course-details-portlet

TDT4216 - Applied Data Science

About

Lessons are not given in the academic year 2020/2021

Course content

Data science comprises a significant variety of methods and technologies for mining, aggregating and analzying data.


The aim of most courses in AI is understanding the finer details of the methodological aspects. This course, however, is aimed at developing knowledge of, skills in and competance of the most used methods.

The course exploits the fact that very many business-relevant, practical problems applications of data science do not require the most sophisticated methods. Many practical problems from private and public organizations may be tackled with known methods readily available in commodified technologies in the form of open source.

Learning outcome

Knowledge: The candidate will establish deep knowledge about the variety of data science methods, technologies and algorithms.

Skills: The candidate will gain solid skills in setting up and configuring data science tools. The candidate will develop good skills in identifying what methods are appropriate for what type of problems. The candidate will also develop good skills in preparing and pre-processing data for input.

Competence: The candidate will estabslish a compentence in the conditions for the application of selected data science methods to address business and strategica challenges.

Learning methods and activities

The course consists of lectures and project work.

The students need to complete a group-based project as well as an individual assignment. In the group project the students go through a realistic, problem-oriented analytics of the data.

The group project is develop practical skills in configuring the relavant tools/ technologies, pre-processing of data and conducting the analytics. The individual assignment discusses the group project in light of relevant literature from the course’s curriculum.

The group-based project counts for 50% and the indivual assignment 50% of the evaluation. Both parts need a pass for a student to obtain a pass in the course.

The course may be lectured in English if there are students not knowledgable in Norwegian

Specific conditions

Limited admission to classes.

Required previous knowledge

None

Course materials

Information given at beginning of course

More on the course

No

Facts

Version: 1
Credits:  7.5 SP
Study level: Second degree level

Coursework

Language of instruction: English

Location: Trondheim

Subject area(s)
  • Computer and Information Science
  • Computer Systems
Contact information
Course coordinator: Lecturer(s):

Department with academic responsibility
Department of Computer Science

Phone:

Examination

  • * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.
Examination

For more information regarding registration for examination and examination procedures, see "Innsida - Exams"

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