bachelor in artificial intelligence and data science la salle campus barcelona

Bachelor in Artificial Intelligence and Data Science

Computing infrastructures

Description: 
Computing infrastructures constitute the foundation on which modern computer systems operate, including hardware, communication networks, and distributed and cloud environments. The objective of this course is to provide students with a global and integrated view of the main technologies that enable contemporary computing, allowing them to understand how these systems are organized, how they interact, and how they scale. The course first analyzes the architecture and internal structure of computers, studying CPU design, memory hierarchy, and input/output devices. It then introduces computer network architectures and technologies, communication protocols, and the devices involved in data transmission. Finally, distributed environments and cloud computing are studied, addressing concepts such as virtualization, service models, and cloud architectures. From a practical perspective, the course includes activities and exercises focused on the analysis and decision-making processes related to computing infrastructures, applying theoretical knowledge to real-world situations. Through a practical project, students work on aspects related to the design, evaluation, and justification of infrastructure solutions, developing a critical understanding of the advantages and limitations of different technological alternatives. In addition, multiple examples and use cases are introduced to deepen the understanding of the theoretical concepts covered and to relate them to computer systems and computing platforms currently used in the fields of artificial intelligence and data science.
Type Subject
Primer - Obligatoria
Semester
Second
Course
1
Credits
6.00
Previous Knowledge

To take the course Computing Infrastructures, it is recommended that the student has the following prior knowledge:
- Basic concepts of programming and algorithmics.
- Introductory knowledge of computer systems and general computer usage.
- Basic notions of operating systems and networks (at user level).

Objectives

Students enrolled in the course Computing Infrastructures are expected to acquire the following knowledge and skills:
1. Understand the architecture and internal organization of computing systems, as well as the role of their main components.
2. Become familiar with the concepts, technologies, and terminology associated with computer architectures, networks, and distributed systems.
3. Analyze the advantages and limitations of different computing infrastructure solutions depending on the application context.
4. Apply theoretical knowledge to the resolution of practical problems related to architectures, networks, and cloud environments.
5. Communicate correctly using appropriate technical terminology, both orally and in writing.
6. Develop technical work in a structured, well-justified, and properly documented manner.
7. Work effectively both individually and in teams to solve technical problems.

Contents

During the academic year, the following contents will be developed, structured into three main blocks:
1. Computer Architecture
- Organization and structure of computing systems.
- CPU design.
- Memory systems.
- Input/output devices.
2. Computer Network Technologies and Architectures
- Network architecture models.
- Communication protocols.
- Network technologies and devices.
- Performance, reliability, and basic security.
3. Distributed and Cloud Environments
- Distributed systems.
- Virtualization.
- Cloud computing.
- Cloud architectures and service models.

Methodology

The teaching methodology is oriented toward fostering active and progressive learning by the student.

Lectures are combined with problem-solving sessions and practical activities, both in the classroom and in applied working environments. Theoretical explanations are complemented with real examples and practical cases that help contextualize the concepts studied.

Throughout the course, students will complete individual and group exercises and actively participate in practical sessions, where technical decision-making will be addressed by applying the acquired knowledge.

The methodology is mainly based on:
- Lectures.
- Problem-solving and exercises.
- Guided practical activities.

Evaluation

The course consists of two distinct parts:
- Theory
- Practice (final project)

The assessment of both parts is independent, and to pass the course it is necessary to pass both with a minimum grade of 5.

The final grade of the course is calculated according to the following formula:

Final_Grade = 80% · Theory + 20% · Practice

Theory Assessment

The Theory grade is calculated based on the three thematic blocks:

Theory_Grade = 40% · Block1 + 25% · Block2 + 35% · Block3

It is an essential requirement to pass each block independently.

Each block is assessed through:
- Continuous Assessment tests (CA).
- Final exam of the ordinary examination period.
- Recovery exam in the extraordinary examination period, if applicable.

The mechanisms for exemption, weighting, and recovery follow the regulations specified in the course assessment system.

Practice Assessment

The practical component represents 20% of the final grade and is based on:
- Technical project report.
- Validation interview.
- Attendance at practical sessions.

To pass the practical component, a minimum grade of 5 is required.

Evaluation Criteria

The learning outcomes for the subject are the following:

Objective 1
The student must demonstrate knowledge of the basic concepts and terminology of computing architectures and infrastructures.
The student must be able to identify the main components of a computer system and their function.

Objective 2
The student must be able to analyze and compare different computer architectures.
The student must understand the operation of networks and distributed systems.
The student must know the fundamental principles of cloud computing.

Objective 3
The student must be able to apply theoretical knowledge to the resolution of practical problems.
The student must be capable of making reasoned technical decisions based on context.

Objective 4
The student must communicate correctly using appropriate technical vocabulary.
The student must be able to explain and defend solutions orally.

Objective 5
The student must submit structured, clear, and well-justified reports.
The student must demonstrate synthesis skills and technical rigor in documentation.

Objective 6
The student must be able to work effectively in teams, distributing tasks and integrating knowledge.
The student must demonstrate responsibility and collaborative skills in the development of the practical project.

Basic Bibliography

PATTERSON, D.A. & HENNESSY, J.L. Computer Organization and Design: The Hardware/Software Interface, 5th Edition, Morgan Kaufmann, ISBN-13: 978-0124077263, 2013
HENNESSY, J.L. & PATTERSON, D.A. Computer Architecture: A Quantitative Approach, 6th Edition, Morgan Kaufmann, ISBN: 9351073653, 2018
TANENBAUM, A.S. & BOS, H. Modern Operating Systems, 4th Edition, Pearson, ISBN: 978-0133591620, 2014
STALLINGS, W. Operating Systems: Internals and Design Principles, 9th Edition, Pearson, ISBN: 978-0134670959, 2017
SILBERSCHATZ, A., GALVIN, P.B. & GAGNE, G. Operating System Concepts, 10th Edition, Wiley, ISBN: 978-1119454083, 2018
STALLINGS, W. Data and Computer Communications, 10th Edition, Pearson, ISBN: 978-0133506488, 2013
KUROSE, J.F. & ROSS, K.W. Computer Networking: A Top-Down Approach, 7th Edition, Pearson, ISBN: 978-0135926475, 2020
FOROUZAN, B.A. Data Communications and Networking, 5th Edition, McGraw-Hill, ISBN: 978-0073376226, 2013
KUBERNETES: Up and Running: Dive into the Future of Infrastructure, 3rd Edition, O'Reilly, ISBN: 978-1098106732, 2022
RAJ, P. & KUMAR, G. Cloud Computing: Principles and Paradigms, Wiley, ISBN: 978-1119288588, 2017
VOGELSANG, T. Distributed Systems: Principles and Paradigms, 2nd Edition, Pearson, ISBN: 978-0132392273, 2006
AMAZON WEB SERVICES (AWS). AWS Well-Architected Framework, Online Documentation, 2023.
CISCO NETWORKING ACADEMY. CCNA Exploration Curriculum, Cisco Press, Online Resource.
COMER, D.E. Computer Networks and Internets, 6th Edition, Pearson, ISBN: 978-0133587937, 2014
NIELSEN, M.A. & CHUANG, I.L. Quantum Computation and Quantum Information, Cambridge University Press, ISBN: 978-1107002173, 2010

Additional Material