IT Training Big Data & Hadoop Courses in Dubai

Course Details

Taught by a 4 person team including 2 Stanford-educated, ex-Googlers and 2 ex-Flipkart Lead Analysts. This team has decades of practical experience in working with Java and with billions of rows of data. 

This course is a zoom-in, zoom-out, hands-on workout involving Hadoop, MapReduce and the art of thinking parallel. 

Let’s parse that.

Zoom-in, Zoom-Out:  This course is both broad and deep. It covers the individual components of Hadoop in great detail, and also gives you a higher level picture of how they interact with each other. 

Hands-on workout involving Hadoop, MapReduce: This course will get you hands-on with Hadoop very early on.  You'll learn how to set up your own cluster using both VMs and the Cloud. All the major features of MapReduce are covered - including advanced topics like Total Sort and Secondary Sort. 

The art of thinking parallel: MapReduce completely changed the way people thought about processing Big Data. Breaking down any problem into parallelizable units is an art. The examples in this course will train you to "think parallel". 

What's Covered: Lot's of cool stuff ..

Using MapReduce to:

• Recommend friends in a Social Networking site: Generate Top 10 friend recommendations using a Collaborative filtering algorithm. 
• Build an Inverted Index for Search Engines: Use MapReduce to parallelize the humongous task of building an inverted index for a search engine. 
• Generate Bigrams from text: Generate bigrams and compute their frequency distribution in a corpus of text. 

Build your Hadoop cluster: 

• Install Hadoop in Standalone, Pseudo-Distributed and Fully Distributed modes 
• Set up a Hadoop cluster using Linux VMs.
• Set up a cloud Hadoop cluster on AWS with Cloudera Manager.
• Understand HDFS, MapReduce and YARN and their interaction 

Customize your MapReduce Jobs: 

• Chain multiple MR jobs together
• Write your own Customized Partitioner
• Total Sort: Globally sort a large amount of data by sampling input files
• Secondary sorting 
• Unit tests with MR Unit
• Integrate with Python using the Hadoop Streaming API

.. and of course all the basics: 

• MapReduce: Mapper, Reducer, Sort/Merge, Partitioning, Shuffle and Sort
• HDFS & YARN: Namenode, Datanode, Resource manager, Node manager, the anatomy of a MapReduce application, YARN Scheduling, Configuring HDFS and YARN to performance tune your cluster. 

Using discussion forums

Please use the discussion forums on this course to engage with other students and to help each other out. Unfortunately, much as we would like to, it is not possible for us at Loonycorn to respond to individual questions from students:-(

We're super small and self-funded with only 2 people developing technical video content. Our mission is to make high-quality courses available at super low prices.

The only way to keep our prices this low is to *NOT offer additional technical support over email or in-person*. The truth is, direct support is hugely expensive and just does not scale.

We understand that this is not ideal and that a lot of students might benefit from this additional support. Hiring resources for additional support would make our offering much more expensive, thus defeating our original purpose.

It is a hard trade-off.

Thank you for your patience and understanding!

Who is the target audience?

• Yep! Analysts who want to leverage the power of HDFS where traditional databases don't cut it anymore
• Yep! Engineers who want to develop complex distributed computing applications to process lot's of data
• Yep! Data Scientists who want to add MapReduce to their bag of tricks for processing data

BASIC KNOWLEDGE

• You'll need an IDE where you can write Java code or open the source code that's shared. IntelliJ and Eclipse are both great options.
• You'll need some background in Object-Oriented Programming, preferably in Java. All the source code is in Java and we dive right in without going into Objects, Classes etc
• A bit of exposure to Linux/Unix shells would be helpful, but it won't be a blocker

