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Cursus: INFOMDSS
INFOMDSS
Data Science and Society
Cursus informatieRooster
CursuscodeINFOMDSS
Studiepunten (ECTS)7,5
Categorie / NiveauM (Master)
CursustypeCursorisch onderwijs
VoertaalEngels
Aangeboden doorFaculteit Betawetenschappen; Graduate School of Natural Sciences;
Contactpersoondr. M.R. Spruit
Telefoon+31 30 2533708
E-mailM.R.Spruit@uu.nl
Docenten
Docent
dr. M.J.S. Brinkhuis
Overige cursussen docent
Blok
3  (06-02-2017 t/m 21-04-2017)
Aanvangsblok
3
TimeslotB: DI-ochtend, DO-middag, DO-namiddag
Onderwijsvorm
Voltijd
OpmerkingPlease read HERE
for the latest course information.
Cursusinschrijving geopendvanaf 30-10-2016 t/m 27-11-2016
AanmeldingsprocedureOsiris
Inschrijven via OSIRISJa
Inschrijven voor bijvakkersJa
VoorinschrijvingJa
Na-inschrijvingJa
Na-inschrijving geopendvanaf 23-01-2017 t/m 24-01-2017
WachtlijstJa
Plaatsingsprocedureadministratie onderwijsinstituut
Cursusdoelen
At the end of this course, you will be able to:
  1. Understand the role of data science and its societal impact
  2. Recognise the knowledge discovery processes in applied data science
  3. Identify trends and developments in big data technologies
  4. Apply selected big data technologies to solve real-world problems
Inhoud
This is the introductory course for the Applied Data Science profile. As such, it's primary objective is to inspire and introduce you to the emerging domain of Applied Data Science. The course balances between Big Ideas and their feasibility due to the Big Diversity of its qualifying students. On the one hand it aims to trigger your enthousiasm for applied data science, and to inspire you to aim for societal impact through data science. On the other hand, it needs to provide you with a core set of information science essentials to properly understand big data technologies, while leveraging your diversity as an opportunity to create an inspiring course.
 
The following assignments are scheduled:
  • Explore data science and its societal impact
  • Survey the market landscape
  • Study selected scientific literature
  • Practice with big data tools
The graded deliverables generate the final course grade as follows:
  1. [A] Book review
  2. [B] Market research
  3. [C] Project pitch event
  4. [D] Written, mostly multiple choice, exam
  5. [E] Optional bonus for extraordinary participation/performance
Grade = [A]*0.15 + [B]*0.15 + [C]*0.30 + [D]*0.40 + [E]

NB: To qualify for the second chance exam, all grading components need to be at least 4.0.
Ingangseisen
Verplicht materiaal
Boek
Domingos, P. (2015). The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World. Basic Books.
ISBN:9780465065707
Boek
Pritzker, P., and May, W. (2015). NIST Big Data interoperability Framework (NBDIF): Volume 1: Definitions. NIST Special Publication 1500-1. Final Version 1. National Institute of Standards and Technology.
Artikelen
Spruit,M., & Jagesar,R. (2016). Power to the People! Meta-algorithmic modelling in applied data science. In Fred,A. et al. (Ed.), Proc. 8th Int.Conf. on Knowledge Discovery (pp. 400–406). KDIR 2016, November 11-13, 2016, Porto, Portugal: ScitePress.
Artikelen
Spruit,M., & Boer,T. de (2014). Business Intelligence as a Service: A Vendor’s Approach . International Journal of Business Intelligence Research, 5(4), 26–43.
Artikelen
Lazer, D., Kennedy, R., King, G., & Vespignani, A. (2014). The parable of Google Flu: traps in big data analysis. Science, 343(6176), 1203-1205.
Werkvormen (aanwezigheidsplicht)
Hoorcollege (Verplicht)

Algemeen
There will be 6 contact hours per week. On Tuesdays and Thursdays, regular lectures will be given.

In the first weeks, the lectures will focus more on the fundamentals of applied data science, whereas in the second half we will be introduced into current research of various UU/UMCU researchers related to applied data science.

Werkcollege (Verplicht)

Algemeen
The Thursday lectures are then followed by workshop sessions where we will practice with big data tools (esp. Hadoop) and collaboratively investigate their societal impact.

Toetsen
Eindresultaat
Weging100
Minimum cijfer6

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