Lesson 1: Solving Business Problems Using AI and ML

• Topic A: Identify AI and ML Solutions for Business Problems
• Topic C: Formulate a Machine Learning Problem
• Topic D: Select Appropriate Tools

Lesson 2: Collecting and Refining the Dataset

• Topic A: Collect the Dataset
• Topic B: Analyze the Dataset to Gain Insights
• Topic C: Use Visualizations to Analyze Data
• Topic D: Prepare Data

Lesson 3: Setting Up and Training a Model

• Topic A: Set Up a Machine Learning Model
• Topic B: Train the Model

Lesson 4: Finalizing a Model

• Topic A: Translate Results into Business Actions
• Topic B: Incorporate a Model into a Long-Term Business Solution

Lesson 5: Building Linear Regression Models

• Topic A: Build a Regression Model Using Linear Algebra
• Topic B: Build a Regularized Regression Model Using Linear Algebra
• Topic C: Build an Iterative Linear Regression Model

Lesson 6: Building Classification Models

• Topic A: Train Binary Classification Models
• Topic B: Train Multi-Class Classification Models
• Topic C: Evaluate Classification Models
• Topic D: Tune Classification Models

Lesson 7: Building Clustering Models

• Topic A: Build k-Means Clustering Models
• Topic B: Build Hierarchical Clustering Models

Lesson 8: Building Advanced Models

• Topic A: Build Decision Tree Models
• Topic B: Build Random Forest Models

Lesson 9: Building Support-Vector Machines

• Topic A: Build SVM Models for Classification
• Topic B: Build SVM Models for Regression

Lesson 10: Building Artificial Neural Networks

• Topic A: Build Multi-Layer Perceptrons (MLP)
• Topic B: Build Convolutional Neural Networks (CNN)

Lesson 11: Promoting Data Privacy and Ethical Practices

• Topic A: Protect Data Privacy
• Topic B: Promote Ethical Practices
• Topic C: Establish Data Privacy and Ethics Policies