Programming for Data Science (PDS-DAB)

Área

AC Gestão > UC Mestrados

Activa nos planos curriculares

Data Analytics for Business > Data Analytics for Business > 2º Ciclo > Unidades Curriculares Obrigatórias > Programming for Data Science

Nível

2º Ciclo (M)

Tipo

Estruturante

Regime

Semestral

Carga Horária

Aula Teórica (T): 0.0 h/semana

Aula TeoricoPrática (TP): 3.0 h/semana

Trabalho Autónomo: 121.0 h/semestre

Créditos ECTS: 6.0

Objectivos

L0 1.Consolidate main programming concepts
L0 2.Understand programming techniques to manipulate and visualize data
L0 3.Understand main algorithms that implemented in programming languages
L0 4.Solve problems using programming and algorithms.

Programa

1.Introduction to Programming
2.Object Oriented Programming
3.Extract, clean, prepare, and mine data
4.Data Visualization
5.Text and image processing
6.Machine Learning algorithms
a.Regressions and Classification
b.Unsupervised learning
7.Introduction to web programming

Metodologia de avaliação

All the classes are theoretical and practical. Lectures typically have a small presentation of theory, context of usage and techniques used. Lecturer also illustrate some practical cases. In this demonstration, the lecturer needs to use computer and adequate compilers/interpreters and IDE. Students may or may not follow this presentation in his own desktop. Then, there are several exercises where students are supported by the lecturer. Individual work is complemented with groupworks. Laboratory work may be individual or group work. Students also must perform a project in group.
Students performance evaluation will derive from laboratory work, submitted during classes (30%) the assigned team-works project presented during the semester (40%) and from a final individual exam (30%).

Bibliografia

Principal