Course curriculum

  • 1

    Chapter 1

    • Lesson Introduction

    • Learning Review

    • Introduction to AI and Machine Learning

    • AI Applications

    • Moore's Law

    • Discuss about Machine Learning

    • Machine Learning Types

    • Discuss about Linear Regression

    • Graphing Math/Algebraic Functions

    • Line of Best Fit

    • Line of Best Fit continued

    • Prediction with the Model

    • Model Fits

    • Neural Networks Explanation
  • 2

    Chapter 2

    • Setup Kaggle

    • Previous Chapter Review

    • Different Models

    • Selecting a Model for Our Task

    • Setting Notebook Appearance

    • Problem Explanation

    • Problem Explanation continued

    • Notebook Setup

    • Data Inspection

    • Applying Data to Model

    • Converting Categorical Data to Calculable Data

    • Converting Categorical Data to Calculable Data continued

    • Trimming and Renaming DataFrame Columns

    • Splitting Data to Train/Test Sets

    • Chapter Review
  • 3

    Chapter 3

    • Chapter Introduction

    • Chapter Introduction continued

    • Chapter Introduction continued

    • Explaining Training/Test Data

    • Cast Pandas Data to Numpy Data

    • Explain Numpy Data Structure

    • Explain Numpy Data Structure continued

    • Selecting And Visualizing Data for Model

    • Visualizing Data for Model continued

    • Choosing a Model

    • Transforming Data for Model

    • Fitting the Model and Getting Output

    • Plotting and Scoring the Model