PhD in Computer Science

Cloud Computing for Science

Cloud Computing for Science

Academic year 2018/2019

Sommario del corso

• Course objectives
• Results of learning outcomes
• Program
• Suggested textbooks and readings
• Notes
• Teaching tools

Course objectives

This course aims at introducing the student to the key concepts and technologies of current cloud computing systems.

Results of learning outcomes

Students will learn both theoretic and practice concepts concerning Cloud Computing so as they will be able to realize in which scientific scenarios this computing paradigm can be fully exploited.

Program

The course introduces the student to cloud computing. It surveys the technology that underpins the cloud, new approaches to technical problems enabled by the cloud, and the concepts required to integrate cloud services into scientific work. It covers:

• managing data in the cloud, and how to program cloud services;
• computing in the cloud, from deploying single virtual machines or containers to support basic interactive science experiments, to gathering clusters of machines to do data analytic;
• using the cloud as a platform for automating analysis procedures, machine learning, and analyzing streaming data;
• interacting with main cloud platforms through open source software;
• cloud security.

•  Ian Foster and Dennis B. Gannon. Cloud Computing for Science and Engineering. MIT Press, 2017. ISBN: 9780262037242.

Class schedule

Note

• Teaching materials
• Exams and finals
• Go to Moodle
• Visit the forums