Checking date: 20/05/2024


Course: 2024/2025

Object-oriented programmin
(19359)
Master in Applied Artificial Intelligence (Plan: 475 - Estudio: 378)
EPI


Coordinating teacher: GARCIA OLAYA, ANGEL

Department assigned to the subject: Computer Science and Engineering Department

Type: Additional training
ECTS Credits: 2.0 ECTS

Course:
Semester:




Requirements (Subjects that are assumed to be known)
None
Objectives
- Knowledge of fundamentals of imperative programming from an object oriented point of view. - Basic knowledge of the syntax of an object oriented programming language. - Knowledge of best programming practices and code style - Ability to break down a real problem by following an object oriented methodology, in order to code it into a computer program. - Ability to understand technical documents and to reuse third parties programming code and libraries.
Skills and learning outcomes
Description of contents: programme
1. Introduction to Python 2. Flow control: conditionals and loops 3. Simple data structures 4. Functions 5. Object Oriented Programming
Learning activities and methodology
Learning activities: AF1: Teacher class presentations with computer and audiovisual support AF2: E-learning AF3: Lectures AF4: Lab exercises AF5: Tutorship AF7: Individual and autonomous work AF8: Final and partial exams Teaching Methodologies: MD1: Classroom Lectures (in a synchronous online teaching mode) using computer and audiovisual aids to develop the main concepts of the subject, with bibliographic references provided to supplement student learning. MD2: Critical Reading of texts recommended by the course professor. MD3: Case Study and Problem Solving of practical cases, problems, etc., posed by the professor, either individually or in groups. MD4: Exposition and discussion in class, moderated by the professor, on topics related to the course content as well as practical cases. MD5: Preparation of projects and reports, either individually or in groups. MD6: Specific e-learning activities, including viewing recorded content, self-correction activities, participation in forums, and any other online teaching mechanisms.
Assessment System
  • % end-of-term-examination 50
  • % of continuous assessment (assigments, laboratory, practicals...) 50
Calendar of Continuous assessment
Basic Bibliography
  • Ana Bell. Get Programming Learn to code with Python. Manning publications. 2018
  • John S. Conery. xplorations in Computing: An Introduction to Computer Science and Python Programming. CRC Press. 2014
Recursos electrónicosElectronic Resources *
(*) Access to some electronic resources may be restricted to members of the university community and require validation through Campus Global. If you try to connect from outside of the University you will need to set up a VPN


The course syllabus may change due academic events or other reasons.