ECTS credits ECTS credits: 6
ECTS Hours Rules/Memories Student's work ECTS: 99 Hours of tutorials: 3 Expository Class: 24 Interactive Classroom: 24 Total: 150
Use languages Spanish, Galician
Type: Ordinary Degree Subject RD 1393/2007 - 822/2021
Departments: Electronics and Computing
Areas: Computer Science and Artificial Intelligence
Center Faculty of Physics
Call: First Semester
Teaching: With teaching
Enrolment: Enrollable | 1st year (Yes)
General objectives: To introduce the knowledge of the basic concepts of computer science and in the resolution of problems by means of algorithms.
Specific objectives: To achieve that students are able to design, code and test programs of average complexity, which will be developed in various subjects of the degree.
Learning outcomes: Each student will demonstrate
- Who has developed basic programming skills.
- That he is capable of solving problems whose solution does not derive from the application of a standardized procedure.
- That he will present original solutions
- That he will plan and conduct your own learning
- That he will employ new technologies.
- That he will argue from rational criteria.
The following website will be used in the interactive lab sessions:
https://persoal.citius.usc.es/eva.cernadas/informaticaparacientificos/
Exhibition Classes
I. Python programming languages.
- Installation and preparation of the development environment. Modules.
- Data types and expressions.
- Control instructions.
- Strings and files.
- Functions.
- Classes.
- Lists and dictionaries.
- Other data structures.
- Graphics with Python. Matplotlib.
Introduction to computer science.
- Algorithms.
- Programming languages.
- Programming environments.
- Operating Systems.
- Computer Networks.
- The Web.
Interactive classes: programming in Python
- Week 1: Interactive Python environment (arithmetic operations, data types)
- Week 2: Numerical calculation with NumPy.
- Week 3: Graphical representation with Matplotlib. Symbolic calculus with Sympy.
- Week 4: Basic programs in Python.
- Week 5: Exercises with lists. Measuring the time of a program.
- Week 6: Matrixes. Interpolation. Adjustment to functions.
- Week 7: Input/Output from files.
- Week 8: Definition of functions. Creation of modules.
- Week 9: Linear Regression.
- Week 10: Sum of a series. Numerical calculation of derivatives and integrals. Newton's method.
- Week 11: Advanced graphical representation. Data management with Pandas.
- Week 12: Numerical methods and other exercises.
- Week 13: Problems of mechanics, thermodynamics and optics.
Basic Bibliography
Prieto Espinosa A et al: Introducción a la Informática. Editorial McGraw-Hill 2006.
Marzal A, Gracia I: Introducción a la programación con Python. (http://repositori.uji.es/xmlui/bitstream/10234/102653/1/s93.pdf)
Additional Bibliography
- García Molina JJ, Montoya Dato FJ, Fernández Alemán JL, Majado Rosales MJ: “Una introducción a la programación. Un enfoque algorítmico”. Ed Thomson 2005.
- Silberschatz A, Galvin PB, Gagne G: “Sistemas Operativos”. Ed McGrawHill 2002.
- Forouzan BA: “Transmisión de Datos y Redes de Comunicaciones”. Ed McGrawHill 2007.
- Castro E: “HTML, XHTML & CSS”. Ed Anaya 2007.
Resources on the Web
Solved Python exercises: "http://persoal.citius.usc.es/eva.cernadas/informaticaparacientificos"
Women in Computer Science:
* Conferencia: Ada Lovelace e as pioneiras informáticas
* Blog Mujeres con ciencia.
BASIC AND GENERAL
CB1 - Demonstrate possession and understanding of knowledge in an area of study which is at the foundation of general secondary education, and is usually at a level which, while supported by advanced textbooks, also includes some aspects involving knowledge from the cutting edge of the field of study.
CB2 - Be able to apply their knowledge to their work or vocation in a professional way and possess the skills that are usually
demonstrated by developing and defending arguments and solving problems within their area of study.
CB3 - Have the ability to gather and interpret relevant data (usually within their area of study) to make judgments that include reflection on relevant social, scientific or ethical issues.
CB4 - Be able to convey information, ideas, problems and solutions to both specialist and non-specialist audiences.
CB5 - have developed those learning skills necessary to undertake further study with a high level of competence.
degree of autonomy.
CG3 - Apply both the theoretical-practical knowledge acquired and the capacity for analysis and abstraction in the definition and posing of problems and in the search for their solutions in both academic and professional contexts.
TRANSVERSALS
CT1 - Acquiring analysis and synthesis skills.
TC2 - Have the capacity to organize and plan.
TC4 - Be able to work in a team.
TQ5 - Develop critical thinking skills.
SPECIFIC
SG2 - Be able to clearly handle orders of magnitude and make appropriate estimates in order to develop a clear perception of situations that, although physically different, show some analogy, allowing the use of known solutions to new problems.
SG5 - Be able to do the essentials of a process or situation and model it and make the required approaches to reduce the problem to a manageable level. Demonstrate critical thinking to build physical models.
CE7 - Be able to use computer tools and develop software programs.
CE8 - Be able to manage, search and use bibliography, as well as any relevant information source and apply it to research and technical development projects.
