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Programming and Databases

Code: CC4042     Acronym: CC4042     Level: 400

Classification Keyword
OFICIAL Computer Science

Instance: 2020/2021 - 1S Ícone do Moodle Ícone  do Teams

Active? Yes
Web Page: http://www.dcc.fc.up.pt/~slc/aulas/PBD/2021/index.html
Responsible unit: Department of Computer Science
Course/CS Responsible: Master's degree in Bioinformatics and Computational Biology

Cycles of Study/Courses

Acronym No. of Students Study Plan Curricular Years Credits UCN Credits ECTS Contact hours Total Time
E:BBC 3 PE_Bioinformatics and Computational Biology 1 - 6 42 162
M:BBC 14 The study plan since 2018 1 - 6 42 162
M:CTN 0 Official Study Plan since 2020_M:CTN 1 - 6 42 162
M:DS 12 Official Study Plan since 2018_M:DS 1 - 6 42 162

Teaching Staff - Responsibilities

Teacher Responsibility
Sérgio Armindo Lopes Crisóstomo

Teaching - Hours

Theoretical and practical : 3,00
Type Teacher Classes Hour
Theoretical and practical Totals 1 3,00
Sérgio Armindo Lopes Crisóstomo 3,00

Teaching language



Introduction to programming using the Python language. Values, types and expressions. Functions and procedures. Conditionals and selection. Iteration and recursion. Basic data structures and algorithms: data processing, text.
Scientific programming with python.

Database modelling using the entity/relationship model.
Relational database implementaion with SQL. Database queries using the SQL language.

Learning outcomes and competences

Program autonomously in the Python programming language, gaining skills to learn and program in other programming languages.

Ability to model and implement relational databases and their manipulation through the SQL language.

Working method



1. Introduction to Python: variables, expressions and instructions.
2. Interactive use of Python language; defining scrips and short functions.
3. Conditions and logical values; instructions for conditional execution.
4. Cicles and iteration. Examples using turtle graphics.
5. Using pseudo-random numbers; examples for simulation.
6. Numerical solution of equations; implementation of basic algorithms.
7. Processing indexed variables (lists) and text (strings).
8. Writing and reading data as text files; plotting data using external tools (e.g. gnuplot).
9. Recursion.

10. Databases: the ER and EER model.
11. The relational model.
12. Conversion of the EER model to the relational model.
13. The SQL language.

Database access with python:
14. Python and MySQL, connection from Python to MySQL databases.
15. Cursors and manipulation of SQL query results in Python.
16. The MySQLdb module and psycopg2.

Mandatory literature

Allen Downey; How to think like a computer scientist. ISBN: 0-9716775-0-6
Ramez Elmasri; Fundamentals of database systems. ISBN: 9780805317534 pbk

Teaching methods and learning activities

Theoretical teaching with presentation based on projected notes.

Take advantage of examples by developing small programs interactively in Python during presentation classes.

Laboratory classes with computers where students solve small chips with varied problems, with the support of the teacher.

Practical exercises on computer (self-evaluation) to make out of classes and using a platform for automatic validation of programs through unit tests.

Evaluation Type

Distributed evaluation without final exam

Assessment Components

designation Weight (%)
Trabalho prático ou de projeto 30,00
Teste 70,00
Total: 100,00

Amount of time allocated to each course unit

designation Time (hours)
Elaboração de projeto 32,00
Estudo autónomo 88,00
Frequência das aulas 42,00
Total: 162,00

Eligibility for exams

Project development.

Calculation formula of final grade

The final grade (FG) is the weighted average of the grades obtained in the project (Prj) and in the two tests (T1 and T2):

FG = 0.3*Prj + 0.35*T1 + 0.35*T2

If FG < 9.5 (in 20 marks), then students are still eligible for "exame de recurso" (ExR). In this case final grade is:

FG = 0.3*Prj + 0.7*ExR
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