About this Course
The demand for professionals in data analysis has increased drastically since information can be translated to money. When it comes to processing big data, there is no other perfect software than Hadoop. So, what is Hadoop?
Hadoop is an open-source software framework that allows users to store and process large amounts of data in a distributed environment across clusters of computers that use simple programming models. Think you know everything about Hadoop? Think again.
Created by experts from the industry, our course is designed to not only provide you a comprehensive guide for learning Hadoop and Big Data, but it also breaks down related concepts and technologies associated with the software into meaningful tasks and concepts.
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.
Our course will test your limits of Hadoop and also help you build cutting edge knowledge of how Hadoop can be used in everyday big data analysis. Our course aims to make you a Hadoop Jedi.
The professional course will teach you to build the following projects:
Add Value to Existing Data – Learn how to use MapReduce to process large amounts of data and solve clustering problems.
Hadoop Analytics and NoSQL – Parse a twitter stream with Python, extract keyword with apache pig and map to hdfs, pull from hdfs and push to mongodb with pig, visualise data with node js. Learn all of this and much more in this cool tutorial.
Kafka Streaming with Yarn and Zookeeper – Set up a twitter stream with Python and a kafka stream with java coding. Learn how to pack and deploy java code with Apache Samza.
Real-Time Stream Processing with Apache Kafka and Apache Storm – Learn how to effectively use Apache Storm to focus on real-time streaming on twitter.
Big Data Applications for the Healthcare Industry with Apache Sqoop and Apache Solr – Set up the relational schema for a Health Care Data dictionary used by the US Dept of Veterans Affairs, demonstrate underlying technology and conceptual framework. Demonstrate issues with certain join queries that fail on MySQL, map technology to a Hadoop/Hive stack with Scoop and HCatalog, and learn how this stack can perform the query successfully.
Log collection and analytics with the Hadoop Distributed File System using Apache Flume and Apache HCatalog – Use Apache Flume and Apache HCatalog to map real time log stream to hdfs and tail this file as Flume event stream. Map data from hdfs to Python with Pig, use Python modules for analytic queries
Data Science with Hadoop Predictive Analytics – Create structured data with Mapreduce, Map data from hdfs to Python with Pig, run Python Machine Learning logistic regression, use Python modules for regression matrices and supervise training.
Visual Analytics with Apache Spark on Yarn – Create structured data with Mapreduce, Map data from hdfs to Python with Spark, convert Spark data frames and RDD’s to Python datastructures, Perform Python visualisations
Customer 360 degree view, Big Data Analytics for e-commerce – Demonstrate use of EComerce tool ‘Datameer’ to perform many fo the analytic queries from part 6, 7 and 8. Perform queries in the context of Senitment analysis and Twiteer stream.
Putting it all together Big Data with Amazon Elastic Map Reduce – Rub clustering code on AWS Mapreduce cluster. Using AWS Java sdk spin up a dedicated task cluster with the same attributes.
Leave the tired old tried methods and sign up to learn with hands-on experience. With our video course, you not only gain theoretical knowledge about the technologies but also hands on experience using the projects. So, what are you waiting for? Sign up now and start learning about how organizations solve their big data problems.