IA-2-013 (0) - Descriptive Analytics - Data/Text Mining

• Information technology 2014 - Service oriented architectures and system design
• Information technology 2015 - Service oriented architectures and system design
• Information technology 2016 - Service oriented architectures and system design
• Information technology 2017 - Service oriented architectures and system design
• Information technology 2018 - Machine learning and decision support system development
• Information technology 2019 - Machine learning and decision support system development
• Information technology 2020 - Machine learning and decision support system development
• Information technology 2021 - Machine learning and decision support system development - advanced studies
• Information technology 2022 - Machine learning and decision support system development - advanced studies
• Information technology 2023 - Machine learning and decision support system development - advanced studies

3 (2024-01-01 to 2024-03-17)

English

Compulsory

First

3

5 cr

In this study unit the focus lies on the following
competencies:

Machine learning and decision support system
development with an emphasis on:

Analysis of unstructured data

Development of software applying relevant
algorithms in text analysis

SDG's in focus:
#4: Quality education
#9: Industry, innovation and infrastructure

Upon completion of this study unit:

You know the key issues and basic concepts,
methods and techniques of text analysis.
(Knowledge)

You can process natural languages in practice.
(Skills)

You can construct programs capable of processing
and analysing large amounts of natural language
data. (Skills)

You have an understanding of how text analysis can
be used to facilitate various everyday problems.
(Approach)

Data processing

Jurafsky, Dan, and James H. Martin. "Speech and
language processing. Vol. 3." US: Prentice Hall
(2014). (online copy available:
https://web.stanford.edu/~jurafsky/slp3/ External link )

Christopher D. Manning, Prabhakar Raghavan and
Hinrich Schütze. Introduction to information
retrieval. Vol. 39. Cambridge: Cambridge
University Press, 2008.
https://nlp.stanford.edu/IR External link-
book/html/htmledition/irbook.html

• Lectures - 40 hours
• Project- and production work/artistic activities - 95 hours

• Total workload of the course: 135 hours
• Of which autonomous studies: 135 hours
• Of which scheduled studies: 0 hours

Participation in tuition

Course Project

Dayama Niraj

Dayama Niraj

https://arcada.itslearning.com/ External link

No limit

12 months after course has ended

2023-11-24 to 2023-12-22

Date will be announced later - Other assignments