- Stakeholder Engagement
- Jupyter
- Peer Review
- Data Science
- Predictive Modeling
- Data Transformation
- Data Modeling
- Data Cleansing
- Data Collection
- Data Mining
- Feature Engineering
- Data Analysis
Data Science Methodology
Completed by MARK EMMANUEL QUILAPIO RANA
March 22, 2022
6 hours (approximately)
MARK EMMANUEL QUILAPIO RANA's account is verified. Coursera certifies their successful completion of Data Science Methodology
What you will 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 will gain
