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Predictive Analytics: Gaining Insights from Big Data

Learn to use predictive analytics tools and HPE Vertica Analytics to gain insights from big data, with this free online course.

4,963 enrolled on this course

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  • Duration

    4 weeks
  • Weekly study

    2 hours

Learn how predictive analytics tools can help you gain insights from big data.

Collecting big data is just the first step; once you have it, how do you make sense of it? This free online course will show you how predictive analytics tools can help you gain information, knowledge and insights from big data.

Over the next four weeks, experience the power of HPE’s Vertica Analytics platform as an applied tool. Using Vertica Analytics and a case study approach, apply built-in predictive analytics functions and algorithms – linear regression, logistics regression and k-means clustering – to derive insight from your data, helping to create opportunities for your organisation.

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Skip to 0 minutes and 8 seconds Hello. Big data is everywhere. We can capture trends, patterns and associations which tell us a story about human behaviour across many different areas—business and health, the environment and industry. Here at QUT we work across these domains drawing on the expertise of researchers to develop methodologies for analysing, visualising and managing big data for different organisations. QUT’s Australian Research Council Centre of Excellence in Mathematical and Statistical Frontiers aims to bring together expert in mathematics, statistics and machine learning to tackle frontier research challenges. These new solutions are used to contribute to the creation of healthy people, sustainable environments and prosperous societies.

Skip to 1 minute and 3 seconds Using HPE Vertica Analytics and a real-world case study, this course will show you how to apply three predictive models – linear regression, logistics regression and K-means clustering – to gain knowledge and insights from big data. Join us — and you too can learn how to make sense of big data.

What topics will you cover?

  • Modelling, estimation and prediction
  • Estimation and prediction using linear regression
  • Estimation and prediction using logistic regression
  • Estimation and prediction using k-means clustering

Learning on this course

On every step of the course you can meet other learners, share your ideas and join in with active discussions in the comments.

What will you achieve?

By the end of the course, you‘ll be able to...

  • Describe big data analytics
  • Identify solutions to big data problems
  • Evaluate predictive data analysis models
  • Assess the suitability of predictive models
  • Model data using various predictive models

Who is the course for?

This course is aimed at data scientists, data analysts and those who need to deal with big data in their workplace. For learners without experience in this field, familiarity with SQL and UNIX is highly recommended in order to make the most of the learning opportunities.

What software or tools do you need?

There are many tools available for making sense of big data. In this course, we will be using Hewlett Packard Enterprise’s Vertica Analytics platform. New to Vertica Analytics? Don’t have the software? Don’t worry: we’ll send you a link with instructions on how you can download a data-limited version – yours to keep indefinitely. The downloadable virtual machine includes a case study data set that we’ll be using for the practical sessions of this course.

You will need access to a Windows or Mac machine with the following:

  • 64-bit Windows 7 or above; 64-bit macOS (previously known as OS X)
  • 30 GB free disk space
  • 12 GB RAM
  • administrator rights to your machine so that you can install the VM Player.

Who will you learn with?

I’m a Professor at QUT and a Deputy Director of ACEMS. My interests are in statistical modelling and analysis, computational and simulation sciences and big data analytics.

I have been developing educational materials for Vertica Analytics at Micro Focus Software Education since 2011, focusing on instructor-led materials and self-paced training.

Who developed the course?

Queensland University of Technology

QUT is a leading Australian university ranked in the top 1% of universities worldwide by the 2019 Times Higher Education World University Rankings. Located in Brisbane, it attracts over 50,000 students.

  • Established

  • Location

    Brisbane, Australia
  • World ranking

    Top 180Source: Times Higher Education World University Rankings 2019

Learning on FutureLearn

Your learning, your rules

  • Courses are split into weeks, activities, and steps to help you keep track of your learning
  • Learn through a mix of bite-sized videos, long- and short-form articles, audio, and practical activities
  • Stay motivated by using the Progress page to keep track of your step completion and assessment scores

Join a global classroom

  • Experience the power of social learning, and get inspired by an international network of learners
  • Share ideas with your peers and course educators on every step of the course
  • Join the conversation by reading, @ing, liking, bookmarking, and replying to comments from others

Map your progress

  • As you work through the course, use notifications and the Progress page to guide your learning
  • Whenever you’re ready, mark each step as complete, you’re in control
  • Complete 90% of course steps and all of the assessments to earn your certificate

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