- Program Overview
- Learn how to solve real life problem using the Linear Regression technique
- Preliminary analysis of data using Univariate analysis before running Linear regression
- Predict future outcomes basis past data by implementing Simplest Machine Learning algorithm
- Understand how to interpret the result of Linear Regression model and translate them into actionable insight
- In-depth knowledge of data collection and data preprocessing for Machine Learning Linear Regression problem
- Course contains an end-to-end DIY project to implement your learnings from the lectures
The Main Outlines
Getting Data Ready for Regression Model | Outlier Treatment |
Univariate analysis and EDD | Identifying and Treating Outliers in Excel |
Descriptive vs Predictive vs Prescriptive Analytics | Missing Value Imputation |
Descriptive Data Analytics in Excel | Identifying and treating missing values in Excel |
Variable Transformation in Excel | Dummy variable creation: Handling qualitative data |
Dummy Variable Creation in Excel | Correlation Analysis |
Correlation Coefficient in Excel | Creating Correlation Matrix in Excel |
Other Branches