Data Science is Pop!

The purpose of the practical training "Data science is pop" is to provide an overview of data science, including machine vision, data visualization, Python libraries and much more. There are 15 training videos in total, and all can be found in one video list.

The trainers are Kristjan and Eneli Eljand.

Training materials are available from here.

The training was organized by the Ministry of Economic Affairs and Communications from the support scheme of the European Union structural support "Increasing digital literacy", which was financed by the European Social Fund.

Linkandmete tehnoloogia koolitus

 Koolituse eesmärk on tõsta avaliku sektori andmete tootmise protsesside loojate teadlikkust andmete avaldamise kvaliteedist, et toodetavad avaandmed oleksid võimalikult kõrgekvaliteedilised. Koolituse läbinutel on teadmised linkandmetest (linked data), nende olemusest ja olulisusest.


Koolitus koosneb neljast osast, kõik videod on järelvaadatavad siit.

Materjalid kättesaadavad siit.

Processing of personal data in data analytics

The training deals with the main problems related to the processing of personal data in the context of data analytics. The process of choosing the legal basis for processing personal data is explained, the risks and differences in the automated processing of special types of personal data are reviewed, and the principle of integrated data protection and default data protection is introduced.


The training consists of three parts, all videos are watchablehere.

Materials available from here.

Tableau training for analysts with materials

Tableau software training is primarily aimed at those public sector data analysts and other data workers who are aware of data visualization and processing, but do not have extensive experience and skills with the data analytics tool or, more specifically, with Tableau. The training focuses on Tableau roles Author, Designer, Analyst.

The training also includes practical exercises. 

Materials available from here.

Conducting a data science project

The aim of the training is to give public sector project managers an overview of data science projects and how to carry them out better. In particular, the training focuses on the PoC phase of data science projects, where uncertainty is still very high. The training is three-part.

Privacy-preserving technologies

The training "Privacy-preserving technologies" takes place under the "Simple and understandable" training series. The purpose of the training is to introduce various privacy-enhancing technologies (in English, privacy-enhancing technologies or PET), which guarantees their application provides, and what the prerequisites are for this. After completing the training, the participant will be able to assess which privacy-preserving technologies could be applied based on the specifics of information processing and what are the risks and limitations that should be taken into account during implementation.


We can view the training by topicon youtube channel.

Training seminar on creating data warehouses

The purpose of the training seminar on creating data warehouses is to provide the training participants with the necessary background system to orient themselves in the field of data warehouses. The training will introduce what a data warehouse is, what its different components are, what technologies and software are used to create data warehouses, and which (data protection) requirements should be taken into account when creating data warehouses. In addition, during the training, recommendations are given on how to carry out the data warehouse project.

Materials availablefrom here.

Tableau training for managers with materials

The purpose of the training is to introduce the capabilities of Tableau software to public sector managers. Data analytics valuable for managers to order and consume reports in a new way. The training provides an overview of both theoretical and practical aspects.

Materials available from here.

Processing of personal data in data analytics

In the training, the general principles of data protection will be introduced as an introduction and their implementation will be discussed in the key to persistent problem areas. Materials:

1.Participation (legal basis).

2.Involvement (impact assessment).