WHAT YOU WILL LEARN

• Develop advanced MapReduce applications to process BigData
• Master the art of "thinking parallel" - how to break up a task into Map/Reduce transformations
• Self-sufficiently set up their own mini-Hadoop cluster whether it's a single node, a physical cluster or in the cloud.
• Use Hadoop + MapReduce to solve a wide variety of problems: from NLP to Inverted Indices to Recommendations
• Understand HDFS, MapReduce and YARN and how they interact with each other
• Understand the basics of performance tuning and managing your own cluster

Course Details

Big Data and Hadoop

Course description

It is a comprehensive Hadoop Big Data training course designed by industry experts considering current industry job requirements to help you learn Big Data Hadoop and Spark modules. This is an industry-recognized Big Data certification training course that is a combination of the training courses in Hadoop developer, Hadoop administrator, Hadoop testing and analytics with Apache Spark.

Course outline

1. The big picture of Big Data

2. Demystifying Hadoop

3. Setup and Installation of Hadoop

4. HDFS – The Storage Layer

5. A Deep Dive into MapReduce

6. MapReduce - Advanced Concepts

7. Hive – Data Analysis Tool

8. Pig – Data Analysis Tool

9. NoSQL Database - HBase

10. Data Collection using Sqoop

11. Data Collection using Flume

12. Apache YARN & advanced concepts in the latest version

13. Processing data with Apache Spark

14. Real-Life Project on Big Data

Course Details

This Short-Term Program – designed by veterans in the Analytics industry; helps you master ‘Spark with Python’, which is predominantly used in Data Science. This course will help you learn and master the Python Programming language that is widely used among software developers for build control and management, testing, and in many other ways. You can become a Software Developer once you have mastered the Python Programming language – one of the most popular tools for data analysis. Learners are required to complete 10 weeks of faculty led Online mode. The following are the modules covered Refresher Python Programming Spark Introduction and Architechture Spark RDDs Spark transformation and actions  Spark DataFrames and SparkSQL Apache Flume and Apache Kafka Spark Streaming Spark Streaming - Processing Mulitple batches Introduction to SparkMLib

This program is brought to you by Praxis B schoolThe entry-level course is a gateway to the world of analytics that enables the students to gain expertise knowledge from top instructors for high data processing, querying, data analysis operations and generating analytics reports in a faster way, paving a way to the career world. 

Course Details

This Short-Term Program – designed by veterans in the Analytics industry; helps you master the ‘R’ tool, which is predominantly used in Data Science. This course will help you learn and master the R language specifically for Data Science, wherein it is widely used to build methods, processes, and systems to extract knowledge or insights from data in various forms. You can become a Data Science Expert once you have mastered R – one of the most popular tools for data science. Learners are required to complete 10 weeks of faculty led Online mode. The following are the modules covered Machine Learning with R & Python Introduction to NumPy Introduction to Pandas Slicing Data Exploratory Data Analysis Exploratory Data Analysis (Continue) Missing Value Imputation and Outlier Analysis Linear Regression Motivation Linear Regression optimization objective Linear Regression in Python Introduction to Regression Tree Introduction to Classification Tree Measures of Selecting the best Split Cluster Analysis – Hierarchical Clustering & k-Means Clustering Customer segmentation in Telecom Industry using Cluster Analysis k-Means clustering Association Rules mining Market Basket Analysis

This program is brought to you by Praxis B schoolThe course is designed to enable the candidates to be responsible for business analytics, building data products and software platforms, along with developing visualizations and machine learning algorithms.

Course Details

This Short-Term Program – designed by veterans in the Analytics industry; helps you master the ‘Access Method’ tool, which is predominantly used in Data Science. This course will help you learn and master Access Methods used to access data on disk, tape or other external devices. It will help you understand how Access Methods is used technically and its future prospects. Learners are required to complete 10 weeks of faculty led Online mode. The following are the modules covered Flume introduction Data streaming demo through Flume Scala Programming - Intro Scala Programming Spark Shell, Spark Context, RDD Spark Streaming Architecture Oozie Components, Scheduling with Oozie, Demo on Oozie Workflow, Oozie Co-ordinator, Oozie Commands.

