Course Unit Page
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Teacher Andrea Bartolini
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Credits 3
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Teaching Mode Traditional lectures
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Language English
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Teaching Material
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Course Timetable from Sep 23, 2019 to Dec 16, 2019
Academic Year 2019/2020
Learning outcomes
The Lab of Big Data architectures extends and integrates what learnt by the student in the course statistics and architectures for big data processing with a more in depth and practical knowledge of the big-data technologies and architectures. The students will learn how to design a big data system, the key concepts and differentiators behind state-of-the-art technologies and architectures, and how to use it effectively. This will be done by a series of practical exercises with interactive explanations, where students will learn by solving practical problems and examples.
Course contents
Configuring a Python environment
Connecting to a remote Big-Data Cluster
Creating a Big-Data Pipeline
Working with large datasets: from Pandas data frame to Spark data frame
Machine learning on large-scale time-series dataset
Teaching methods
The class with consists of the completion of a set of practical tutorials and assignments conducted on the own laptop and on a remote big data cluster hosted by the Italian Supercomputing Centre CINECA.
Assessment methods
Based on student's reports
Office hours
See the website of Andrea Bartolini