UnitLevel 5Postgraduate

ITO5145 Introduction to data science

Faculty of Information Technology

ITO5145 Introduction to data science is a level 5, 6-credit-point, postgraduate unit from the Faculty of Information Technology. It isn't offered in 2022. It needs ITO4131, ITO4133 or ITO4136.

Credit points
6
Offered in 2022
Other periods
Monash Online
Assessment
No exam
4 tasks

This is the 2022 handbook entry. See the 2027 entry.

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Requisites

After ITO5145

No unit lists ITO5145 as a prerequisite in the 2022 handbook.

Equivalent units

The same content under another code. Only one of them counts.

Overview

This unit looks at processes, case studies and simple tools to understand the many facets of working with data, and the significant effort in Data Science over and above the core task of Data Analysis. Working with data as part of a business model and the lifecycle in an organisation is considered, as well as business processes and case studies. Data and its handling is also introduced: characteristic kinds of data and its collection, data storage and basic kinds of data preparation, data cleaning and data stream processing. Styles of data analysis and outcomes of successful data exploration and analysis are reviewed. Standards, tools and resources are also reviewed. Basic curation and management are reviewed: archival and architectural practice, policy, legal and ethical issues.

Offerings in 2022

Teaching periodCampusMode
Teaching period 4Monash OnlineOnline
Teaching period 5Monash OnlineOnline
Teaching period 6Monash OnlineOnline

Assessment

  • Data science exercisesOther
    20%
  • Business and data case studyOther
    40%
  • QuizOther
    30%
  • Video presentation
    10%

Learning outcomes

When you finish this unit, you should be able to:

  1. 1

    Analyse the role of data in organisations, including curation and management issues;

  2. 2

    Apply basic tools for performing exploratory data analysis and visualisation;

  3. 3

    Apply basic tools for managing and processing big data;

  4. 4

    Apply basic predictive modeling and data analysis methods;

  5. 5

    Determine data storage and processing requirements for a data science project;

  6. 6

    Identify data resources and standards.

Workload and teaching

  • Workshops12 hours
  • Teaching approachOnline learning

A minimum of 144 hours over the 6 week teaching period should be used to complete assignments, participating in discussions, private study and revision.

Learning resources

Technology resources

Python is free to download from https://www.python.org/downloads/

Contacts

Chief Examiners
Dr Guanliang Chen

Common questions

What are the prerequisites for ITO5145?

You need ITO4131, ITO4133 or ITO4136 before you enrol.

When is ITO5145 offered?

ITO5145 has no offerings listed in the 2022 handbook.

Does ITO5145 have an exam?

No. ITO5145 has 4 assessment tasks and no exam.

More details

Credit points
6
Level
5
Study level
Postgraduate
Faculty
Faculty of Information Technology
Type
Coursework
EFTSL
0.125
Student contribution
SCA Band 2
Study abroad
Not available
Handbook years
202220232024202520262027