data analytics (Descriptive, Diagnostic, Predictive, Prescriptive)

Topic 3: Understanding business data

Topic 4: Data preparation: value generation from raw data

Topic 5: Explorative analysis for model planning

Topic 6: Model building and communication in data analytics projects

 

Availabilities

Location Domestic International
Online
Term1
Term1

Learning outcomes

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:

articulate and apply knowledge of frameworks, processes, and techniques of data analytics and incorporate with the principles and strategies of the business environment

apply analytical thinking on business needs assessment and analytical problem framing

apply practical knowledge and skills of Python programming to perform data preparation, exploration, and modelling tasks

effectively interpret and communicate insights from data analytics projects using appropriate data analytics techniques.

Prescribed learning resources

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Prescribed Resources/Equipment
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Prescribed Learning Resources may change in future Teaching Periods.