The course enables the canThis program is brought to you by Praxis B school

candidates to be valuable expertise to any organization that uses the database program. They may be database users, Access trainers, database creators, user-supporters, teachers, or professors. Because of the level of knowledge required to obtain certification, they often become the Access experts within their organizations.

Course Details

This course will help you learn and master the tools used in Web Analytics which are widely used for measurement, collection, analysis and reporting of web data for purposes of understanding and optimizing web usage. You can become a Web Analytics Expert once you have mastered the tools like Google Analytics, Spring Metrics, Woopra, etc. Learners are required to complete 6 weeks of faculty led Online mode.

The following are the modules covered

• Web Analytics
• Introduction to Digital Media Analytics
• Introduction to Google Analytics
• Concept of Account, Property and View
• Concept of Sessions and Users
• Concept of Dimension, Metric and Segment
• Reading a Google Analytics Report
• Audience Analytics
• Acquisition Analytics
• Behaviour Analytics
• Real-Time Analytics
• Setting Up and Analysing Events
• Intelligent Events
• Setting Up and Analysing Experiments
• Setting Up and Measuring Conversion Goals
• Attribution Modelling
• Segment Reporting
• Designing Custom Reports
• Introduction to Google Adwords
• Search Marketing
• Display Marketing
• Google Adwords Analytics
• Managing a Google Analytics Account

This program is brought to you by Praxis B school

The course is designed in such a way that the candidates equip and master the critical elements of the web, mobile and other social media platform to make apt business decisions. The candidates will be highly expertise at performing qualitative & quantitative searches, gathering and working with multi-channel data sources.

Course Details

This course will help you learn and master the R language that is widely used among arithmeticians and data miners for mounting statistical software and data examination. You can become a Statistics Expert once you have mastered R – one of the most popular tools for data analysis and statistics. Learners are required to complete 10 weeks of faculty led Online mode. The following are the modules covered

• Statistics with R
• Introduction to Data
• Introduction to Probability
• Distributions
• Introduction to linear regression
• Foundations for inference and estimation
• Foundations for inference and hypothesis testing
• Linear Regression and Multiple Regression

This program is brought to you by Praxis B school

In this specialization, you will learn to analyze and visualize data in R and create data reproducible data analysis report, demonstrate a conceptual understanding of the unified nature of statistical inference, make data-based decisions, visualize date with R packages and communicate effectively without relying on statistical jargon. 

Course Details

The Statistics 101 course will help you build knowledge about the current trends and future aspects of Statistics. It will help you understand how Statistics is used in businesses, corporates, governments to assemble data and draw conclusions using specific mathematical formula. Learners are required to complete 6 weeks of faculty led Online mode. The following are the modules covered Statistics 101 Introduction to Statistics Introduction to Statistics – II Measures of Central Tendency, Spread and Shape – I CMeasures of Central Tendency, Spread and Shape – II Measures of Central Tendency, Spread and Shape – III Measuring Association

This program is brought to you by Praxis B school

The entry-level course is a gateway to the world of analytics that covers the fundamentals of statistics that enables the candidates to gather industry knowledge in Data Visualization, Summarizing Data, Displaying and Comparing Quantitative Data, and more.

Course Details

This course will help you learn and master the RDSMS that is widely used in database management systems to manage and examine huge amount of data. You can become a Data Analyst Expert once you have mastered RDSMS – one of the most popular tools in database management systems. Learners are required to complete 6 weeks of faculty led Online mode. The following are the modules covered RDBMS with SQL and DWH Introduction to DBMS / RDBMS Data Modelling Physical Data Model Getting Started with SQL Lite DDL DML Introduction to Data Warehousing Dimensional Modelling Advanced SQL Olap Cubes Olap Cubes Practicals

This program is brought to you by Praxis B school

This program is designed to equip candidates with immense industry knowledge in relational database management systems, to describe the data, to define and manipulate date, to create and drop database and tables, administration, upgrading and improving current database, retaining and protecting the reliability of data.

