ECTS credits ECTS credits: 3
ECTS Hours Rules/Memories Student's work ECTS: 51 Hours of tutorials: 3 Expository Class: 9 Interactive Classroom: 12 Total: 75
Use languages Spanish, Galician
Type: Ordinary subject Master’s Degree RD 1393/2007 - 822/2021
Departments: Social, Basic and Methodological Psychology
Areas: Basic Psychology
Center Faculty of Psychology
Call: Second Semester
Teaching: With teaching
Enrolment: Enrollable | 1st year (Yes)
• To introduce and get to know the peculiarities of the formal programming languages of Python and Matlab, as well as the specific characteristics of the logic applied in the development of code and programming, with special emphasis on the processes of "decomposition" and "abstraction" of the problem to be solved.
• To develop personal skills in the use of the basic aspects of both programs through the work with different types of data and the handling of variables and matrices, as well as to familiarize the student in the use of logical operators and the iterative and recursive processes that give rise to the use of these programs in data processing and, therefore, in research.
• At the end of the course, the student should be able to develop simple programs for data acquisition. These programs will generate a small interface (i.e. presentation of questionnaires or stimuli on screen) that requires the introduction of answers by the user of the program.
The student must demonstrate ability to perform basic operations and simple comparisons with numerical data contained in variables (i.e. matrices or databases).
What are Python and Matlab. Characteristics of formal languages in Python and Matlab. Decomposition and abstraction as basic tools to solve a problem and create code. Data: types of values and organization in variables. Iterative and recursive processes: use of the main logical and mathematical operators. Towards efficient programming via "testing" and "debugging"
Basic bibliography:
1. Cohen, M. X. (2017). MATLAB for Brain and Cognitive Scientists. MIT Press.
2. Dalmaijer, E. S. (2016). Python for experimental psychologists. Routledge.
3. Borgo, M., Soranzo, A., & Grassi, M. (2012). MATLAB for Psychologists. Springer Science & Business Media.
4. VanderPlas, J. (2016). Python data science handbook: essential tools for working with data. O'Reilly Media
Complementary bibliography:
1. Rosenbaum, D. A., Vaughan, J., & Wyble, B. (2014). MATLAB for behavioral scientists. Routledge.
2. Wallisch, P., Lusignan, M. E., Benayoun, M. D., Baker, T. I., Dickey, A. S., & Hatsopoulos, N. G. (2014). MATLAB for neuroscientists: an introduction to scientific computing in MATLAB. Academic Press.
3. Madan, C. R. (2013). An Introduction to MATLAB for Behavioral Researchers. Sage Publications.
4. Grus, J. (2015). Data science from scratch: first principles with python. O'Reilly Media.
5. Haslwanter, T. (2016). An Introduction to Statistics with Python. Springer International Publishing.
6. Downey, A. B. (2014). Think stats: exploratory data analysis. O'Reilly Media.
7. Peirce, J., & MacAskill, M. (2018). Building experiments in PsychoPy. Sage Publications.
BASIC AND GENERAL COMPETENCES
BC6. To have knowledge that allows students to be original when it comes to developing and implementing ideas, often in a research context.
BC10. To possess the learning skills needed to make progress autonomously in the future.
GC2. To be able to choose an appropriate strategy in order to tackle the problems in the field.
TRANSVERSAL COMPETENCES
TC2. To be able to show an abaility to solve problems and make context-sensitive decisions.
TC5. To be able to update acquired knowledge and skills in accordance with the standards in the field, the profession and the applicable laws.
SPECIFIC COMPETENCES
SC3. To know how to identify and select techniques and instruments specific to the areas of specialization of the master in accordance with the chosen objectives.
SC4. To know how to use and adapt the techniques and instruments of Psychology to deal with specific situations of professional practice in the knowledge domains of the master.
SC5. To be able to analyze and solve complex situations, in specific areas of the master's degree, through the design, programming and implementation of strategies aimed at solving problems.
• Lesson-explanation
• Laboratory work
• Reading and analysis of texts and documents
• Preparation and presentation of reports, tests and works
Continuous evaluation of activities: 25% of the final mark
Evaluation of reports, works and presentations: 75% of the final mark
Students with exemption from attendance: Given the nature of the subject, based on the use of computer tools, there will be no changes in the methodology and system of evaluation. The same work system will be maintained, but using the tools provided by the USC for telematic teaching.
Master Classes 9 hours (attending is required)
Interactive laboratory classes 9 hours (attending is required)
Personal work of the student 48 hours
Work and report preparation 6 hours
Individual and/or small group mentoring sessions 3 hours (attending is required)
In this subject, personal work of the student is a fundamental pillar. Given the eminently practical character of the subject, weekly, if not daily, work is recommended to be able to complete the subject and to maximize the learning of its contents. Likewise, the realization of the suggested exercises after each master class will be key to strengthen the learning of the concepts introduced in the classroom.
Tutoring timetable: consultar horario de titorías actualizado en: https://www.usc.gal/gl/departamento/psicoloxia-clinica-psicobioloxia/di…
Marcos Diaz Lago
Coordinador/a- Department
- Social, Basic and Methodological Psychology
- Area
- Basic Psychology
- marcos.diaz [at] usc.es
- Category
- Professor: Intern Assistant LOSU
| Tuesday | |||
|---|---|---|---|
| 18:00-20:00 | Grupo /CLE_01 | Spanish | Seminar for the Basic Psychology Area |
| Thursday | |||
| 16:00-18:00 | Grupo /CLE_01 | Spanish | Seminar for the Basic Psychology Area |