Cloud Computing and Big Data Analytics
Spring 2025

Cloud computing is a service model for large-scale distributed computing based on concentrated infrastructure and a set of collaborative services over which applications can be deployed and run over the network.

This course about Cloud computing has a mainly practical approach dealing with the related technologies. While most computer applications can be deployed in the cloud using the concepts explained, the classes pay particular attention to the creation of Big Data Analytics applications on the Cloud. It is offered to students of both degrees: Master in Innovation and Research in Informatics and Master in Data Science .

In the lectures of this course, the students learn the principles and the state of the art of large-scale distributed computing in a service-based model. Students will study how scale affects system properties, models, architecture, and requirements.

In the laboratory sessions of this course, the students gain a practical view of the latest in Cloud technology to implement a prototype that meets a business idea created by the student.

Class Contents

• Syllabus.
• QuickStart: Hands-on experience for the students of the master's course enrolled on this subject.
• Laboratory assignments.
• Course Project.

Lecturer

Angel Toribio-González  ( )

Tentative calendar!!!

	Class topics and laboratory sessions
	Monday (Lectures)		Wednesday (Laboratory)
February	10	Presentation of the subject	12	Environment configuration and warm up
	17	Introduction to Cloud Computing	19	Basic knowledge toolbox
	24	Virtualization	26	Doors in the cloud
March	3	Cloud computing architecture	5	Basic use of the cloud
	10	Cloud computing architecture	12	Use of services programmatically through their API
	17	Cloud computing architecture	19	Deploy a custom web app using additional cloud services
	24	Best practices for creating SaaS The twelve factor methodology Service oriented architectures	26	Run a custom web app in the cloud
April	31	Cloud security	2	Mid-term exams
	7	Mid-term exams	9	Continuous Integration, Continuous Delivery, and Observability
	14	Easter break	16	Easter break
	21	Easter break	23	Programming your cloud infrastructure
	28	Cloud security	30	Student project development
May	5	Student project development	7	Student project development
	12	Research topics presentation	14	Student project development
	19	Student project development	21	Student project development
	26	Student project Final presentation presence required	28	Student project Technical interview 8:00 - 12:00 (25 min pre-scheduled slot) presence required to pre-scheduled interviews
June			10	Final Exam 08:00 - 11:00

Evaluation