Data Science: Data Driven Decision-Making - PDB1027

Data Science: Data Driven Decision-Making

Professional development short course

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 Data Science: Data Driven Decision-Making microcredential, you’ll work through practical programming exercises 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.

This microcredential is jointly offered by the Monash School of Business and the Faculty of Information Technology. If you successfully complete the microcredential, you’ll receive a certificate of completion from Monash University.

You’ll receive one unit (six credit points) of academic credit which you can use towards a relevant Monash postgraduate award course in business or IT. To join a postgraduate course you must also meet Monash University’s entry criteria.

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.

At a glance


16 August 2021


Twelve weeks





Alumni discounted fees


Terms and conditions