Course Details

This course will help you learn and master the R language that is widely used among arithmeticians and data miners for mounting statistical software and data examination. You can become a Data Analyst Expert once you have mastered R – one of the most popular tools for data analysis. Learners are required to complete 6 weeks of faculty led Online mode. The following are the modules covered R Programming R Programming Introduction to R – I Introduction to R – II Common Data Structures in R Conditional Operation and Loops Looping in R using Apply Family Functions Creating User Defined Functions in R Graphics with R Advanced Graphics with R

This program is brought to you by Praxis B school

The program is designed to enable candidates with effectual industry knowledge for data importing and cleaning, statistical computing and designing, creating tools for data analysis, data modeling, data visualization and more, useful for their career.

Course Details

This course will help you learn and master the tools used in Text Analytics which are widely used for deriving high-quality information from text through data mining. You can become a Text Analytics Expert once you have mastered the tools like Lexalytics, IBM Watson AlchemyAPI, Sysomos, etc. Learners are required to complete 6 weeks of faculty led Online mode. The following are the modules covered Text Analytics Basics of text analysis processes Web crawling Web Scraping from downloaded html files Text classification Singular Value decomposition concept Latent Semantic Analysis Document clustering Topic Modeling Class Assignments Presentation

This program is brought to you by Praxis B school

The program covers the essentials of text analytics in text categorization, text clustering, sentimental analysis, concept extraction, document summarization and entity related modeling. 

Course Details

This course will help you learn and master the Python Programming language that is widely used among software developers for build control and management, testing, and in many other ways. You can become a Software Developer once you have mastered the Python Programming language – one of the most popular tools for data analysis. Learners are required to complete 4 weeks of faculty led Online mode. The following are the modules covered Python Understanding Basics of Python Control Structures and for loop Playing with while loop | break and continue Strings and files List Dictionary and Tuples

This program is brought to you by Praxis B school

This course is designed to provide in-depth knowledge in open source and object-oriented programming language to serve purposes like website programming, writing system administration software, software testing, desktop application development and much more.

Course Details

This course will help you learn and master the Hadoop Software which is widely used for distributed storage and processing of datasets of big data. You can become a Big Data Engineer once you have mastered the Apache Hadoop Software – one of the most popular tools for used for processing of datasets of big data. Learners are required to complete 10 weeks of faculty led Online mode. The following are the modules covered Hadoop Introduction to Big Data and Hadoop Introduction to DBMS systems using MySQL Big Data and Hadoop EcoSystem HDFS Unix & HDFS Hands-on Map-Reduce basics Map Reduce Advanced Topics and Hands on Pig introduction and Hands on Pig Scripting Hive Introduction, Metastore, Limitations of Hive Comparison with Traditional Database and HIVE scripting Hive Data Types, Partitioning and Bucketing Hive Tables (Managed and External) Hive Continued Scoop Introduction and Hands-on Introduction to NoSql and HBASE HBASE architecture and Hands-on

This program is brought to you by Praxis B school

The candidates are provided with ground breaking online certificate courses in Hadoop to program, execute parallel processing, testing designing and developing systems, and documentation skills.

Course Details

This course will help you learn and master the Data Visualization with Tableau which is widely used in corporates for business intelligence. You can become a Tableau expert once you have mastered this software – one of the most popular tools for Business Intelligence and Analytics. Learners are required to complete 6 weeks of faculty led Online mode. The following are the modules covered Data Visualization with Tableau Need for visualizing data Research methodologies Importance of Big data visualization Tableau product offerings Installation of Tableau Public Working with Tableau - Live Case study/Discussion Creating interactive dashboards with Tableau Public Case study discussion Story Boarding with Tableau Public Case study discussion Geomapping in Tableau Qlik view – Basics Google charts – Basics Dynamic charts with Google Docs Supplementary material & Case study discussion Closing session & Queries

This program is brought to you by Praxis B school

This high-end program designed and delivered by top industry experts and professors train the new generation of data-savvy professionals for fast analytics, producing visualizations for an outsized quantity of information and integration.

