- Evolvement of data science
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What can we expecet from data science?
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Evolvement of data science, data doers and citizen data scientists
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Reducing time spent on data collection
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How to reduce time on data collection?
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Automated features
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Automated feature engineering and modeling
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Who is a citizen data scientist?
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An emerging role of a citizen data scientist
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Check your knowledge
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What can we expect?
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Key takeaways
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Feedback
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Well done
Evolvement of Data Science, Data Doers and Citizen Data Scientists
In this course you will learn what is expected evolvement of data science, data doers and citizen data scientists
Welcome to the course on the evolvement of data science, data doers and citizen data scientists
In this course, we will look at why and how tools for more streamlined work, related to data science projects, cover more and more steps and sub-steps of the data scientist workflow. This is also enabling other professionals, so-called citizen data scientists, to do some of the work data scientists are doing today.
By the end of this chapter you will understand:
- the importance of making data collection more efficient
- what kinds of automated feature engineering and modeling tools are available
- the role of citizen data scientist
Who should take this course?
This course was created for anybody interested to learn more about data science.
This course is independent, but also part of the learning path Data Science Fundamentals. We recommend that you take all courses from the Data Science Fundamentals series and take the final test to receive a certificate of completion.
Estimated duration
20 min
Instructors
The courses are developed by Cognite Academy in collaboration with other industry experts.
Rebecca Seyfarth
Senior ML Engineer in Contextualization at Cognite AS
Alina Astrakova
Senior ML Engineer in Services - Solution Architecture at Cognite AS
Collaborator
Vegard Flovik, Ph.D.
Lead Data Scientist | Associate Professor II in Machine