Predictive Analytics: Gaining Insights from Big Data
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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.
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.
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.
- 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
- 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.