The general methodological guidelines established in the USC Physics Degree Report will be followed. The classes will be face-to-face and the distribution of expository and interactive hours follows the specifications in the Grade Report.
The teaching methodology will be based on the individual work of each student, on discussions with the teaching staff in class and on individual tutorials. It will be supported by all the information provided by the teaching staff through the virtual course of the subject (Moodle da Campus Virtual).
For each subject, the teaching staff will prepare the contents, explain the objectives of the subject in class, and suggest bibliography on which to rely.
The practices will be done in the Computer Room of the faculty using the Python programming language. The students will work in individual positions with the constant support of the teaching staff following a learning methodology based on examples.
Tutorials may be face-to-face or telematic. If they are telematic they will require an appointment. This is also recommended for face-to-face tutorials.
The evaluation of the course will consist of a part dedicated to theory and another part dedicated to practice. The theory part (30%) will be evaluated in a final exam. The practical part (70%) can be evaluated both in the final exam and continuously in the interactive classes. When the student obtains more than 6 points out of 10, she can decide to take the practical part in the final exam or not. In order to pass the subject, it is essential to obtain 5 points out of 10 in the final grade of the subject, but with a minimum of 3 points out of 10, in the theory part.
In case you get 0 points during the continuous assessment process (either because you do not attend or because you do not perform the requested tasks), the final grade of the subject will be the grade of the final exam. In this case, in order to pass the course, it is essential to obtain at least 5 points out of 10, in the theory part of the exam, but with a minimum of 3 points out of 10, in the theory part.
The score obtained during the continuous assessment process will be kept for the July special session of the same academic year in which it was obtained.
The score will be "NO PRESENTADO" for students who do not take the final exam and have not attended any of the continuous assessment activities, and "SUSPENSO" (not pass) when they do not take the final exam but have attended one of the continuous assessment activities.
The course consists of 4 hours per week (2 hours of lectures dedicated to blackboard classes and 2.5 hours of interactive classes for the creation of computer programs), during 12 weeks, plus 2h of additional interactive classes, which gives a total of 24 hours of lectures and 32 hours of interactive classes. There are also 4 tutorial hours dedicated to problem solving. In addition, each student will have to work individually other 2.5 hours/week. In total this would be 7 hours/week x 12 weeks + 2 interactive hours + 4 tutorial hours = 90 hours.
It is recommended that students individually design, implement and verify all the proposed exercises.
In order to perform the practical part of the subject, it is mandatory to have an account on the computing system of the USC.
Pablo Garcia Tahoces
Coordinador/a- Department
- Electronics and Computing
- Area
- Computer Science and Artificial Intelligence
- Phone
- 881813580
- pablo.tahoces [at] usc.es
- Category
- Professor: University Professor
Manuel Fernandez Delgado
- Department
- Electronics and Computing
- Area
- Computer Science and Artificial Intelligence
- Phone
- 881816458
- manuel.fernandez.delgado [at] usc.es
- Category
- Professor: University Lecturer
Eva Cernadas García
- Department
- Electronics and Computing
- Area
- Computer Science and Artificial Intelligence
- Phone
- 881816459
- eva.cernadas [at] usc.es
- Category
- Professor: University Lecturer
Victor Jose Gallego Fontenla
- Department
- Electronics and Computing
- Area
- Computer Science and Artificial Intelligence
- victorjose.gallego [at] usc.es
- Category
- Professor: Intern Assistant LOSU
| Monday | |||
|---|---|---|---|
| 13:00-14:00 | Grupo /CLE_01 | Spanish | Classroom 130 |
| 15:30-18:00 | Grupo /CLIL_04 | Galician | 3 (Computer Science) |
| 18:00-20:30 | Grupo /CLIL_05 | Galician | 3 (Computer Science) |
| Tuesday | |||
| 13:00-14:00 | Grupo /CLE_02 | Spanish | Classroom 6 |
| 16:00-18:30 | Grupo /CLIL_02 | Galician | 3 (Computer Science) |
| Wednesday | |||
| 13:00-14:00 | Grupo /CLE_01 | Spanish | Classroom 130 |
| 16:00-18:30 | Grupo /CLIL_06 | Galician | 3 (Computer Science) |
| Thursday | |||
| 13:00-14:00 | Grupo /CLE_02 | Spanish | Classroom 6 |
| 16:00-18:30 | Grupo /CLIL_01 | Galician | 3 (Computer Science) |
| Friday | |||
| 16:00-18:30 | Grupo /CLIL_03 | Galician | 3 (Computer Science) |
| 01.21.2025 09:00-13:00 | Grupo /CLE_01 | Classroom 0 |
| 01.21.2025 09:00-13:00 | Grupo /CLE_01 | Classroom 130 |
| 01.21.2025 09:00-13:00 | Grupo /CLE_01 | Classroom 6 |
| 01.21.2025 09:00-13:00 | Grupo /CLE_01 | Classroom 830 |
| 06.10.2025 09:00-13:00 | Grupo /CLE_01 | Classroom 0 |
| 06.10.2025 09:00-13:00 | Grupo /CLE_01 | Classroom 6 |
| 06.10.2025 09:00-13:00 | Grupo /CLE_01 | Classroom 830 |