Cloud Computing and Big Data Analytics
Spring 2026

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 the degrees: Master in Innovation and Research in Informatics , Master in Data Science , Master in Informatics Engineering , and Master in Artificial Intelligence .

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
• Research topics
• Course Project

Lecturer

Angel Toribio-González  ( )

Tentative calendar!!!

	Class topics and laboratory sessions
	Thursday (Lectures)		Friday (Laboratory)
February	12	Presentation of the subject	13	Basic knowledge toolbox
	19	Introduction to Cloud Computing	20	Doors in the cloud
	26	Virtualization	27	Basic use of the cloud
March	5	Cloud computing architecture	6	Use of services programmatically through their API
	12	Cloud computing architecture	13	Deployment of a custom web app using additional cloud services
	19	Cloud computing architecture	20	Running a custom web app in the cloud
	26	Best practices for creating SaaS The twelve factor methodology Service oriented architectures	27	Continuous Integration, Continuous Delivery, and Observability
April	2	Easter break	3	Easter break
	9	Mid-term exams	10	Mid-term exams
	16	Cloud security	17	Serverless applications
	23	Cloud security	24	Student project development Presence required
	30	Student project development No class. Use it to work on your project.	1	Labor day
May	7	It has the schedule of a Friday Student project development Presence required	8	FIB festivity
	14	Research topics presentation	15	Student project development Presence required
	21	Student project development No class. Use it to work on your project.	22	Student project development Presence required
	28	Student project development No class. Use it to work on your project.	29	Student project Project defense presence required
June			10	Student project Technical interview 8:00 - 10:00 (25 min pre-scheduled slot) presence required to pre-scheduled interviews Final Exam 10:00 - 11:00

Evaluation