Introduction to Data Science

Code:

CC4060

Acronym:

CC4060

Level:

400

Keywords
Classification	Keyword
OFICIAL	Computer Science

Instance: 2018/2019 - 1S

Active?	Yes
Web Page:	http://www.dcc.fc.up.pt/~maraujo/ids18/
Responsible unit:	Department of Computer Science
Course/CS Responsible:	Master in Data Science

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
M:BBC	17	The study plan since 2018	1	-	6	42	162
M:DS	20	Official Study Plan since 2018_M:DS	1	-	6	42	162

Teaching language

Suitable for English-speaking students

Objectives

Students will obtain a global perspective on the different steps of a Data Science project. For each of these steps, some of the main techniques and methods will be presented while further details will be addressed in more specific courses.

Learning outcomes and competences

Students should know all the steps in a typical data science project and the most common operations on each stage. They should understand the different problems in the scope of a typical data scientist job and develop the required critical thinking to discuss the pros and cons of the each approach.

Working method

Presencial

Program

Mandatory literature

Torgo Luís; Data mining with R. ISBN: 978-1-4398-1018-7

Teaching methods and learning activities

Tutorial classes with theory exposition and problem solving activities.

Evaluation Type

Distributed evaluation with final exam

Assessment Components

designation	Weight (%)
Teste	50,00
Trabalho prático ou de projeto	50,00
Total:	100,00

Amount of time allocated to each course unit

designation	Time (hours)
Elaboração de projeto	78,00
Estudo autónomo	42,00
Frequência das aulas	42,00
Total:	162,00

Eligibility for exams

Calculation formula of final grade