Learn Hadoop and Big Data by Building Projects - FREE
Learn Hadoop and Big Data by Building Projects
Learn Hadoop and master how to organize & monetize your big data with this unique project-based online Hadoop training.
💓 Price : FREE
📝 Lectures: 42
📺 Video: 10 hours
📱 Level: All level
💼Languages: English
The comprehensive course covers Hadoop and all relevant technologies such as MapReduce, Python, Apache Pig, Kafka Streaming, Apache Storm, Yarn and Zookeeper, Apache Sqoop, Apache Solr, Apache Flume, Apache HCatelog, and many more. Not only this, the course will also teach you to do a predictive analysis using Hadoop and even Visual Analysis.
1 Introduction
Section 2 : ?Add Value to Existing Data with Mapreduce
2 Introduction to the Project
3 Build and Run the Basic Code
4 Understanding the Code
5 Dependencies and packages
Section 3 : Hadoop Analytics and NoSQL
6 Introduction to Hadoop Analytics
7 Introduction to NoSQL Database
8 Solution Architecture
9 Installing the Solution
Section 4 : Kafka Streaming with Yarn and Zookeeper
10 Introduction to Kafka Yarn and Zookeeper
11 Code Structure
12 Creating Kafka Streams
13 Yarn Job with Samza
Section 5 : Real Time Stream processing with Apache Kafka and Apache Storm
14 Real Time Streaming
15 Hortonbox Virtual Machine
16 Running in Cluster Mode
17 Submitting the Storm Jar
Section 6 : Big Data Applications for the Healthcare Industry with Apache Sqoop and Apache S
18 Introduction to the Project
19 Introduction to HDDAccess
20 Sqoop, Hive and Solr
21 Hive Usage
Section 7 : ?Log collection and analytics with the Hadoop Distributed File System using Apach
22 Apache Flume and HCatalog
23 Install and Configure Apache Flume
24 Visualisation of the Data
25 Embedded Pig Scripts
Section 8 : ?Data Science with Hadoop Predictive Analytics
26 Introduction to Data Science
27 Source Code Review
28 Setting Up the Machine
29 Project Review
Section 9 : Visual Analytics with Apache Spark on Yarn
30 Project Setup
31 Setting Up Java Dependencies
32 Spark Analytics with PySpark
33 Bringing it all together
Section 10 : Customer 360 degree view, Big Data Analytics for e-commerce
34 Ecommerce and Big Data
35 Installing Datameer
36 Analytics and Visualizations
37 Demonstration
Section 11 : Putting it all together Big Data with Amazon Elastic Map Reduce
38 Introduction to the Project
39 Configuration
40 Setting Up Cluster on EMR
41 Dedicated Task Cluster on EMR
Section 12 : Summary
42 Summary
The comprehensive course covers Hadoop and all relevant technologies such as MapReduce, Python, Apache Pig, Kafka Streaming, Apache Storm, Yarn and Zookeeper, Apache Sqoop, Apache Solr, Apache Flume, Apache HCatelog, and many more. Not only this, the course will also teach you to do a predictive analysis using Hadoop and even Visual Analysis.
Course Content :
Section 1 : Introduction1 Introduction
Section 2 : ?Add Value to Existing Data with Mapreduce
2 Introduction to the Project
3 Build and Run the Basic Code
4 Understanding the Code
5 Dependencies and packages
Section 3 : Hadoop Analytics and NoSQL
6 Introduction to Hadoop Analytics
7 Introduction to NoSQL Database
8 Solution Architecture
9 Installing the Solution
Section 4 : Kafka Streaming with Yarn and Zookeeper
10 Introduction to Kafka Yarn and Zookeeper
11 Code Structure
12 Creating Kafka Streams
13 Yarn Job with Samza
Section 5 : Real Time Stream processing with Apache Kafka and Apache Storm
14 Real Time Streaming
15 Hortonbox Virtual Machine
16 Running in Cluster Mode
17 Submitting the Storm Jar
Section 6 : Big Data Applications for the Healthcare Industry with Apache Sqoop and Apache S
18 Introduction to the Project
19 Introduction to HDDAccess
20 Sqoop, Hive and Solr
21 Hive Usage
Section 7 : ?Log collection and analytics with the Hadoop Distributed File System using Apach
22 Apache Flume and HCatalog
23 Install and Configure Apache Flume
24 Visualisation of the Data
25 Embedded Pig Scripts
Section 8 : ?Data Science with Hadoop Predictive Analytics
26 Introduction to Data Science
27 Source Code Review
28 Setting Up the Machine
29 Project Review
Section 9 : Visual Analytics with Apache Spark on Yarn
30 Project Setup
31 Setting Up Java Dependencies
32 Spark Analytics with PySpark
33 Bringing it all together
Section 10 : Customer 360 degree view, Big Data Analytics for e-commerce
34 Ecommerce and Big Data
35 Installing Datameer
36 Analytics and Visualizations
37 Demonstration
Section 11 : Putting it all together Big Data with Amazon Elastic Map Reduce
38 Introduction to the Project
39 Configuration
40 Setting Up Cluster on EMR
41 Dedicated Task Cluster on EMR
Section 12 : Summary
42 Summary
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