Back to Data Science Methodology
Learner Reviews & Feedback for Data Science Methodology by IBM
20,241 ratings
About the Course
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.
Begin by learning about forming the business/research problem Learn how data scientists obtain, prepare, and analyze data. Discover how applying data science methodology practices helps ensure that the data used for problem-solving is relevant and properly manipulated to address the question. Next, learn about building the data model, deploying that model, data storytelling, and obtaining feedback You’ll think like a data scientist and develop your data science methodology skills using a real-world inspired scenario through progressive labs hosted within Jupyter Notebooks and using Python.
Top reviews
HV
Invalid date
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
JG
Invalid date
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).
Filter by:
2551 - 2557 of 2,557 Reviews for Data Science Methodology
By Avi
•Nov 5, 2019
not stimulating at all
By RABÄ°A K
•Oct 19, 2023
#zionistterrorism
By Abdurrachman M
•Apr 20, 2018
Not interesting
By Naga s T
•Feb 21, 2023
not impressive
By Saptashwa B (
•Apr 8, 2019
Useless Course
By Jean-Yves R
•Oct 29, 2021
Really bad.
By Boru R
•Sep 5, 2020
Useless