If there is a shortcut to becoming a Data Scientist, then learning to think and work like a successful Data Scientist is it. In this course, you will learn and then apply this methodology that you can use to tackle any Data Science scenario. You’ll explore two notable data science methodologies, Foundational Data Science Methodology, and the six-stage CRISP-DM data science methodology, and learn how to apply these data science methodologies. Most established data scientists follow these or similar methodologies for solving data science problems.

Data Science Methodology

Data Science Methodology
This course is part of multiple programs.


Instructors: Alex Aklson
Access provided by Vishwakarma Intitutes
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What you'll learn
Describe what a data science methodology is and why data scientists need a methodology.
Apply the six stages in the Cross-Industry Process for Data Mining (CRISP-DM) methodology to analyze a case study.
Evaluate which analytic model is appropriate among predictive, descriptive, and classification models used to analyze a case study.
Determine appropriate data sources for your data science analysis methodology.
Skills you'll gain
Tools you'll learn
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There are 4 modules in this course
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Reviewed on Nov 29, 2019
This was a clear and concise overview of the methodology and using the case study really helped (although sometimes it got a bit advanced considering this comes before actually learning models).
Reviewed on May 16, 2021
A bit more complex than what I would have hoped, but the material is still digestible. I think this course could be improve if the lecturer slow down a bit and spend more time on each topic
Reviewed on Apr 14, 2020
It's a very good course for getting the basic idea of the methodology of data science. It will help to get grip on how to proceed to a problem in a systematic manner for getting good results.
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