In a Digital Economy, Data is the backbone of many activities. Data Science is a scientific
methodology helping organizations to transform questions into actions.
The goal of this course is to develop critical thinking while having a good understanding of the
capabilities of Data.
It will progressively help students to master 3 levels:
– General knowledge about Data Science
– Data Literacy (capability to speak Data and argue with) – a key skill to take better
informed decisions
– Data Science methodology introduction (tools and techniques) – skills to extract
advanced insights
The course will empower students to learn how to learn as the Data Science tools are evolving
quickly while having the Analytical thinking and methodology that will help them to apply
easily those later.
1.5 Million Jobs in Data Science are open overall (according to Microsoft) and the 2018
“Emerging Jobs in Singapore” report released on the 6th of September 2019 showed that data-
scientist jobs recorded the steepest rate of growth 17 x between 2013 and last year.
Only 20% of the workforce in SMEs is data literate, despite this being a key for greater
performance and development (Qlik study).
Data Scientist is the sexiest job in the world!
The course will be a mix of lectures to bring the overview, individual technological watch
and team work on practical examples to learn the different elements.
Making it condensed in bootcamps will help to learn differently too, by experience an intense
learning both theoretically and by experience.
We will encourage a lot of presentations from students to work on communication skills and
argumentation.
LO1: Understand the Data Economy global picture
LO2: Explain the difference between Data Science and Artificial Intelligence
LO3: Use the principles to argue with Data
LO4: Challenge a statement visualization or a metric (curiosity)
LO5: Understand the human-decision main processes
LO6: Leverage on data-informed decisions
LO7: Use Data Science methodology
LO8: Interpret business requirements
LO9: Understand and transform the data (basics)
LO10: Design and build visualizations (basics)
LO11: Interpret visualizations
LO12: Analyze results
LO13: Act on Results
LO14: Share Results
LO15: Understand key Data Science tools and methodology