Course Details

This course will help you learn and master the R language that is widely used among arithmeticians and data miners for mounting statistical software and data examination. You can become an Advanced Statistics Expert once you have mastered R – one of the most popular tools for data analysis and statistics. Learners are required to complete 10 weeks of faculty led Online mode. The following are the modules covered  

• Advanced Statistics with R
• Inference and hypothesis testing on single population
• Analysis of difference in two populations
• Analysis of Variance
• Chi-Square Analysis
• Analysis of data using Non-parametric Statistics
• Linear regression analysis
• Multiple regression analysis
• Advanced Multiple regression analysis
• Logistic Regression
• Forecasting

This program is brought to you by Praxis B school

This program will provide guidance for Statisticians in manipulation, preparation, exploration, and visualization on different kinds of business data. Along with training modules on these phases, predictive analytics techniques like regression models, clustering and decision trees are covered using real time case studies.

Course Details

This course will help you learn and master the R language specifically for Advanced Data Science, wherein it is widely used to build methods, processes, and systems to extract knowledge or insights from data in various forms. You can become an Advanced Data Science Expert once you have mastered R – one of the most popular tools for data science. Learners are required to complete 10 weeks of faculty led Online mode. The following are the modules covered Big Data 101 Big Data Characteristics Big Data and Business Case Studies Data Relationships and Data Model Data Grouping Clustering Algorithms Getting ready for Clustering Algorithms KPIs, Businesses & Data Elements Mapping for business outcomes Basic Query Advanced Query – Embedding R Programming R Programming Introduction to R – I Introduction to R – II Common Data Structures in R Conditional Operation and Loops Looping in R using Apply Family Functions Creating User Defined Functions in R Graphics with R Advanced Graphics with R Statistics 101 Introduction to Statistics Introduction to Statistics – II Measures of Central Tendency, Spread and Shape – I Measures of Central Tendency, Spread and Shape – II Measures of Central Tendency, Spread and Shape – III Machine Learning with R Introduction to R, R Studio and Basic R Operations Import, Export and Data Manipulation with R Concept of data structure in R Concept of Index in R Creating Boolean index in R based on conditions Hands on exercise Understanding Loops in R Building User functions in R Basic R Graphics Understanding data clustering concepts and techniques Running clustering in R with Silhouette distance measure for cluster validity Understanding data classification concepts and techniques using decision trees Model building concepts and techniques Concepts of Association Rule Mining Building association rules and interpretation

This program is brought to you by Praxis B school

The course is designed to enable the candidates to be responsible for business analytics, building data products and software platforms, along with developing visualizations and machine learning algorithms.

Course Details

Professional Certificate Program in Big Data Technologies is one of the key requisites in any large organization. The time is at its best for someone to take up a career in this domain. Enormous opportunities and extreme dearth in getting candidates force large organizations go helter-skelter. It is imperative that career seekers grab this opportunity. Learners are required to complete 3-6 months of faculty led Online mode.

The following are the subjects covered  

• Big Data 101
• Big Data Characteristics
• Big Data and Business
• Data Relationships and Data Model
• Data Grouping
• Clustering Algorithms
• Getting ready for Clustering Algorithms
• Clustering Algorithms – UPGMA, single Link Clustering
• KPIs, Businesses & Data Elements
• Mapping for business outcomes
• Basic Query
• Advanced Query – Embedding
• Mathematics Modelling
• Introduction to key mathematical concepts
• Application of eigenvalues and eigenvectors
• Application of the graph Laplacian
• Application of PCA and SVD
• Coding in DB Environment
• Making Data Sets

