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Last updated on
07 November 2022

Course on "Cloud Computing & Big Data"

General information

Lecturer: Prof. Tommaso Cucinotta
Duration and format: 30 hours of front lessons (3 CFU)
Target programs: PhD in Artificial Intelligence, PhD in Data Science, PhD in Emerging Digital Technologies
Schedule: Tuesday 3pm-6pm and Friday 4pm-7pm, starting on November 15th, 2022
Location: TECIP Institute, CNR Area, ground floor. Students of the PhD in AI not based in Pisa will be able to attend via an on-line link provided to registered students.
Exam: Oral.

Schedule updates

The upcoming lectures are scheduled as follows:

Goal

This course provides an overview of the challenges to face, and the technical solutions to embrace, when building large-scale, fault-tolerant, distributed and replicated real-time cloud services. These systems need to be capable of serving millions/billions of requests per second with industrial-grade reliability, availability and performance, and are composed of thousands of components spanning across millions of machines, worldwide. The course focuses on design, development and operations of scalable software systems, including big-data processing and analytics, as used increasingly often for nowadays intensive computations needed to train large machine-learning and artificial intelligence models, where the huge volumes of data to handle mandates the use of heavily distributed algorithms. The course covers also basic concepts on networking architectures for data-centre and cloud computing infrastructures.

Program at a glance

Requirements

Students need a basic understanding of software, computer architectures, distributed systems and communication protocols.

Why to attend

Students will acquire a unique insight into the world of cloud computing and big-data related technologies, and will be able to master key concepts behind them. This is a fundamental brick in the background of a software engineer / computer scientist who will deal with modern distributed software systems in industry or academia, spanning across high-performance, cloud and even (increasingly connected) embedded systems.

About the lecturer

Prof. Tommaso Cucinotta has a MSc in Computer Engineering from University of Pisa and a PhD from Scuola Superiore Sant'Anna. He spent more than 10 years at the Real-Time Systems Laboratory (ReTiS) of Scuola Superiore Sant'Anna carrying out research in security and smart-card based authentication, adaptive deadline-based scheduling in the Linux kernel for embedded, soft real-time and multimedia applications, temporal isolation in virtualized cloud services and novel OS designs for massively parallel and distributed systems. He has been MTS at Bell Labs in Dublin, carrying out industrial research on security and confidentiality, and real-time performance of cloud systems, with a focus on Telco applications. He has also been a Software Development Engineer in AWS DataBase Services in Dublin, Ireland, working on scalability and performance enhancements to the AWS DynamoDB NoSQL real-time data-base. Since 2016, he is back at the ReTiS of Scuola Superiore Sant'Anna as associate professor. He is a member of the PhD board of the Data Science PhD program jointly offered by Scuola Sant’Anna, University of Pisa, Scuola Normale Superiore, IMT Lucca and CNR since its first edition in the a.y. 2017/2018. He is also a member of the PhD board of the National PhD in AI - AI for Society - program jointly offered by Scuola Sant'Anna, University of Pisa and other academic institutions. Since year 2019, he is head of the real-time and embedded systems research area at the RETIS.

Useful information and links

Download course brochure PDF format: CloudComputingBigData.pdf

Access to course material: please, follow this link (reserved to attendees)

Access to course discussions: please, follow this link (reserved to attendees)

Follow-up course: Cloud Computing & Big Data Lab


Main page Research activities Publications Talks MSc thesis projects Courses Mentoring Hobby and spare time Write me Last updated on
07 November 2022