R with Database and Big Data is our fifth course of the autumn term. It takes place in November 21-22 in a location close to Milano Lima.
During this course you will see how to connect databases through R, and how to use dplyr with databases. Then you will become familiar with the basic IT infrastructures behind big data, the R toolbox to access and manipulate big data structures, the sparkML libraries for out of memory data modeling and ad hoc techniques for big data visualization. It presents the latest techniques to work with big data within the R environment, which means manipulating, analyzing, visualizing big data structures that exceed the single computer capacity in a true R style.
No previous knowledge of big data technology is required, while a basic knowledge of R is necessary.

R with Database and Big Data: Outlines

– Introduction to databases
– Connecting databases through R: ODBC and RSQLite
– Data manipulation with dplyr
– Using dplyr with databases
– Introduction to distributed infrastructure
– Spark and Hadoop
– Sparklyr
– Distributed data manipulation with dplyr
– SparkML

R with Database and Big Data is organized by the R training and consulting company Quantide and is taught in Italian, while all the course materials are in English.

This course is for max 6 attendees.

Location

The course location is 550 mt. (7 minutes on walk) from Milano central station and just 77 mt. (1 minute on walk) from Lima subway station.

Registration

If you want to reserve a seat go to: FAQ, detailed program and tickets.

Other R courses | Autumn term

You can find an overview of all our courses here. Next dates will be:

• November 29-30: Professional R Programming. Organise, document and test your code: write efficient functions, improve the code reproducibility and build R packages. Reserve now!

In case you are a group of people interested in more than one class, write us at training[at]quantide[dot]com! We can arrange together a tailor-made course, picking all the topics that are interesting for your organization and dropping the rest.

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