Data analytics and artificial intelligence (4 cr)

Evaluation scale

0-5

Objective

In the course, you will get an overview of the methods, possibilities and applications of data analytics and artificial intelligence, as well as the most common programming environments and libraries used in them.

EUR-ACE Knowledge and understanding
You understand the key concepts of data analytics and artificial intelligence. In addition, you will recognize the different stages of data processing and the libraries suitable for them.

EUR-ACE Engineering practice
You know how to choose libraries suitable for different stages of data analytics and machine learning and use them as part of data processing.

Content

This course will give you a comprehensive overview of the methods, possibilities and applications of data analytics and artificial intelligence. You will learn to understand the key concepts and identify the different stages of data processing and the libraries that can be used for them. You will be able to select and use libraries suitable for the different stages of data analytics and machine learning in practical data processing. This course will enable you to apply data analytics and artificial intelligence methods in a variety of situations.

Data sources
Data analysis
Data visualisation
Machine learning

Materials

Course material page (lecture materials, exercises)

Teaching methods

- Weekly demos in class
- In addition, students can come to class to do exercises weekly and receive support from the teacher in doing the exercises

Completion alternatives

The admission procedures are described in the degree rule and the study guide. The teacher of the course will give you more information on possible specific course practices.

Student workload

Distance learning 88 h (environment preparation, familiarisation with the material, exercises)
In-class demos led by the teacher and guidance sessions 20 h
Total 108 h

Assessment criteria, satisfactory (1)

Sufficient (1):
You know the basic concepts of data analytics and artificial intelligence superficially. You know how to use some methods as part of data processing.

Satisfactory (2):
You know the key concepts of data analytics and artificial intelligence. You know how to apply your knowledge at a basic level in data processing problems.

Assessment criteria, good (3)

Good (3):
You understand the key concepts and basic principles of data analytics and artificial intelligence. You know how to apply your knowledge consistently and successfully in most data processing situations.

Very good (4):
You have a deep understanding of the key concepts and methods of data analytics and artificial intelligence. You know how to apply your information effectively and analyze the results even in more demanding data processing problems.

Assessment criteria, excellent (5)

Excellent (5):
You have an excellent command of the concepts of data analytics and artificial intelligence and combine information from different sources seamlessly. You can apply your knowledge effectively and analyze the results clearly and critically even in more demanding data processing problems.

Qualifications

Basics of Programming

Further information

The course assessment consists of returned exercises (no separate exam). There is one given deadline for returning exercises for the course, before which the exercises must be submitted for assessment. The student may submit exercises for assessment at any point in the course.