satya - 7/10/2020, 1:16:57 PM
Course Contents

* Course Introduction
    * Promo/Intro Video
    * Course Curriculum Overview
    * Introduction to Spark, RDDs, and Spark 2.0
    
* Course Set-up
    * Set-up Overview
    * EC2 Installation Guide
    * Local Installation Guide with VirtualBox
    * Databricks Notebooks
    * Unix Command Line Basics and Jupyter Notebook Overview
    
* Spark DataFrames
    * Spark DataFrames Section Introduction
    * Spark DataFrame Basics
    * Spark DataFrame Operations
    * Groupby and Aggregate Functions
    * Missing Data
    * Dates and Timestamps
    
* Spark DataFrame Project
    * DataFrame Project Exercise
    * DataFrame Project Exercise Solutions
    
* Machine Learning
    * Introduction to Machine Learning and ISLR
    * Machine Learning with Spark and Python and MLlib
    * Consulting Project Approach Overview
    
* Linear Regression
    * Introduction to Linear Regression 
    * Discussion on Data Transformations
    * Linear Regression with PySpark Example (Car Data)
    * Linear Regression Consulting Project (Housing Data)
    * Linear Regression Consulting Project Solution

* Logistic Regression
    * Introduction to Logisitic Regression 
    * Logistic Regression Example
    * Logistic Regression Consulting Project (Customer Churn)
    * Logistic Regression Consluting Project Solution
    
* Tree Methods
    * Introduction to Tree Methods
    * Decision Tree and Random Forest Example
    * Random Forest Classification Consulting Project - Dog Food Data
    * RF Classification Consulting Project Solutions
    * RF Regression Project - (Facebook Data)
    
* Clustering
    * Introduction to K-means Clustering
    * Clustering Example - Iris Dataset
    * Clustering Consulting Project - Customer Segmentation (Fake Data)
    * Clustering Consulting Project Solutions
    
* Recommender System
    * Introduction to Recommender Systems and Collaborative Filtering
    * Code Along Project - MovieLens Dataset
    * Possible Consulting Project ? Company Service Reviews
    
* Natural Language Processing
    * Introduction to Project/NLP/Naive Bayes Model
    * What are pipelines?
    * Code Along 
    
* Spark Streaming
    * Introduction to Spark Streaming 
    * Spark Streaming Code-along!