If there is a shortcut to becoming a Data Scientist, then learning to think and work like a successful Data Scientist is it. Most of the established data scientists follow a similar methodology for solving Data Science problems. In this course you will learn and then apply this methodology that can be used to tackle any Data Science scenario.
IBM Skills NetworkAbout this Course
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Coursera Labs
Includes hands on learning projects.
Learn more about Coursera Labs Beginner Level
No previous experience required, although prior use of Jupyter Notebooks will be beneficial.
Approx. 8 hours to complete
English
Could your company benefit from training employees on in-demand skills?
Try Coursera for BusinessWhat you will learn
Describe what a 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.
Determine an appropriate analytic model including predictive, descriptive, and classification models to analyze a case study.
Decide on appropriate sources of data for your data science project.
Skills you will gain
- Data Science
- Methodology
- CRISP-DM
- Data Analysis
- Data Mining
Flexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Coursera Labs
Includes hands on learning projects.
Learn more about Coursera Labs Beginner Level
No previous experience required, although prior use of Jupyter Notebooks will be beneficial.
Approx. 8 hours to complete
English
Could your company benefit from training employees on in-demand skills?
Try Coursera for Business
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Start working towards your Bachelor's degree
This course is part of the 100% online Bachelor of Applied Arts and Sciences from IBM Skills Network. If you are admitted to the full program, your courses count towards your degree learning.
Syllabus - What you will learn from this course
3 hours to complete
From Problem to Approach and From Requirements to Collection
3 hours to complete
5 videos (Total 19 min), 3 readings, 4 quizzes
3 hours to complete
From Understanding to Preparation and From Modeling to Evaluation
3 hours to complete
6 videos (Total 22 min), 3 readings, 4 quizzes
2 hours to complete
From Deployment to Feedback
2 hours to complete
3 videos (Total 10 min), 2 readings, 3 quizzes
Reviews
- 5 stars71.22%
- 4 stars21.48%
- 3 stars4.89%
- 2 stars1.52%
- 1 star0.87%
TOP REVIEWS FROM DATA SCIENCE METHODOLOGY
by ARNov 22, 2019
It was a good course with very easy to understand material and methodology.
In my opinion additional optional reading resources or case study links is required for this to be a 5 star course.
by AMJun 4, 2021
A very important course to develop a fundamental understanding of data science. Excellent in-course example to simplify the process of learning (think of it as a recipe in cooking). Enjoyed it.
by NNJul 6, 2019
I like the way they provide sample with food preparation on each of the stage of data science methodology. Need to give more sample for the study case to give more insight and understanding.
by HHSep 18, 2019
This was a critical course for me. Understanding the data scientists workflow which includes customer\client interaction has help me in understanding how to proceed in future endeavors.
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