Artificial Intelligence Foundations: Machine Learning

Introduction

• Introduction to AI foundations: Machine learning course
• Reviewing the course scenarios

1. Understanding Machine Learning

• Exploring machine learning
• Examining how machines learn
• Why traditional ML still matters

2. Implementing a Machine Learning Solution

• Breaking down the machine learning lifecycle
• Framing machine learning problems
• Identifying a pre-built model
• Understanding tools used to train a model

3. Preparing Data for Machine Learning

• Obtaining data
• Visualizing and understanding data
• Understanding feature engineering
• Demo: Performing feature engineering

4. Training a Machine Learning Model

• Understanding learning algorithms and model training
• Exploring learning algorithms for classification
• Reviewing learning algorithms for regression
• Examining additional learning algorithms
• Training a custom machine learning model
• Demo: Training a custom machine learning model

5. Evaluating Model Performance

• Exploring common classification metrics
• Understanding the confusion matrix
• Exploring common regression metrics
• Determining feature importance
• Combating bias

6. Operationalizing a Machine Learning Pipeline

• Structuring a machine learning pipeline
• Demo: Designing and building a pipeline

Conclusion

• Your machine learning journey
• Bridge to generative AI