Data Science Methodology
Completed by Athanasios Staveris-Polykalas
October 18, 2018
8 hours (approximately)
Athanasios Staveris-Polykalas'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
- Category: Data Preprocessing
- Category: Data Cleansing
- Category: Jupyter
- Category: Business Research
- Category: Model Evaluation
- Category: Model Deployment
- Category: Data Collection
- Category: Data Manipulation
- Category: Data Wrangling
- Category: Data Science
- Category: Data Mining
- Category: Data Analysis
