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Programming

Code: 106932 ECTS Credits: 6
2024/2025
Degree Type Year
2503743 Management of Smart and Sustainable Cities FB 1

Contact

Name:
Carles Ferrer Ramis
Email:
carles.ferrer@uab.cat

Teachers

Raimon Casanova Mohr
Carlos Casado Martinez

Teaching groups languages

You can view this information at the end of this document.


Prerequisites

Basic computer skills.


Objectives and Contextualisation

In this area, the basic concepts related to Information Technology and Communications (ICT) as tools for the development of city management applications will be introduced, as well as basic notions of algorithmics and application programming.


Learning Outcomes

  1. KM09 (Knowledge) Understand the functioning and correct management of databases.
  2. SM07 (Skill) Solve simple problems for the management of cities by means of computer applications that process and extract information from geospatial data.
  3. SM08 (Skill) Use algorithm and programme analysis techniques to design new algorithmic solutions based on the idea of recursion or specific algorithm design techniques.

Content

1. Introduction to programming

1.1. Variables and data types

1.2. Operators

1.3. Precedence

2. Control structures

2.1. Conditionals

2.2. Loops

3. Structured Data Types I

3.1. Lists

3.2. Dictionaries

4. Functions

5. Algorithmic schemes

6. Files

7. Structured Data Type II

7.1. Sets

7.2. Tuples

 

Activities and Methodology

Title Hours ECTS Learning Outcomes
Type: Directed      
Autonomous work 76 3.04 SM08
Exercises and laboratories 24 0.96 SM08
Theory classes 26 1.04 KM09, SM07, SM08

The teaching methodology will be based on three types of activities:

  • Guided activity: theoretical classes, laboratory, and exercise analysis.
  • Supervised activity: attendance to tutorials and completion of exercises with scheduled follow-up.
  • Autonomous activity: part of student study and case resolution, individually or in groups.

In order to be able to perform a correct assessment of the transversal competencies corresponding to the subject, the students will be proposed to carry out joint work. This activity will allow them to develop the transversal competencies related to group work (T01), becoming responsible for the tasks assigned, respecting the role of the different members of the team, and evaluating critically the work carried out (T05) among them.

The preferred form of communication with students will be the virtual campus combined with the institutional mail of the UAB.

Annotation: Within the schedule set by the center or degree program, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.

Annotation: Within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.


Assessment

Continous Assessment Activities

Title Weighting Hours ECTS Learning Outcomes
Evaluation tests 60% 4 0.16 KM09, SM07, SM08
Laboratory activities 30% 10 0.4 SM08
Supervised activities 10% 10 0.4 SM08

1. Evidence of continuous evaluation
There are two tests that include the five blocks of matter (1,2 in the first test and 3,4,5 in the second test).

Continuous evaluation tests Weight note continuous
assessment
Minimum mark to make an
average
1-3 Introduction programming, control structures, types of data structures I.
50% 4

4-7 Functions, algorithmic schemas, files, types of data structures II.

50% 4


2. Final evaluation mark

Final mark Weight final mark
Continuous evaluation 60%
Class Picks 10%
Laboratory 30%

3. It is considered approved by anyone:

  • have a final mark equal to or greater than 5 and
  • have approved the laboratory activities (minimum 5) i
  • there is no evidence of continuous evaluation below the minimum mark (4.0) to do the average.

4. Assessment of practices

There will be a total of 2 laboratory activities one per part where the algorithm will be asked to bring home prepared for each one of them, which will count as 10% of the laboratory activities mark.

5. Class picks cannot be retrieved.

6. There will be a final exam of the two blocks of theory aimed at recovering the not surpassed part of the continuous evaluation.

7. At the beginning of the academic year, if possible, it will be notified if there is a validation of laboratory activities. In the case of being, the validation of laboratory activities only will be realized to the students who request it and have approved the laboratory activities in the previous course. The weight of the continuous evaluation
in the final mark, in the students with the validation of laboratory activities, becomes 90%.

8. Continuous evaluation dates are set at the beginning of the course and do not have alternative recovery dates in case of non-attendance. If there is any change in programming due to the adaptation to possible incidents, the virtual campus will always be informed about these changes.

9. Notwithstanding other disciplinary measures deemed appropriate, and in accordance with the current academic regulations, irregularities committed by a student that can lead to a variation of the qualification will be classified as zero (0). For example, plagiarizing, copying, copying, ..., an evaluation activity, will imply suspending this evaluation activity with zero (0). Assessment activities qualified in this way and by this procedure will not be recoverable. If it is necessary to pass any of these assessment activities to pass the subject, this subject will be suspended directly, without an opportunity to recover it in the same course.

10. Non-evaluable cases
In case no delivery is made, it will not be included in any laboratory session and no exam will be carried out, the corresponding grade will be "not evaluable". In any other case, "notpresented" counts as a 0 for calculating the weighted average, which will be a maximum of 4.5. Then, participation in an activity evaluated implies that
"not presented" in other activities such as zeros are taken into account. For example, an absence in a laboratory session involves a note for that activity.

11. Pass the course with honors
At the discretion of the teaching staff, passing the course with honors will be awarded to those who obtain a mark greater than or equal to 9.5 in each part, up to 5% of those enrolled in descending order of final grade. They may also be granted in other cases.

12. Examination by a single assessment
Single assessment is not foreseen

Bibliography

  • A. Prieto, A. B. Prieto. Conceptos de informática. Ed. Mc Graw Hill, 2005.
  • Mark Lutz. Learning Python, Fourth Edition. Ed. O'Reilly Media, Inc., 2009.

Software

Python IDLE

 

Language list

Name Group Language Semester Turn
(PAUL) Classroom practices 611 Catalan second semester morning-mixed
(PAUL) Classroom practices 612 Catalan second semester morning-mixed
(TE) Theory 61 Catalan second semester morning-mixed