• Statistics 101
• Introduction to Statistics
• Introduction to Statistics – II
• Measures of Central Tendency, Spread and Shape – I
• Measures of Central Tendency, Spread and Shape – II
• Measures of Central Tendency, Spread and Shape – III
• R Programming
• R Programming
• Introduction to R – I
• Introduction to R – II
• Common Data Structures in R
• Conditional Operation and Loops
• Looping in R using Apply Family Functions
• Creating User Defined Functions in R
• Graphics with R
• Advanced Graphics with R

• Hadoop
• Introduction to Big Data and Hadoop
• Introduction to DBMS systems using MySQL
• Big Data and Hadoop EcoSystem
• HDFS
• Unix & HDFS Hands-on
• Map-Reduce basics
• Map Reduce Advanced Topics and Hands on
• Pig introduction and Hands on
• Pig Scripting
• Hive Introduction, Metastore, Limitations of Hive
• Comparison with Traditional Database and HIVE scripting
• Hive Data Types, Partitioning and Bucketing
• Hive Tables (Managed and External)
• Hive Continued
• Scoop Introduction and Hands-on
• Introduction to NoSql and HBASE
• HBASE architecture and Hands-on

Access Methods Big Data with Spark and Python

• Python
• Understanding Basics of Python
• Control Structures and for loop
• Playing with while loop | break and continue
• Strings and files
• List
• Dictionary and Tuples
• RDBMS with SQL and DWH
• Introduction to DBMS / RDBMS
• Data Modelling
• Physical Data Model
• Getting Started with SQL Lite
• DDL
• DML
• Introduction to Data Warehousing
• Dimensional Modelling
• Advanced SQL
• Olap Cubes
• Olap Cubes Practicals

This program is brought to you by Praxis B school

At the completion of this course, students will be able to build their career in Software Development, Testing, Administration, Building Data, Processing Systems and Data Warehousing.

Course Details

Certificate Program in Big Data Technologies is one of the key requisites in any large organization. The time is at its best for someone to take up a career in this domain. Enormous opportunities and extreme dearth in getting candidates force large organizations go helter-skelter. It is imperative that career seekers grab this opportunity. Learners are required to complete 3 months of faculty led Online mode. The following are the subjects Big Data 101 Big Data Characteristics Big Data and Business Data Relationships and Data Model Data Grouping Clustering Algorithms Getting ready for Clustering Algorithms Clustering Algorithms – UPGMA, single Link Clustering KPIs, Businesses & Data Elements Mapping for business outcomes Basic Query Advanced Query – Embedding Mathematics Modelling Introduction to key mathematical concepts Application of eigenvalues and eigenvectors Application of the graph Laplacian Application of PCA and SVD Coding in DB Environment Making Data Sets R Programming R Programming Introduction to R – I Introduction to R – II Common Data Structures in R Conditional Operation and Loops Looping in R using Apply Family Functions Creating User Defined Functions in R Graphics with R Advanced Graphics with R Hadoop Introduction to Big Data and Hadoop Introduction to DBMS systems using MySQL Big Data and Hadoop EcoSystem HDFS Unix & HDFS Hands-on Map-Reduce basics Map Reduce Advanced Topics and Hands on Pig introduction and Hands on Pig Scripting Hive Introduction, Metastore, Limitations of Hive Comparison with Traditional Database and HIVE scripting Hive Data Types, Partitioning and Bucketing Hive Tables (Managed and External) Hive Continued Scoop Introduction and Hands-on Introduction to NoSql and HBASE HBASE architecture and Hands-on Big Data with Spark and Python The job market for candidates with Hadoop skills is revealing. The course enables candidates to build their career in Software Development, Testing, Administration, Building Data, Processing Systems and Data Warehousing.

