Online Microcredential in IT & Computer Science

Data Science: Data-Driven Decision Making

Discover storytelling with data and make better business decisions using data wrangling, modelling, and storytelling techniques.

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Monash UniversityMonash University

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Develop your own interactive dashboard that tells a data-driven story

Data becomes valuable when it allows us to make a decision or take action in the real world.

On this microcredential, you’ll work through practical programming exercises in R language to learn the process of tidying, harvesting and wrangling data and applying statistical models to simulate complex functions that solve a broad range of problems.

Using data visualisation techniques, you’ll learn to interpret and explain data to inform your decision-making process and communicate your message to others.

You’ll also explore the essential ethical, legal and organisational issues of data collection and management.

You’ll gain the skills you need to apply for roles as a data scientist or use the knowledge you’ve gained to enhance your current organisation.

The data science and data analytics industry is expected to grow by seven times in the next few years, reaching a value of $103 billion by 2023.

Industry statistics

  • Median base salary£45,000
  • UK job openings/month 1,724
Download video: standard or HD

Skip to 0 minutes and 4 secondsMICHAEL NIEMANN: What makes a data scientist?

Skip to 0 minutes and 6 secondsDIANNE COOK: What can data tell us about our world?

Skip to 0 minutes and 8 secondsMICHAEL NIEMANN: What underpins data-driven decisions?

Skip to 0 minutes and 10 secondsDIANNE COOK: These are the questions at the heart of the field of data science.

Skip to 0 minutes and 13 secondsMICHAEL NIEMANN: Hi, I'm Michael Niemann. I'm a lecturer in data science in the Faculty of Information Technology at Monash University.

Skip to 0 minutes and 20 secondsDIANNE COOK: I'm Dianne Cook, Professor of Business Analytics in the Department of Econometrics and Business Statistics at Monash University. In this course, you'll be introduced to the fundamental techniques used by professionals in the field of data science. You'll learn data analysis workflow, data wrangling, and plotting data, which lay the foundation for more advanced techniques like statistical modelling, regression, and decision trees, sentiment analysis, and working with big data.

Skip to 0 minutes and 47 secondsMICHAEL NIEMANN: Being able to effectively work with a variety of data types and sources and then tell a story that informs decision making is crucial. In this course, you'll have the opportunity to hone your data science skills alongside other learners as you complete practical programming exercises that reflect scenarios from the world around us. You'll gain the expertise needed to develop your own interactive dashboard that tells a data-driven story about a topic that matters to you.

Skip to 1 minute and 17 secondsDIANNE COOK: This course is jointly offered by the Monash School of Business and the Faculty of Information Technology. Learners who successfully complete the course and meet the Monash entry criteria can receive one unit or six credit points of academic credit towards a relevant Monash Master's Degree in Business Analytics or IT.

Skip to 1 minute and 36 secondsMICHAEL NIEMANN: This course is intended for anyone interested in developing skills in the industry standard tools and techniques and enhancing their ability to use data to inform decision making. That said, we'd highly recommend that you've studied an undergraduate unit in statistics.

Skip to 1 minute and 51 secondsDIANNE COOK: So if you're ready to complete further study with a university that is ranked among the best in the world, then we encourage you to join us in this course from Monash University.

What skills will you learn?

  • Data wrangling
  • R programming
  • Developing data analysis workflows
  • Work with and visualise spatial and temporal data
  • Developing statistical models
  • Harvesting data
  • Tidying data
  • Data collection methods
  • Data visualisation
  • Data analysis

What you will achieve

By the end of the microcredential, you’ll be able to...

  • Compile information and communicate as a data story
  • Read different data formats and utilise web scraping to collect data
  • Apply effective techniques to wrangle and visualise data
  • Design solutions for the challenges of big data
  • Apply modelling techniques and effective visualisation to make decisions with data
  • Compare and contrast a range of statistical and machine-learning tools
  • Assess and interpret the results of an analysis
  • Wrangle data into tidy format in preparation for visualisation and modelling
  • Identify and assess ethical, legal, social and organisational issues in data science

Are you eligible for this microcredential?

