Spark and Python for Big Data with PySpark
What you will learn
- Use Python and Spark together to analyze Big Data
- Learn how to use the new Spark 2.0 DataFrame Syntax
- Work on Consulting Projects that mimic real world situations!
- Classify Customer Churn with Logisitic Regression
- Use Spark with Random Forests for Classification
- Learn how to use Spark's Gradient Boosted Trees
- Use Spark's MLlib to create Powerful Machine Learning Models
- Learn about the DataBricks Platform!
- Get set up on Amazon Web Services EC2 for Big Data Analysis
- Learn how to use AWS Elastic MapReduce Service!
- Learn how to leverage the power of Linux with a Spark Environment!
- Create a Spam filter using Spark and Natural Language Processing!
- Use Spark Streaming to Analyze Tweets in Real Time!
Section 1: Introduction to Course
Section 2: Setting up Python with Spark
Section 3: Local VirtualBox Set-up
Section 4: AWS EC2 PySpark Set-up
Section 5: Databricks Setup
Section 6: AWS EMR Cluster Setup
Section 7: Python Crash Course
Section 8: Spark DataFrame Basics
Section 9: Spark DataFrame Project Exercise
Section 10: Introduction to Machine Learning with MLlib
Section 11: Linear Regression
Section 12: Logistic Regression
Section 13: Decision Trees and Random Forests
Section 14: K-means Clustering
Section 15: Collaborative Filtering for Recommender Systems
Section 16: Natural Language Processing
Section 17: Spark Streaming with Python
Learn how to use Spark with Python, including Spark Streaming, Machine Learning, Spark 2.0 DataFrames and more!
- General Programming Skills in any Language (Preferrably Python)
- 20 GB of free space on your local computer (or alternatively a strong internet connection for AWS)
Learn the latest Big Data Technology - Spark! And learn to use it with one of the most popular programming languages, Python!
One of the most valuable technology skills is the ability to analyze huge data sets, and this course is specifically designed to bring you up to speed on one of the best technologies for this task, Apache Spark! The top technology companies like Google, Facebook, Netflix, Airbnb, Amazon, NASA, and more are all using Spark to solve their big data problems!
Spark can perform up to 100x faster than Hadoop MapReduce, which has caused an explosion in demand for this skill! Because the Spark 2.0 DataFrame framework is so new, you now have the ability to quickly become one of the most knowledgeable people in the job market!
This course will teach the basics with a crash course in Python, continuing on to learning how to use Spark DataFrames with the latest Spark 2.0 syntax! Once we've done that we'll go through how to use the MLlib Machine Library with the DataFrame syntax and Spark. All along the way you'll have exercises and Mock Consulting Projects that put you right into a real world situation where you need to use your new skills to solve a real problem!
We also cover the latest Spark Technologies, like Spark SQL, Spark Streaming, and advanced models like Gradient Boosted Trees! After you complete this course you will feel comfortable putting Spark and PySpark on your resume! This course also has a full 30 day money back guarantee and comes with a LinkedIn Certificate of Completion!
If you're ready to jump into the world of Python, Spark, and Big Data, this is the course for you!
Who this course is for:
- Someone who knows Python and would like to learn how to use it for Big Data
- Someone who is very familiar with another programming language and needs to learn Spark