AI and Data AnalysisLaajuus (5 cr)

Objective

After completing the course, students will understand the importance of data visualisation in data analysis and be able to apply different visualisation techniques. They will develop a strong basic knowledge of statistical analysis of discrete data and be able to apply different statistical analysis methods. They will also be able to interpret the results of statistical analysis of discrete data and draw conclusions based on the results.

Students will also be introduced to various AI techniques and algorithms, including supervised and unsupervised learning, learn about Bayesian probabilistic approaches and inference, and explore graphical models as a powerful tool for representing and solving complex probabilistic problems.

Content

• Data visualisation
• Discrete data analysis
• AI tools and methods
• Bayesian Learning principles
• Graphical models
• Hands-on project on a simple discrete data analysis

Qualifications

Applied AI programming or equivalent knowledge

Assessment criteria, satisfactory (1)

The student
• has achieved the objectives of the course to a satisfactory level
• is able to identify, define and use concepts and models in the subject area of the course
• understands the conditions and principles of the development of expertise
• has completed the learning tasks required for the course to the minimum standard
• has developed their competences in such a way that they will be able to complete their future professional studies and eventually work in the field.

Assessment criteria, good (3)

The student
• has achieved the objectives of the course well, although there are still areas where knowledge and skills need to be improved
• has completed the learning tasks of the course at a satisfactory or good level
• has a good understanding of the concepts and models of the subject matter of the course and is able to carry out a reasoned analysis
• is able to apply what they have learned in learning and working life situations
• understands the importance of expertise in the field and is able to analyse their own expertise.

Assessment criteria, excellent (5)

The student
• has achieved the objectives of the course with excellent marks
• has completed the learning tasks of the course at a good or excellent level
• has an excellent command of the concepts and models of the subject matter of the course
• is able to analyse clearly and reasonably and propose practical development measures
• has a good ability to apply what they have learned in learning and working life situations
• is able to analyse expertise in their field and their own development towards expertise.