Module 1 : Understanding Machine Learning and Excel Data Processing

• Understanding ML and Excel
• Intro to ML
• Why use Excel
• Types of ML in Excel

Module 2 : Data Preparation: Excel

• Data preparation basics
• Data exploration and preparation
• Handle missing values, outliers, and categorical variables

Module 3 : Create and Deploy a Regression Model: Excel

• Build a regression model
• Regression model use cases
• Perform linear regression.
• Interpret and evaluate results. 
• Visualize regression result
• Case study 1:
• Build a regression model.
• Interpret results from regression model
• Discussion

Module 4 : Create and Deploy a Classification Model: Excel

• Build a classification model
• Classification model use cases 
• Perform classification
• Interpret and evaluate results 
• Visualize classification results
• Case study 2:
• Build a classification model
• Interpret result from classification model

Module 5 : Create and Deploy a Clustering Model: Excel

• Build a clustering model
• Clustering model use cases
• Perform clustering
• Interpret and evaluate results 
• Visualize clustering results
• Case study 3:
• Build a clustering model
• Interpret result from clustering model
• Discussion
  

Module 6 : Create and Deploy Decision Trees: Excel

• Build a clustering model
• Entropy (Loss function)
• Information Gain
• Decision Trees in Excel
• Decision trees (Prediction)
• Case study 3:
• Build a decision tree
• Interpret result from decision tree
• Reflection
• Conclusion