Programming and Databases

Code:

CC4042

Acronym:

CC4042

Level:

400

Keywords
Classification	Keyword
OFICIAL	Computer Science

Instance: 2023/2024 - 1S

Active?	Yes
Web Page:	http://www.dcc.fc.up.pt/~slc/aulas/PBD/index.html
Responsible unit:	Department of Computer Science
Course/CS Responsible:	Master 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	1	PE_Bioinformatics and Computational Biology	1	-	6	42	162
M:A_ASTR	10	Study plan since academic year 2023/2024	1	-	6	42	162
			2
M:BBC	18	The study plan since 2018	1	-	6	42	162
M:CTN	1	Official Study Plan since 2020_M:CTN	1	-	6	42	162
			2
M:DS	15	Official Study Plan since 2018_M:DS	1	-	6	42	162
M:ECAD	3	Study plan since 2021/2022	2	-	6	42	162

Teaching language

English

Objectives

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

Presencial

Program

Python:
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. 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.
9. Recursion.

Databases:
10. Databases: the ER and EER model.
11. The relational model.
12. The SQL language.

Database access with python:
13. Python and MySQL, connection from Python to MySQL databases.
14. Cursors and manipulation of SQL query results in Python.

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	10,00
Teste	90,00
Total:	100,00

Amount of time allocated to each course unit

designation	Time (hours)
Elaboração de projeto	30,00
Estudo autónomo	90,00
Frequência das aulas	42,00
Total:	162,00

Eligibility for exams

Required to obtain a minimum grade of 35% in each of the tests T1 and T2.

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 = 0.1*Prj + 0.6*T1 + 0.3*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 = 0.1*Prj + 0.9*ExR

Special assessment (TE, DA, ...)

Students with special circumstances should discuss their situation with the Professor.

Classification improvement

The final grade "Melhoria de Classificação" (CM) is the weighted average of the grades obtained in the project (Prj), and in the exam "Melhoria de Classificação" (Exm):

CM = 0.1*Prj + 0.9*Exm

Observations

Jury: Sérgio Crisóstomo, Eduardo Marques