This course is brought to you by Praxis B school

Course Details

Hadoop is an open-source software framework for storing data and running applications on clusters of commodity hardware. It provides massive storage for any kind of data, enormous processing power and the ability to handle virtually limitless concurrent tasks or jobs.

• We are best in town when it comes to training Big Data Hadoop aspirants online.

• We work in small batches; our students enjoy our full and undivided attention all the time.

• We provide necessary study material to our students.

• We are a team of professional trainers with years of domain expertise. 

• We offer training solutions that are true value-for-money. 

• We are passionate about enhancing excellence and committed to quality.

Course Details

• Be trained by highly qualified and certified instructors
• Have access to the Innosoft Gulf course material
• Obtain a course completion certificate from Innosoft Gulf

Course Details

This course is a really comprehensive guide to the Google Cloud Platform - it has ~25 hours of content and ~60 demos.

The Google Cloud Platform is not currently the most popular cloud offering out there - that's AWS of course - but it is possibly the best cloud offering for high-end machine learning applications. That's because TensorFlow, the super-popular deep learning technology is also from Google.

What's Included:

• Compute and Storage - AppEngine, Container Enginer (aka Kubernetes) and Compute Engine
• Big Data and Managed Hadoop - Dataproc, Dataflow, BigTable, BigQuery, Pub/Sub 
• TensorFlow on the Cloud - what neural networks and deep learning really are, how neurons work and how neural networks are trained.
• DevOps stuff - StackDriver logging, monitoring, cloud deployment manager
• Security - Identity and Access Management, Identity-Aware proxying, OAuth, API Keys, service accounts
• Networking - Virtual Private Clouds, shared VPCs, Load balancing at the network, transport and HTTP layer; VPN, Cloud Interconnect and CDN Interconnect
• Hadoop Foundations: A quick look at the open-source cousins (Hadoop, Spark, Pig, Hive and HBase)

Who is the target audience?

• Yep! Anyone looking to use the Google Cloud Platform in their organizations
• Yep! Anyone who is interesting in architecting computes, networking, loading balancing and other solutions using the GCP
• Yep! Anyone who wants to deploy serverless analytics and big data solutions on the Google Cloud
• Yep! Anyone looking to build TensorFlow models and deploy them on the cloud

BASIC KNOWLEDGE

• Basic understanding of technology - superficial exposure to Hadoop is enough.

WHAT YOU WILL LEARN

• Deploy Managed Hadoop apps on the Google Cloud
• Build deep learning models on the cloud using TensorFlow
• Make informed decisions about Containers, VMs and AppEngine
• Use big data technologies such as BigTable, Dataflow, Apache Beam and Pub/Sub

Course Details

Taught by a 4 person team including 2 Stanford-educated, ex-Googlers and 2 ex-Flipkart Lead Analysts. This team has decades of practical experience in working with Java and with billions of rows of data. 

This course is a zoom-in, zoom-out, hands-on workout involving Hadoop, MapReduce and the art of thinking parallel. 

Let’s parse that.

Zoom-in, Zoom-Out:  This course is both broad and deep. It covers the individual components of Hadoop in great detail, and also gives you a higher level picture of how they interact with each other. 

Hands-on workout involving Hadoop, MapReduce : This course will get you hands-on with Hadoop very early on.  You'll learn how to set up your own cluster using both VMs and the Cloud. All the major features of MapReduce are covered - including advanced topics like Total Sort and Secondary Sort. 

The art of thinking parallel: MapReduce completely changed the way people thought about processing Big Data. Breaking down any problem into parallelizable units is an art. The examples in this course will train you to "think parallel". 

What's Covered: Lot's of cool stuff ..

Using MapReduce to:

• Recommend friends in a Social Networking site: Generate Top 10 friend recommendations using a Collaborative filtering algorithm. 
• Build an Inverted Index for Search Engines: Use MapReduce to parallelize the humongous task of building an inverted index for a search engine. 
• Generate Bigrams from text: Generate bigrams and compute their frequency distribution in a corpus of text. 

