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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
Contactpersoon van de cursus
dr. M.R. Spruit
Overige cursussen docent
Docent
dr. M.R. Spruit
Overige cursussen docent
Blok
1-GSNS  (03-09-2018 t/m 09-11-2018)
Aanvangsblok
1-GSNS
TimeslotC: MA-middag/namiddag,DI-middag, DO-ochtend
Onderwijsvorm
Voltijd
OpmerkingPlease read HERE
for the latest information.
Cursusinschrijving geopendvanaf 28-05-2018 t/m 24-06-2018
AanmeldingsprocedureOsiris
Inschrijven via OSIRISJa
Inschrijven voor bijvakkersJa
VoorinschrijvingJa
Na-inschrijvingJa
Na-inschrijving geopendvanaf 20-08-2018 t/m 16-09-2018
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, the Applied Data Science postgraduate MSc programme, and the Business Informatics (MBI) programme. As such, it's primary objective is to inspire and introduce you to the emerging domain of Applied Data Science. . The following assignments are among the key parts of the course:
  • Book review: Explore data science and its societal impact
  • Mid-term e-exam on data engineering with Hadoop
  • End-term e-exam on data analytics with Spark
The graded deliverables generate the final course grade as follows:
  1. [A] Book review
  2. [B] Mid-term exam
  3. [C] End-term exam
  4. [D] Optional bonus for extraordinary participation/performance
Grade = [A]*0.10 + [B]*0.40 + [C]*0.50 + [D] 

NB: To qualify for the second chance exam, all grading components need to be at least 4.0, and component A needs to have been submitted within the allotted time. The 2nd chance exam is an extensive market survey report assignment.
Ingangseisen
Verplicht materiaal
Boek
White, J. (2016). Hadoop: The Definitive Guide. Third edition. O'Reilly.
Boek
Chambers, B., & Zaharia, M. (2018). Apache Spark - The Definitive Guide. O'Reilly.
Artikelen
Spruit, M., & Lytras, M. (2018). Applied Data Science in Patient-centric Healthcare: Adaptive Analytic Systems for Empowering Physicians and Patients. Telematics and Informatics, 35(4), 643–653.
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.
Aanbevolen materiaal
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
Dean, J., & Ghemawat, S. (2008). MapReduce: simplified data processing on large clusters. Communications of the ACM, 51(1), 107-113.
Artikelen
Ghemawat, S., Gobioff, H., & Leung, S. (2003). The Google file system. SIGOPS Operating Systems Review, 37(5), 29-43.
Artikelen
Davenport, T. H., & Patil, D. J. (2012). Data scientist: The Sexiest Job of the 21st Century. Harvard business review, 90(5), 70-76.
Boek
Stair, R. & Reynolds, G. (2012). Fundamentals of Information Systems. Sixth Edition. NOTE: Chapters 1 and 3 ONLY, on Information Systems in Perspective & Database Systems, Data Centers, and Business Intelligence. Cengage: Boston, MA.
ISBN:978-0-8400-6218-5
Handleiding
Chapman, P. Clinton, J., Kerber, R., Khabaza, T., Reinartz, T., Shearer, C., and Wirth, R. (2000). CRISP-DM 1.0 Step-by-step Data Mining Guide.
Werkvormen
Hoorcollege

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

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 cijfer-

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