This data science microcredential is designed for anyone interested in developing skills in industry-standard tools and techniques, and enhancing their ability to use data to inform real-world decision-making.

Monash strongly recommends that you’ve studied maths or statistics at a first-year undergraduate level before joining this microcredential. To complete the programming exercises, you’ll need a computer to install and run RStudio and install R packages.

Is this microcredential right for you?

This is a practical microcredential and the application of the skills you’ll learn will benefit a wide range of professional contexts.

From manufacturing to healthcare, tourism to transportation, and media to government, if data or business intelligence is essential to the success of your organisation, this course will ensure you can use your data to make effective business decisions.

Syllabus

What happens before, during, and after your microcredential

  • Before learning

    You’ll have access to our online welcome area where you’ll be able to start conversations with fellow learners and read any additional information relating to your microcredential.

  • Course 1

    From 2 Mar 2020

    Wrangling and Workflow

    Get an introduction to data science and learn how to make the most of your data through effective data wrangling and storytelling.

    4 weeks
    12 hours per week
  • Course 2

    From 6 Apr 2020

    Modelling and Visualisation

    Explore the role of data visualisation in data science, and learn how to use and apply data modelling techniques.

    4 weeks
    12 hours per week
  • Course 3

    From 11 May 2020

    Formats, Ethics, and Storytelling

    Evaluate the challenges of data variety, ethics, and privacy on this course in Monash University's data science microcredential.

    4 weeks
    12 hours per week
  • After learning

    Once you have successfully completed the microcredential, you’ll receive your certificate of completion from Monash University.

What you will receive

6 credit points at Postgraduate level from Monash University

Find out how credits work and where you can use them in our FAQs.

A Certificate of Completion from Monash University

Learn more about this organisation

What is a microcredential?

Microcredentials are designed to upskill you for work in rapidly-growing industries, without the time and cost commitment of a full degree. You’ll earn academic credit to build towards a full degree, or your microcredential can stand alone as an independent credential.

Learn online with a leading university

Complete online courses led by expert tutors over 12-16 weeks with a dedicated group of professionals.

Complete project-based assessments

Test your understanding with online tutor-marked assessments and exercises.

Earn a professional credential

Finish your learning and pass your assessments to gain an accredited credential.

Advance further in your career

Use your microcredential as evidence of your specialised skills and progress further in your industry.

Learn more about the Common Microcredential Framework

Career-focused learning by Monash University

Monash University is one of Australia’s leading universities, ranked in the world’s top 1% by the Times Higher Education World University Rankings. It was established in Melbourne in 1958.

  • Established1958
  • LocationMelbourne, Australia
  • World rankingTop 80Source: Times Higher Education World University Rankings 2019

Delivered by expert academics

Dianne Cook

Dianne Cook

Di Cook is Professor of Business Analytics at Monash University. She is a Fellow of the American Statistical Association, and elected Member of the R Foundation.

Michael Niemann

Michael Niemann

I am a Data Science Lecturer at Monash University's Faculty of Information Technology. A computational linguist, I examine relationships & language use of online communities, leaders & professionals.

When would you like to start?

We aim to run our microcredentials every few months. Join on the date that suits you or register to hear from an enrolment advisor about future runs and updates.

Speak to an advisor

Not sure if this microcredential is right for you? Fill in your details below and one of our enrolment advisors will be in contact to provide you with the information you need to make a decision.

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Frequently asked questions

We can accept payments made by card (Visa, Mastercard and American Express) or PayPal via our online system.

You will have 14 days from the day the course starts to apply for a refund. You can find more information in our refund policy.

Microcredentials are designed to fit around your life and timezone.

There may be live events as part of your studies, but these will be recorded and can be watched afterwards if you aren’t online for the live broadcast.

No, microcredentials are designed to be taken anywhere in the world. You won’t need the right to study in the country where the university offering the microcredential is based.

If you wish to continue your data science studies and you meet Monash University’s entry criteria, you can use your academic credit towards a relevant Monash postgraduate award course in business or IT.

Want to know more? Read the microcredential FAQs, or contact us.