Data Bases and Programming

Code:

2MADSAD02

Acronym:

BDP

Keywords
Classification	Keyword
OFICIAL	Information Technology

Instance: 2020/2021 - 1S

Active?	Yes
Responsible unit:	Agrupamento Científico de Matemática e Sistemas de Informação
Course/CS Responsible:	Master in Modeling, Data Analysis and Decision Support Systems

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
MADSAD	1	Bologna Official Syllabus	1	-	7,5	56	202,5

Teaching language

English

Objectives

The main aim of the course "Databases and Programming" is to provide the MSc student with the skills on Database Management Systems (DBMS),
with particular emphasis on relational databases, as well as some basic training about Programming.

Within the topic of DBMS, MSc students will acquire knowledge about analysis methologies for modeling problems, as well as the query language for relational databases SQL.

MSc students will learn R programming language to enable them to use the potential available to perform processing, graphing and modeling of data. They will also learn howto import/export data from various sources according to several formats.
The ability of R to connect to relational databases is also discussed.
Master's students should be able to create their own functions to solve problems posed in exercises and practical work.
By the end of the course students will be able to implement algorithms using R programming language.

Learning outcomes and competences

MSc students will be able to master the key concepts on database management systems . They acquire the skills to design a database for specific problems using the methodologies presented in class. They will be able to build SQL queries to obtain information with certain criteria from databases.

Under the programming scope, MSc students will learn about the R programming language and how to  implement algorithms. They will master the main elements of the R programming language in the context of information processing, graphing, and import and export data.

Working method

Presencial

Program

Programming

* Basic concepts : expressions , operators , assignment statement .
* Vectors : value types (numeric , character , etc. ) , length and element names
* Indexing: by numbers , names and conditions
* Complex objects : arrays , factors , data.frames , arrays and lists.
* Simple functions : mathematical ( exp ) , statistics (mean , sd ) , the ifelse function , functions "vectorized"
* Complex functions : Vectoring Function : apply , sapply , summarization functions by and aggregate.
* Reading and writing data of different types and from various sources.
* Graphical representation of data : different types of graphs , eg . 's scatter plot , bar graphs , boxplots , histograms , etc. .
* Access to packages of functions: library and require.
* Control Structures program flow : the if statement , the loops ( while, for, etc. )
* Object oriented: objects , classes and methods, methods and states, inheritance and superclass .
* Debugging Programs : R facilities to detect functional errors in programs developed by the user . The debug function and debug browser .
* Building graphical user interfaces for programs.

Databases
Fundamentals of Databases
Data Modeling . Drawing diagrams and Entity Relationship (E / R ) .
The Relational Model of Databases
Transformation of a Model E / R in a table schema
Query languages: SQL
SQL -related parts
Data Definition DDL ( data definition language ) create table ....
data manipulation DML ( data manipulation language ) ... insert into , update
management of access to information DCL ( data control language) , grant ...
Queries databases using SQL
queries involving a table , queries with joins involving multiple tables
queries with subqueries without interdependence between variables and with interdependence.
summarization queries .

Installation and System Configuration Management Databases ( SQBD )
MySQL
The SQLServer Express Edition
Communication with the DBMS using ODBC

Mandatory literature

Luís Fernando Rainho Alves Torgo; Data mining with R. ISBN: 978-1-4398-1018-7
James R. Groff; Using SQL. ISBN: 0-07-881524-X

Teaching methods and learning activities

Theoretical-practical classes, with a component of oral exposure of the concepts and examples, complemented with practical exercises solving with computer support.

Evaluation Type

Distributed evaluation with final exam

Assessment Components

Designation	Weight (%)
Teste	60,00
Trabalho escrito	40,00
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Estudo autónomo	70,00
Frequência das aulas	42,00
Trabalho escrito	50,00
Total:	162,00

Eligibility for exams

Final grade greater than or equal to 9.5, with the exam grade greater than or equal to 7.

Calculation formula of final grade

The Final Grade (NF) on this course is computed by the following formula:

NF = 0.4 * 0.6 * NP + NE

in which,
NP is the practical assignments grade 
and NE is the grade taken in the exam

NE should be at least 7  (NE>7)

The practical assignments grade is the aritmetic mean of the grades taken at each of two assignments (assign1 and assign2)

NP =  0.5 * assign1 + 0.5 * assign2

Classification improvement

Students can try to improve this course grade  using the special exam epoch (recurso - of appeal)

By default standard formula is used to calculate the final grade. If the student you want to stay with the exam grade, he should contact the teacher to prepare a more complete exam.