Data Science on Sustainable Development Goals (SDGs)

Data Science on Sustainable Development Goals (SDGs)

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.

Understand and analyse SDG data sets. Get an introduction in data science - get inspired for your sustainability journey

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What you will learn

• 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

Rating: 4.15

Level: All Levels

Duration: 2 hours

Instructor: Frank Kienle