A collection of data analytics projects performed under the Google Advanced Data Analytics Certificate Program.
Project 1: Creating a Project Proposal
- this project is an overview of breaking down business objectives, assigning deliverables, and recognizing project stakeholders
Project 2: Preliminary Data Analysis
- this project is an overview of understanding data relationships, catching data errors, and understanding target-feature roles
Project 3: Exploratory Data Analysis
- this project is an overview of data cleaning techniques like encoding categorical values, dropping missing values, changing data types, and visualizing feature distributions
Project 4: Statistical Data Analysis
- this project is an overview of hypothesis testing and determining significance between feature and target variables
Project 5: Build a Multiple Linear Regression Model
- this project is an overview of linear regression techniques, modeling with scikit-learn, and meeting linearity assumptions
Project 6: Build a Random Forest Model
- this project is an overview of random forest techniques, building classifiers, performing hyperparameter tuning with GridSearchCv, comparing model results, and model evaluation