IntroductionBasic Functionality and FeaturesWhat is a Jupyter Notebook and Why is it Useful?Navigating the PlatformExercise 1: Introducing Jupyter NotebooksJupyter FeaturesExercise 2: Implementing Jupyter's Most Useful FeaturesConverting a Jupyter Notebook to a Python ScriptPython LibrariesExercise 3: Importing the External Libraries and Setting Up the Plotting EnvironmentOur First Analysis - The Boston Housing DatasetLoading the Data into Jupyter Using a Pandas DataFrameExercise 4: Loading the Boston Housing DatasetData ExplorationExercise 5: Analyzing the Boston Housing DatasetIntroduction to Predictive Analytics with Jupyter NotebooksExercise 6: Applying Linear Models With Seaborn and Scikit-learnActivity 1: Building a Third-Order Polynomial ModelUsing Categorical Features for Segmentation AnalysisExercise 7: Creating Categorical Fields From Continuous Variables and Make Segmented VisualizationsSummary