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MICROCREDENTIAL

Data Analytics Foundations

Designed for professionals who are new to working with data, this microcredential covers the fundamentals of data analysis. Understand the value and power of data, master key concepts and terminology, explore clustering and analysis techniques and begin analysing and visualising a range of data sets.

About this microcredential

Data Analytics Foundations introduces participants to the significance and language of data analytics for business and society. The participant will be introduced to the cross-industry standard process for data mining (CRISP-DM), the most common approach to data mining.

This microcredential offers practice in the foundations of data analytics, including identifying data set and attribute types, data preparation and cluster analysis. Advanced techniques for clustering will help develop skills in identifying problems for cluster analysis and a range of approaches to address these limitations. Applying these data analytics techniques enables interpretation of a data set and visual data exploration.

Key benefits of this microcredential

  • Get started in data science without the heavy maths or coding – this course uses a visual, open-source platform (KNIME) to demonstrate and practice key concepts and models for those without a programming background.
  • Learn both important context and models and how to apply key techniques with practical exercises.
  • Complete as a self-contained course, or as a potential pathway to future postgraduate study.

This microcredential aligns with the 2 credit point subject, Data Analytics Foundations (42821) in the Graduate Certificate in Professional Practice (C11298), Graduate Diploma of Professional Practice (C06136), Master of Professional Practice (C04404), Graduate Certificate in Technology (C11301), Graduate Diploma in Technology (C06137) and Master of Technology (C04406).

This microcredential may qualify for recognition of prior learning at this and other institutions.

Who should do this microcredential?

This microcredential is accessible to professionals from a wide range of sectors and backgrounds who are new to working with data.

UTS microcredentials are developed for professionals with a capacity to undertake postgraduate tertiary education.

Price

Full price: $1,595.00 (GST-free)*

*Price subject to change. Please check price at time of purchase. 

Enrolment conditions

COVID-19 response 

Additional course information

Course outline

This course has been designed to provide you with an applied introduction to the field of data analytics, and an orientation to its different usages. It has been designed by the UTS Faculty of Engineering and Information Technology, leveraging the Faculty's unique expertise in the area of artificial intelligence.

In this course, you will meet (virtually) and work with a dedicated course facilitator, who will support your learning and engagement with the teaching resources prepared by the academic team and the lead academic.

This course is structured into five modules. Each module includes self-study materials and facilitated online sessions. The five modules are:

Module 1 - Introduction to data analytics

  • In this module, you are introduced to the basics of data analytics. In the weekly live and online sessions, we will review the material and unpack how data analytics can be further applied.

Module 2 - Know your data

  • In this module, we will go through the definition of data, types of data, instances and attributes of the dataset, data quality issues and methods of data collection.

We will also learn about the standard process of data mining in detail with a real-world business scenario.

Module 3 - Data pre-processing

  • In this module, you are introduced to the concept of pre-processing, its techniques, and the effect of pre-processing in transforming the data into a more understandable form.

Module 4 - Data exploration and visualisation

  • Data visualisation represents data in a graphical form that is easy to understand as "a picture is worth a thousand words". It is particularly useful when we are trying to understand data, its trends and outliers.
  • Data visualisation allows sharing unbiased representations of data which can be particularly helpful in making recommendations to stakeholders.

Module 5 - Data clustering

  • In the first part of this module, you will be introduced to the clustering concept, methods, requirements and types of clustering. In the second part, you will be introduced to one of the most famous of clustering methods, K-Means Clustering. 

Scheduling

This course is delivered in a scheduled format over ten weeks.

Each week (during weeks 1 to 8) you will participate in an online session where you will have the chance to apply what you've learned, ask questions and hear from other participants who are taking the course with you. The workshops are led by the course facilitator.

Weeks nine and ten are planned to give you time to complete the final assignment, with support and scheduled Q&A sessions provided.

Course delivery

This microcredential includes weekly, live, one-hour online workshops facilitated by an expert UTS academic supporting self-study and online learning activities. Case studies of real-world business operations will be used to illustrate applications of data mining techniques. The workshop sessions focus on hands-on experience in data mining, data analytics tools and understanding and interpretation of the results. Regular formative quizzes throughout the microcredential will allow participants to gauge their progress.

Course learning objectives

Upon successful completion of this microcredential you will be able to apply pre-processing, transformation and visualisation to business data sets.

You will be able to interpret a contextualized data set and explain your application of data analytics approaches to a peer.

Assessment

The graded assessment task is an individual written assessment on data exploration and preparation. This assignment includes reflection on individual practical work on data visualisation, exploration and preparation (pre-processing and transformation) for data analytics with artefacts (screen shots/outputs) of the practical work submitted in the report.

Length: 2,000 words

In order to pass the microcredential, participants must achieve an overall mark of 50% or more.

Requirements

Mandatory

  • To complete this online course you will need a personal computer with reliable Internet access and the ability to run the latest version of our supported Internet browsers; Zoom for online meetings and classes and the open-source software, KNIME Analytics Platform.
$1,595.00

START DATE

02 August

MODE

Online

DURATION

10 wks

COMMITMENT

Avg 5 hrs p/w

Book a session

Mon 02 Aug 2021 -
Fri 08 Oct 2021
  • 2 August - 8 October 2021
  • Online
Mon 04 Oct 2021 -
Fri 10 Dec 2021
  • 4 October - 10 December 2021
  • Online
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