Apache Spark 2.0 + Python : DO Big Data Analytics & ML
4.5 (74 ratings)
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Apache Spark 2.0 + Python : DO Big Data Analytics & ML

Project Based, Hands-on Practices, Spark SQL, Spark Streaming, Real life Full cycle Project
4.5 (74 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
777 students enrolled
Last updated 1/2017
English
Current price: $10 Original price: $100 Discount: 90% off
1 day left at this price!
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Includes:
  • 7.5 hours on-demand video
  • 11 Articles
  • 3 Supplemental Resources
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
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What Will I Learn?
Acquire Knowledge of Apache Spark 2.0 fundamentals and architecture
Write Spark 2.0 scripts for Transformations, actions, Spark SQL and Spark Streaming
Execute Machine Learning / Data Science algorithms
Solve real world data problems with Apache Spark 2.0
Handle interviews for Apache Spark 2.0 confidently and get jobs
View Curriculum
Requirements
  • Python programming
  • Have a laptop/desktop to setup Spark
Description

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

  • Learn solid fundamentals of the domain
  • See demos, train and execute solid examples
  • Practice hands-on and validate it with solutions provided
  • Apply knowledge you acquired in an end-to-end real life project

Taught by an expert in the field, you will also get prompt response to your queries and excellent support from Udemy.

Who is the target audience?
  • Software Professionals
  • Big Data Architects
  • Data Engineers
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Curriculum For This Course
Expand All 58 Lectures Collapse All 58 Lectures 07:17:45
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Kick-start your learning
4 Lectures 13:32

About the mentor and setting expectations.

Preview 02:54

Introduction to the Learn-Train-Practice-Apply methodology

Preview 03:37


Resource Bundle - Code and Data
00:02
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Introduction to Apache Spark
7 Lectures 51:39

Introduction to Apache Spark

Start your Spark engines
07:58

Download Apache Spark and setup your Python environment to use Spark

<train/> Setup your Spark / Python environment
11:29

Run your first Spark program - get your hands dirty !

<train/> Run your first Spark Program !
05:36

Overview of Spark and its various modules and libraries

Apache Spark eco-system
06:11

Overview of Resilient Distributed Data Sets (RDD)

RDD : The foundation of Spark
05:15

Spark cluster architecture and scalability

Spark Architecture - How it all works.
11:09

Various steps/stages in a Spark project and how things happen.

Preview 04:01

Spark Architecture
5 questions
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Spark Programming with Python
15 Lectures 01:26:12

How you load external data into Spark and how data gets saved.

Loading and Storing Data
08:41

<train/> Loading and Storing Data
07:46

@Practice() Loading and Storing Data
00:12

Transformations - Change how data looks
09:41

<train/> Transformations
14:33

@Practice() Transformations
00:06

Actions - Extract insights from Data
08:39

<train/> Actions
07:30

@Practice() Actions
00:03

Key-Value RDDs
04:16

<train/> Key-Value RDDs
07:10

@Practice() Key-Value RDDs
00:06

Broadcast variables, accumulators, partitioning and persistence

Advanced Spark
10:42

<train/> Advanced Spark - Enhanced Capabilities
06:37

@Practice() Advanced Spark
00:08
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Spark SQL
6 Lectures 27:20
Spark SQL Data Frames - the new era
07:53

<train/> SQL Data Frames
11:18

@Practice() SQL Data Frames
00:17

Temp Tables / Views - Easy querying
02:42

<train/> Temp Tables / Views
05:04

@Practice() Temp Tables/ Views
00:05
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Spark Streaming
3 Lectures 22:33
Spark Streaming - real time data processing
05:14

Spark Streaming Architecture - how it works.
06:44

<train/> Spark Streaming
10:35
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Machine Learning with Spark
18 Lectures 03:42:34
Types of Analytics - simple to predictive
12:08

Types of Machine Learning
17:16

Analyzing results and Errors
13:46

Spark ML Concepts - new data types
08:09

Linear Regression - fit to a line
19:00

<train/> Linear Regression Use Case
17:15

Decision Trees Classification
10:42

<train/> Decision Trees Use Case
12:20

Principal Component Analysis
07:28

Random Forest Classification
10:31

<train/> Random Forests and PCA Use Case
14:00

Text Pre-processing with TF-IDF
14:53

Naive Bayes Classification
19:21

<train/> Naive Bayes and Text Pre-processing Use Case
07:32

K-Means Clustering - grouping similar items
11:53

<train/> K-Means Clustering Use Case
09:22

Recommendation Engines
11:55

<train/> Recommendation Engines Use Case
05:03
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APPLY : Your Course Challenge Project
3 Lectures 12:35
Real world problem Statement - Credit Card defaulters
00:02

Hints to help you with the project
00:03

The final solution is available in the resource bundle ( APPLY Project *.py)

Final Solution Review - we did it !
12:30
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Conclusion
2 Lectures 01:20
Closing Remarks
01:15

BONUS Lecture - Your next steps & Discount coupons
00:05
About the Instructor
V2 Maestros, LLC
4.2 Average rating
1,881 Reviews
19,957 Students
12 Courses
Big Data Science / Analytics Experts | 10K+ students

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.