Build your Hadoop cluster: 

• Install Hadoop in Standalone, Pseudo-Distributed and Fully Distributed modes 
• Set up a hadoop cluster using Linux VMs.
• Set up a cloud Hadoop cluster on AWS with Cloudera Manager.
• Understand HDFS, MapReduce and YARN and their interaction 

Customize your MapReduce Jobs: 

• Chain multiple MR jobs together
• Write your own Customized Partitioner
• Total Sort : Globally sort a large amount of data by sampling input files
• Secondary sorting 
• Unit tests with MR Unit
• Integrate with Python using the Hadoop Streaming API

.. and of course all the basics: 

• MapReduce : Mapper, Reducer, Sort/Merge, Partitioning, Shuffle and Sort
• HDFS & YARN: Namenode, Datanode, Resource manager, Node manager, the anatomy of a MapReduce application, YARN Scheduling, Configuring HDFS and YARN to performance tune your cluster. 

Using discussion forums

Please use the discussion forums on this course to engage with other students and to help each other out. Unfortunately, much as we would like to, it is not possible for us at Loonycorn to respond to individual questions from students:-(

We're super small and self-funded with only 2 people developing technical video content. Our mission is to make high-quality courses available at super low prices.

The only way to keep our prices this low is to *NOT offer additional technical support over email or in-person*. The truth is, direct support is hugely expensive and just does not scale.

We understand that this is not ideal and that a lot of students might benefit from this additional support. Hiring resources for additional support would make our offering much more expensive, thus defeating our original purpose.

It is a hard trade-off.

Thank you for your patience and understanding!

Who is the target audience?

• Yep! Analysts who want to leverage the power of HDFS where traditional databases don't cut it anymore
• Yep! Engineers who want to develop complex distributed computing applications to process lot's of data
• Yep! Data Scientists who want to add MapReduce to their bag of tricks for processing data

BASIC KNOWLEDGE

• You'll need an IDE where you can write Java code or open the source code that's shared. IntelliJ and Eclipse are both great options.
• You'll need some background in Object-Oriented Programming, preferably in Java. All the source code is in Java and we dive right in without going into Objects, Classes etc
• A bit of exposure to Linux/Unix shells would be helpful, but it won't be a blocker

WHAT YOU WILL LEARN

• Develop advanced MapReduce applications to process BigData
• Master the art of "thinking parallel" - how to break up a task into Map/Reduce transformations
• Self-sufficiently set up their own mini-Hadoop cluster whether it's a single node, a physical cluster or in the cloud.
• Use Hadoop + MapReduce to solve a wide variety of problems : from NLP to Inverted Indices to Recommendations
• Understand HDFS, MapReduce and YARN and how they interact with each other
• Understand the basics of performance tuning and managing your own cluster

Course Details

Master Hadoop framework’s concepts, along with its deployment in a cluster environment

Learn to write complex MapReduce programs

From this course, students will learn:

• Perform Data Analytics using Pig and Hive Hadoop Components
• Acquire an in-depth understanding of the Hadoop ecosystem including Flume, Apache Oozie workflow scheduler, and more
• Master advanced Hadoop concepts including Hbase, Zookeeper, and Sqoop
• Get hands-on experience in setting up different Hadoop cluster configurations
• Work on real-life, industry-based projects using Hadoop.

Course Details

We offer advanced learning with in-depth knowledge. The course is structured in detailed fashion and help our students in attaining success with best commitment support. The key specialities are :

• Introduction
• Starting MEP Projects
• Modifying System Settings
• Planning Mechanical Systems
• Designing Mechanical Air Systems
• Designing Mechanical Piping System
• Planning Electrical System
• Designing Electrical System
• Plumbing System
• Planning Fire Protection System
• Designing fire Protection System
• Creating Documentation View
• Annotation and Dimensioning
• Detailing
• Revit Families
• Conclusion