- Model Evaluation
- Predictive Analytics
- Statistical Modeling
- Data Wrangling
- Exploratory Data Analysis
- Regression Analysis
- Data Science
- Feature Engineering
- Data Preprocessing
- Forecasting
- Data Visualization
- Data Cleansing
Data Analysis with R
Completed by Steve CALIXTE
January 22, 2024
16 hours (approximately)
Steve CALIXTE's account is verified. Coursera certifies their successful completion of Data Analysis with R
What you will learn
Prepare data for analysis by handling missing values, formatting and normalizing data, binning, and turning categorical values into numeric values.
Compare and contrast predictive models using simple linear, multiple linear, and polynomial regression methods.
Examine data using descriptive statistics, data grouping, analysis of variance (ANOVA), and correlation statistics.
Evaluate a model for overfitting and underfitting conditions and tune its performance using regularization and grid search.
Skills you will gain
