Checking date: 20/05/2022


Course: 2022/2023

Programming for Business
(17590)
Study: Bachelor in Management and Technology (351)


Coordinating teacher: MEDINA DOMINGUEZ, FUENSANTA

Department assigned to the subject: Computer Science and Engineering Department

Type: Compulsory
ECTS Credits: 6.0 ECTS

Course:
Semester:




Skills and learning outcomes
Description of contents: programme
1.Data Structures: Vector, Factor, Matrix, Array, List, DataFrame 2. Programming Structures 2.1 Conditional structure: if 2.2 Loops: for, while, repeat 3. Complex Programming Structures 4. Functions 4.1 Definitions 4.2 Variables and parameters 4.3 Infix 4.4 Calls 5. Recursive function 6. Input, output and data storage (keyboard, files) 7. Graphics
Learning activities and methodology
This course will consist of regular lectures, exercises and lab classes. Regular lectures will provide the students with the theoretical background required to acquire the outlined competences throught exercices. Lab classes will give the student the chance to develop practical skills on program analysis, design, testing and documentation.
Assessment System
  • % end-of-term-examination 0
  • % of continuous assessment (assigments, laboratory, practicals...) 100
Calendar of Continuous assessment
Basic Bibliography
  • Grolemund, G., Wickham, H. R for Data Science: Import, Tidy, Transform, Visualize, and Model Data. . O'Reilly. 2016
  • Lander, J. R for Everyone: Advanced Analytics and Graphics. . Addison Wesley Data & Analytics Series. 2017
  • Meys, J., Vries, A. R for dummies. John Wiley & Sons. 2012
  • Murdoch Braun. A first course in statistical programming with R. Cambridge University Press. . 2007
  • Rizzo, Maria . Statistical computing with R . Chapman & Hall/CRC. 2007
  • Vries, A., Meys, J. R for Dummies. 2015.
Recursos electrónicosElectronic Resources *
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The course syllabus may change due academic events or other reasons.