Data Science on Sustainable Development Goals (SDGs)

Understand and analyse SDG data sets. Get an introduction in data science - get inspired for your sustainability journey
Free tutorial
Rating: 4.7 out of 5 (136 ratings)
5,770 students
1hr 52min of on-demand video
English [Auto]

Understand the Sustainable Development Goals (SDG)
Get a quick start for visualising SDGs in Python
Perform initial data science practice on combined SDG data sets
Get inspired for your next step and contribution towards sustainability!


  • Basic programming knowledge - the Python parts should give you a starting point
  • The inital capability of analysing data sets. Analysis can be done in any other tool or language as well.


The Sustainable Development Goals (SDGs) are 17 global goals designed to be a "blueprint for achieving a better and more sustainable future for all". The goals to be achieved by 2030 are an urgent call for action by all countries - and us all.

The course highlights the sustainable development goals (SDGs) and analyzes the SDG indicators that track the current global status.

Did you know that there exist 17 goals backed up and monitored by over 230 indicators? Each indicator measures the progress of all countries, sometimes over decades—a lot of data points to analyze. Let's start!

The lecture balances basic principles for everyone and crisp data science sections analyzing SDG indicators based on Python.

The course is divided into 5 sections:

  • General introduction to the SDGs and their data sets to trace the status.

  • Data Science overview and explaining the CRISP-DM methodology.

  • Data Science visualization practices on time series, world maps, and tree view examples.

  • Data Science practice on combining various SDG indicators and doing a cross-analysis.

  • Additional information for your next step and possible contribution.

The course's overall objective is to give you a quick start in data science practice and inspire you to contribute towards our joint SDG goals.

Who this course is for:

  • Data analytics performer interested in SDG and its data sets
  • People interested in analyzing sustainability data sets
  • People interested in contributing in the big SDG goals


Head of Data Science, Digital Strategy Manager
Frank Kienle
  • 4.5 Instructor Rating
  • 350 Reviews
  • 6,932 Students
  • 4 Courses

Frank Kienle worked for Blue Yonder from 01/2013 to 09/2017, first as a senior data scientist, later as director of data science consulting.

10/2017 to 03/2020 he worked for the Consulting Company Camelot ITLabs and headed the competence center artificial intelligence and data science.

Since 04/2020 he is working for Roche Diagnostics as digital strategy manager, defining and preparing the future roadmap for digital production.

He is convinced that Industry 4.0 marks the beginning of a new era in which a strong combination of modern software methods and traditional engineering education becomes mandatory. His main focus topics are within applied machine learning applications and artificial intelligence systems within enterprise IT systems.

Focus is always the value for the customer.

Frank Kienle holds a doctorate in electrical engineering and a Habilitation (venia legendi) at the technical university of Kaiserlautern (TUKL), Germany. Since 2014 he gives the lecture 'Introduction to Data Science' at TUKL, Germany (Privat-Dozent).

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