Teaching plan for the course unit

 

 

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General information

 

Course unit name: Computer Science

Course unit code: 363735

Academic year: 2021-2022

Coordinator: Jose Maria Gomez Cama

Department: Department of Electronic and Biomedical Engineering

Credits: 6

Single program: S

 

 

Estimated learning time

Total number of hours 150

 

Face-to-face and/or online activities

56

 

-  Lecture

Face-to-face and online

 

30

 

-  IT-based class

Face-to-face and online

 

26

Supervised project

44

Independent learning

50

 

 

Recommendations

 

Class participation is particularly relevant since discussion of the concepts being introduced allows for a better understanding of the contents. Besides, attendance to practical sessions is essential, since the contents acquired in the theory sessions can only be fully grasped if practised with computers.

 

 

Competences to be gained during study

 

   -

To be able to resolve problems with initiative and creativity and to take technological decisions in accordance with criteria of cost, quality, safety, sustainability, time and respect for the profession's ethical principles (Instrumental).

   -

To be able to analyse and summarize (Instrumental).

   -

To gain knowledge of basic and technological subjects required to learn new methods and technologies and ensure versatility and the ability to adapt to new situations (Personal).

   -

To be able to design devices and systems to meet information and technology needs in a clinical environment. To establish methods for managing such systems.

Learning objectives

 

Referring to knowledge

— Understand how computers work and be able to distinguish their main components.

 

— Be able to technically assess the computer’s features.

 

— Understand the functions of an operating system and the main differences between those most commonly used.

 

— Become familiar with basic concepts in programming.

 

— Acquire skills to find and correct programming errors.

 

Referring to abilities, skills

— Be able to find a solving algorithm for problems of elementary difficulty. Learn to code it with a set of basic instructions of a specific language.

 

— Use editing, compilation and execution tools to develop programs.

 

— Be able to write programs with a good style, documentation and specifications.

 

 

Teaching blocks

 

1. Hardware

1.1. Computer components

1.2. General concepts in operating systems

2. Computer programming

2.1. Introduction

2.2. Data types

2.3. Variables

2.4. Operators

2.5. Comments

2.6. Basic flow of execution

2.7. Turtle library

2.8. Functions

2.9. Controlling the execution flow

2.10. Data sets

2.11. NumPy library

2.12. SymPy library

2.13. Files

2.14. From script to program

2.15. Input and output

 

 

Teaching methods and general organization

 

During the theory lectures, base programming concepts and numerical methods are explained. This knowledge is applied during the practical laboratory classes. Theory lectures are participatory. Students have access to guide texts and slides used in class. This material has to be studied before attending sessions, so as to make these classes more debate sessions than lectures.

 

 

Official assessment of learning outcomes

 

Practical sessions: 45% + final exam: 45% + problem resolution done in class: 10% 

Students must pass the practical work and the comprehensive examination in order to be eligible to weight the marks.

Repeat assessment

Students that repeat assessment are implicitly renouncing their grades for continuous assessment. The procedure is the same as that for single assessment.

 

Examination-based assessment

Practical sessions: 50% + final exam: 50%.

Students must pass both sections in order to be eligible to weight the marks.

Repeat assessment

Practical sessions: 40% + final exam: 60%. 

Students must pass the final examination to be eligible to weight the marks.