(Batches Start from 29th September 2022)
(2 Demo Sessions Available)
About The Program:
With the belief to build a healthy ecosystem as per the Industry Standards REGex Software brings a Training/Internship Program on “BigData”. We organize Training/Internship Program for improving the knowledge and skills of the Students/Professionals, so that they can become expert in the field of BigData and get their Dream Job in Software Development Field in Big MNCs.
REGex Software Services’s BigData program is a valuable resource for beginners and experts. This program will introduce you to Hadoop, HDFS, HIVE, Apache Spark Amazon EMR etc. from Basics to Advance. If you want to become BigData Analyst, REGex introduce this program for you.
Best affordable Python + Django program with live classes and doubt solving. You can also access to recordings of the classes. Teachers and mentor are very good. All syllabus covered in given time. With multiple live examples. Best part of training is friendly environment. Don't hesitate to enroll if you've never heard the name of this company before. You will not be disappointed.
Competitive Programming is the best course they have - i am part of both python and C++ course. Cracked several interviews with their course, poll test & assignment are always new and beneficial. Best CP course you will find here, i hope this will be beneficial for you
Tushar sir is best in delivery. His approach is mind blowing. I have not found any gap although I am from U.S Lots of Big Data tools I have learnt like Hadoop, Hive, Spark, Sqoop & most amazingly Talend ETL Tools which was the most lovely part of training. every component is told in very simple terms with great practical approach
I recently joined Python Django(Web Development - Full Stack)Course About Course: - I must say instructor makes every concept simple to understand - No Copy Paste,Every line of code is explained - Even given Assignments to work on - Even given Projects to work on If you looking to learn Python Django I highly recommend to go for this course
I am from UK & loved the teaching. Competitive Programming was the best experience I had in coding. I can truly say the money I spend is worth it. Go for it guys!!
Live Sessions by Expertise Trainers and Access of Recorded Session is also available
Get a chance to work on Industry Oriented Projects to implement your learning
24*7 Mentorship Support available for all Students to clear all of your doubts
REGex provides Internship / Job opportunities to the best Students in different Companies.
● Introduction to LINUX Operating System and Basic LINUX commands
● Operating System
● Basic LINUX Commands
● LINUX File System
● File Types
● File Permissions
● File Related Commands
● Filters
o Simple Filters
o Advanced Filters
● Vi Editor
● Input Mode Commands
● Vi Editor – Save & Quit
● Cursor Movement Commands
● Shell Variables
● Environmental Variables
● Shell script Commands
● Arithmetic Operations
● Command Substitution
● Command Line Arguments
● Business Intelligence
● Need for Business Intelligence
● Terms used in BI
● Components of BI
● Data Warehouse
● History of Data Warehousing
● Need for Data Warehouse
● Data Warehouse Architecture
● Data Mining Works with DWH
● Features of Data warehouse
● Data Mart
● Application Areas
● Dimension modeling
● