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.

About this Course
No previous experience required, although prior use of Jupyter Notebooks will be beneficial.
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
No previous experience required, although prior use of Jupyter Notebooks will be beneficial.
Could your company benefit from training employees on in-demand skills?
Try Coursera for BusinessOffered by
Start working towards your Bachelor's degree
Syllabus - What you will learn from this course
From Problem to Approach and From Requirements to Collection
From Understanding to Preparation and From Modeling to Evaluation
From Deployment to Feedback
Reviews
- 5 stars71.22%
- 4 stars21.47%
- 3 stars4.88%
- 2 stars1.53%
- 1 star0.87%
TOP REVIEWS FROM DATA SCIENCE METHODOLOGY
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.
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.
It is a good course, teaching about the general process and life cycle of a data science project. Excellent tips are provided. Overall, I feel it was lacking a bit in content for 3 weeks.
Very interesting course. It shed a light on what the structured approach really is. It's worth to pause for a moment with every step of the methodology and think how to apply it in real life. Thanks!
Frequently Asked Questions
When will I have access to the lectures and assignments?
What will I get if I subscribe to this Certificate?
More questions? Visit the Learner Help Center.