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Overview
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.
This Data Mining Without Coding: Using Rapid Miner in the Context of Education course from Tallinn University equips participants with capabilities to implement bottom-up methods to find existing patterns and relationships in their datasets and employ predictive analytics to predict future results. The learners will experience the hands-on practice of implementing various data mining techniques on different synthetic and real-world datasets in free open-source software.
Why this course?
- You will understand the basics of data mining methods and learn how to implement them in a free open-source software.
- Access video lecturers and experience hands-on practice.
- You will learn how to use bottom-up methods to find existing patterns and relationships in datasets, helping you to improve your decision-making skills.
Programme Structure
Course structure:
- The learners should not worry if they do not know any of these concepts beforehand – all methods and approaches will be introduced and explained in detail in video lectures and in-person practice seminars. This approach allows the learners to rewatch the topics that they feel less confident about and ask additional questions during the seminars. By the end of this course, the learners will have more knowledge of different data mining techniques and should be able to employ these for data-driven decision-making in their area of interest.
- Classes take place each week from Monday to Friday. The lectures are planned for each day starting at 10:00.
Key information
Duration
- Full-time
- 12 days
Start dates & application deadlines
- StartingApplication deadline not specified.
Language
English
Credits
3 ECTS
Delivered
On Campus
Disciplines
Education Web Technologies & Cloud Computing Machine Learning View 9 other Short Courses in Education in EstoniaAcademic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Student insurance
Make sure to cover your health, travel, and stay while studying abroad. Even global coverages can miss important items, so make sure your student insurance ticks all the following:
- Additional medical costs (i.e. dental)
- Repatriation, if something happens to you or your family
- Liability
- Home contents and baggage
- Accidents
- Legal aid
We partnered with Aon to provide you with the best affordable student insurance, for a carefree experience away from home.
Get your student insurance nowStarting from €0.53/day, free cancellation any time.
Remember, countries and universities may have specific insurance requirements. To learn more about how student insurance work at Tallinn University and/or in Estonia, please visit Student Insurance Portal.
Other requirements
General requirements
- Anyone interested in understanding the basics of data mining.
- Anyone interested in mining data using machine learning algorithms.
- Anyone interested in learning RapidMiner.
Tuition Fee
To always see correct tuition fees
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International
400 EUR/fullTuition FeeBased on the tuition of 400 EUR for the full programme during 12 days. -
EU/EEA
400 EUR/fullTuition FeeBased on the tuition of 400 EUR for the full programme during 12 days.
- Early-Bird Course Fee (until 30 November 2022) – 350€
- Regular Course Fee (after 30 November 2022) – 400€
Living costs for Tallinn
598 - 948 EUR /month
Living costs
The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.
Funding
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