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Welcome to our course. Looking to learn Apache Spark 2.0, practice end-to-end projects and take it to a job interview? You have come to the RIGHT course! This course teaches you Apache Spark 2.0 with Python, trains you in building Spark Analytics and machine learning programs and helps you practice hands-on with an end-to-end real life application project. Our goal is to help you and everyone learn, so we keep our prices low and affordable.
Apache Spark is the hottest Big Data skill today. More and more organizations are adapting Apache Spark for building their big data processing and analytics applications and the demand for Apache Spark professionals is sky rocketing. Learning Apache Spark is a great vehicle to good jobs, better quality of work and the best remuneration packages.
The goal of this project is provide hands-on training that applies directly to real world Big Data projects. It uses the learn-train-practice-apply methodology where you
Taught by an expert in the field, you will also get prompt response to your queries and excellent support from Udemy.
Not for you? No problem.
30 day money back guarantee.
Learn on the go.
Desktop, iOS and Android.
Certificate of completion.
|Section 1: Kick-start your learning|
About the mentor and setting expectations.
Introduction to the Learn-Train-Practice-Apply methodology
Your Course Guide - Pathway to successPreview
Resource Bundle - Code and Data
|Section 2: Introduction to Apache Spark|
Introduction to Apache Spark
Download Apache Spark and setup your Python environment to use Spark
Run your first Spark program - get your hands dirty !
Overview of Spark and its various modules and libraries
Overview of Resilient Distributed Data Sets (RDD)
Spark cluster architecture and scalability
Various steps/stages in a Spark project and how things happen.
|Section 3: Spark Programming with Python|
How you load external data into Spark and how data gets saved.
<train/> Loading and Storing Data
@Practice() Loading and Storing Data
Transformations - Change how data looks
Actions - Extract insights from Data
<train/> Key-Value RDDs
@Practice() Key-Value RDDs
Broadcast variables, accumulators, partitioning and persistence
<train/> Advanced Spark - Enhanced Capabilities
@Practice() Advanced Spark
|Section 4: Spark SQL|
Spark SQL Data Frames - the new era
<train/> SQL Data Frames
@Practice() SQL Data Frames
Temp Tables / Views - Easy querying
<train/> Temp Tables / Views
@Practice() Temp Tables/ Views
|Section 5: Spark Streaming|
Spark Streaming - real time data processing
Spark Streaming Architecture - how it works.
<train/> Spark Streaming
|Section 6: Machine Learning with Spark|
Types of Analytics - simple to predictive
Types of Machine Learning
Analyzing results and Errors
Spark ML Concepts - new data types
Linear Regression - fit to a line
<train/> Linear Regression Use Case
Decision Trees Classification
<train/> Decision Trees Use Case
Principal Component Analysis
Random Forest Classification
<train/> Random Forests and PCA Use Case
Text Pre-processing with TF-IDF
Naive Bayes Classification
<train/> Naive Bayes and Text Pre-processing Use Case
K-Means Clustering - grouping similar items
<train/> K-Means Clustering Use Case
<train/> Recommendation Engines Use Case
|Section 7: APPLY : Your Course Challenge Project|
Real world problem Statement - Credit Card defaulters
Hints to help you with the project
The final solution is available in the resource bundle ( APPLY Project *.py)
|Section 8: Conclusion|
BONUS Lecture - Your next steps & Discount coupons
V2 Maestros is dedicated to teaching big data / data science at affordable costs to the world. Our instructors have real world experience practicing big data and data science and delivering business results. Big Data Science is a hot and happening field in the IT industry. Unfortunately, the resources available for learning this skill are hard to find and expensive. We hope to ease this problem by providing quality education at affordable rates, there by building data science talent across the world.