The course is included in these curricula and study modules
- 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
The course takes place in period
3 (2022-01-01 to 2022-03-13)
Level/category
Teaching language
English
Type of course
Compulsory
Cycle/level of course
First
Recommended year of study
3
Total number of ECTS
5 cr
Competency aims
This study unit focuses on the following
competences:
- Analysis of unstructured data
- Development of software that applies relevant
algorithms within the field of text analysis.
Learning outcomes
At the end of the study unit:
- You are aware of important questions and basic
terminology, methods and techniques within the
field of text analytics
- You develop practical experiences within
processing natural languages
- You learn NLP programming
- You are able to build a practical application
within the field of NLP through a course project
Course contents
Basic Text Processing: Regular expressions, Text
Normalization, Edit Distances
Language Modelling with N-Grams
Naïve Bayes, Text Classification
Logistic Regression + Lexicons for sentiment
Information Retrieval and Query processing
Topic Modelling and Word Embeddings/Vectors
Neural Network Models for NLP + Deep learning
models: BERT and Transformer models
Prerequisites and co-requisites
- Data processing
Recommended or required reading
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
Study activities
- Lectures - 40 hours
- Project- and production work/artistic activities - 95 hours
Workload
- Total workload of the course: 135 hours
- Of which autonomous studies: 135 hours
- Of which scheduled studies: 0 hours
Mode of Delivery
Participation in tuition
Assessment methods
Course Project
Assessment requirements
Course project
Teacher
Mukkamala Raghava
Examiner
Karlsson Jonny
Home page of the course
Group size
No limit (34 students enrolled)
Assignments valid until
12 months after course has ended
Course enrolment period
2021-12-22 to 2022-01-14
Assessment methods
Date will be announced later - Other assignments
Date | Time | Room | Title | Description | Organizer |
---|---|---|---|---|---|
2022-01-31 | 08:30 - 12:30 | Deskriptiv analytik - Data/Text mining | Lektionen hålls online i Zoom. Länk publiceras på Itslearning före lektionens början. | ||
2022-02-01 | 08:30 - 12:30 | Deskriptiv analytik - Data/Text mining | Lektionen hålls online i Zoom. Länk publiceras på Itslearning före lektionens början. | ||
2022-02-14 | 08:30 - 12:30 | Deskriptiv analytik - Data/Text mining | Lektionen hålls online i Zoom. Länk publiceras på Itslearning före lektionens början. | ||
2022-02-15 | 08:30 - 12:30 | Deskriptiv analytik - Data/Text mining | Lektionen hålls online i Zoom. Länk publiceras på Itslearning före lektionens början. | ||
2022-02-21 | 08:30 - 12:30 | Deskriptiv analytik - Data/Text mining | Lektionen hålls online i Zoom. Länk publiceras på Itslearning före lektionens början. | ||
2022-02-22 | 08:30 - 12:30 | Deskriptiv analytik - Data/Text mining | Lektionen hålls online i Zoom. Länk publiceras på Itslearning före lektionens början. | ||
2022-02-28 | 08:30 - 12:30 | Deskriptiv analytik - Data/Text mining | Lektionen hålls online i Zoom. Länk publiceras på Itslearning före lektionens början. | ||
2022-03-01 | 08:30 - 12:30 | Deskriptiv analytik - Data/Text mining | Lektionen hålls online i Zoom. Länk publiceras på Itslearning före lektionens början. | ||
2022-03-04 | 08:30 - 12:30 | Deskriptiv analytik - Data/Text mining | Lektionen hålls online i Zoom. Länk publiceras på Itslearning före lektionens början. | ||
2022-03-07 | 08:30 - 12:30 | Deskriptiv analytik - Data/Text mining | Lektionen hålls online i Zoom. Länk publiceras på Itslearning före lektionens början. | ||
2022-03-10 | 08:30 - 12:30 | Deskriptiv analytik - Data/Text mining | Lektionen hålls online i Zoom. Länk publiceras på Itslearning före lektionens början. |