PhD in Computer Science

Cloud Computing for Science

Cloud Computing for Science

Academic year 2023/2024

Sommario del corso

• Course objectives
• Results of learning outcomes
• Program
• Course delivery
• Suggested readings and bibliography
• Notes
• Teaching tools
• Course card

Course objectives

This course aims at introducing the student to the key concepts and technologies of current cloud computing systems and platforms especially targeted to large-scale data storing and processing.

Results of learning outcomes

Students will learn both theoretic and practice concepts concerning the storing and processing massive amount of data on large-scale distributed systems by exploting the cloud computing paradigm 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, by especially focusing on systems and architectures for big data. It will present the key principles, paradigms, tools and technologies underlying distributed systems and architectures for big data analytics services and applications (e.g., batch and stream data processing). Practical examples will be provided mainly based on the Apache Hadoop ecosystem (e.g., MapReduce and Spark).

Course delivery

This course will be delivered on July 2024, specifically:

• July 11, 2024 at 10:00-13:00 and 14:00-17:00
• July 16, 2024 at 10:00-13:00 and 14:00-17:00

See the Moodle page of this course for details.

There are no required textbooks for this course. The lecturers will propose papers, documentation and websites as educational materials during the course.

Notes

Prerequisites

Basic concepts of computer science including operating systems, computer networks, database management systems and computer programming.
Programming languages: Python or Java.

• Teaching material
• Exams and finals
• Class schedule
• Go to Moodle
• Register for the course
• Enrolled students
• Invia email agli studenti registrati
• Export table