Note: 

   

If you guys are getting coupon expired or course is not free after opening the link, then it is due to the fact that course instructors provide only few hundreds or thousands of slots which get exhausted. So, try to enroll in the course as soon as it is posted in the channel. The Coupons may expire any time for instant notification follow telegram channel

New customer offer! Top courses from $13.99 when you first visit Udemy

Learn HDFS, Spark, Kafka, Machine Learning, Hadoop, Hadoop MapReduce, Cassandra, CAP, Predictive Analytics and much more

Description

Big data is a combination of structured, semi structured and unstructured data collected by organizations that can be mined for information and used in machine learning projects, predictive modelling and other advanced analytics applications.

 

Systems that process and store big data have become a common component of data management architectures in organizations, combined with tools that support big data analytics uses. Big data is often characterized by the three V’s:

 

the large volume of data in many environments;

 

the wide variety of data types frequently stored in big data systems; and

 

the velocity at which much of the data is generated, collected and processed.

 

Big data is a great quantity of diverse information that arrives in increasing volumes and with ever-higher velocity.

 

Big data can be structured (often numeric, easily formatted and stored) or unstructured (more free-form, less quantifiable).

 

Nearly every department in a company can utilize findings from big data analysis but handling its clutter and noise can pose problems.

 

Big data can be collected from publicly shared comments on social networks and websites, voluntarily gathered from personal electronics and apps, through questionnaires, product purchases, and electronic check-ins.

 

Big data is most often stored in computer databases and is analysed using software specifically designed to handle large, complex data sets.

 

Topics Covered in these course are:

 

Big Data Enabling Technologies

 

Hadoop Stack for Big Data

 

Hadoop Distributed File System (HDFS)

 

Hadoop MapReduce

 

MapReduce Examples

 

Spark

 

Parallel Programming with Spark

 

Spark Built-in Libraries

 

Data Placement Strategies

 

Data Placement Strategies

 

Design of Zookeeper

 

CQL (Cassandra Query Language)

 

Design of HBase

 

Spark Streaming and Sliding Window Analytics

 

Kafka

 

Big Data Machine Learning

 

Machine Learning Algorithm K-means using Map Reduce for Big Data Analytics

 

Parallel K-means using Map Reduce on Big Data Cluster Analysis

 

Decision Trees for Big Data Analytics

 

Big Data Predictive Analytics

 

PageRank Algorithm in Big Data

 

Spark GraphX & Graph Analytics

 

Case Studies of big companies and how they operate.

 

Who this course is for:

Graduates

Software engineers

Developers

Enroll Now