Educational Data Mining Without Coding
Course code
old course code
Course title in Estonian
Hariduslik andmekaeve programmeerimiseta
Course title in English
Educational Data Mining Without Coding
ECTS credits
Assessment form
lecturer of 2024/2025 Autumn semester
Danial Hooshyar (language of instruction:English)
lecturer of 2024/2025 Spring semester
Not opened for teaching. Click the study programme link below to see the nominal division schedule.
Course aims
Gives an overview of applying data mining in an educational context to students without a computer science or programming background.
Brief description of the course
Some examples of the data mining methods that will be learnt include supervised machine learning algorithms like Decision Trees, Rule Induction, Support Vector Machines, and Artificial Neural Networks. In addition to that, unsupervised learning methods like clustering and association rule mining will be practised.
Learning outcomes in the course
Upon completing the course the student:
- has more knowledge of different data mining techniques;
- employs knowledge and skills for data-driven decision-making in their area of interest;
- is able to implement technologies for educational data mining;
- understands data mining implications.
Danial Hooshyar