- Peer Review
- Business Process
- Data Preprocessing
- Data Mining
- Data Collection
- Data Cleansing
- Data Analysis
- Software Development Methodologies
- Data Modeling
- Classification Algorithms
- User Feedback
- Model Deployment
Data Science Methodology
Completed by DENYS BIELSKYI
September 15, 2019
7 hours (approximately)
DENYS BIELSKYI'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
