- Data Cleansing
- Software Development Methodologies
- Predictive Modeling
- Data Science
- Data Modeling
- Data Quality
- Data Processing
- Feature Engineering
- Stakeholder Engagement
- Peer Review
- Data Transformation
- Data Mining
Data Science Methodology
Completed by Nicolás Eduardo Romero Arévalo
November 20, 2020
6 hours (approximately)
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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
