- Data Modeling
- User Feedback
- Data Processing
- Business Requirements
- Data Mining
- Data Transformation
- Jupyter
- Data Collection
- Predictive Modeling
- Stakeholder Engagement
- Data Quality
- Software Development Methodologies
Data Science Methodology
Completed by Pedro Domingos
July 15, 2024
6 hours (approximately)
Pedro Domingos'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
