Data Analytics and Machine Learning

Data is revolutionising the way companies operate, and companies that view data as a strategic asset are the ones that will survive and thrive. The importance of data across every aspect of business will only increase with the massive growth of big data and the Internet of Things, plus rapidly evolving methods for analysing it.


There are some core areas where data really matters to a business: for improving decision making, operations, and the monetisation of data. The aim of this specialisation is to provide knowledge and practical tools for creating and introducing data strategy based on your company’s needs.


Subjects within the nanodegree

Fall 2020 semester

The aim of the course is to provide an understanding of databases and database management systems, designing databases and using data models. Also, it is essential to support the theoretical part of the course content by doing hands-on tasks using query language.

The aim of the course is to understand the theory behind data analysis and visualisation while using relevant tools to conduct the analysis and create visualisations.

This course provides understanding the organizational and social aspects of digital ecosystems, and the complex interplay between people, business processes and digital technologies in organization.



Spring 2021 semester (starting on the second half of January)

The Emerging Technology course will focus on Artificial Intelligence (AI) in modern business. The managerial perspective to AI will enable you to gain an understanding of how the growth and application of AI will change the business landscape. By the end of the course you are able to craft AI strategy for a business.

  • Data Literacy (3 ECTS) 

Every business is dealing with an incredible amount of data. But collecting it isn’t the same as understanding it. Data literacy is the ability to read, work with, analyse and communicate with data. It’s a skill that empowers you to ask the right questions of data and machines, build knowledge and make decisions.

  • Data Analytics: From Big data to Smart data (3 ECTS)

Today, all entrepreneurs are expected to know and understand how data is generated and collected. It is necessary to understand  what is "big data" and how an analytical approach helps to extract value from it, turning big data to smart data.


Coming semesters

  • Cyber Security and Legal Aspects of Data Protection
  • Machine Learning 
  • Data in Business

Today, every business is data business. It is already revolutionising the way companies operate and it will become increasingly critical to organisations in coming years. 

Learning Outcomes

Upon completion of the subjects you have:

  • A systematic overview of the company's need for information
  • An understanding, knowledge and skills of data management and data analytics
  • Ability to organise and use real-world data collections and data visualisation tools
  • Sound knowledge and skills in economic, legal, political and security aspects of digital ecosystems
  • Awareness of the legal aspects and cyber threats associated with the development of data and IT management.


Price for the 15 ECTS  nanodegree module: 2250 €

10% discount applies for alumni.
It is possible to buy each course separately. 

Paying in two or more parts 35 € will be added to the total sum.


  • Basic understanding of business and entrepreneurship
  • Bachelor degree and minimum 3-year working experience in the business or relevant area
    or bachelor degree in business, management, economics 
  • Master sufficient proficiency in English (B2)
  • send us a CV or LinkedIn profile
  • Passed consultation with EBS consultant

EBS alumni can go to and add the full module or course into the cart.

Registration and shop


  • For EBS alumni or previous open university participants, please use your current EBS account (previously named OIS account). If you do not remember it contact with 
  • For the prospective learner, please fill the registration form and register to the consultation.



Beginning of module

Mirell Merirand

Mirell Merirand

Learning Path Coordinator
Kärt Padur

Kärt Padur

Meelis Kitsing

Meelis Kitsing

Toomas Danneberg

Toomas Danneberg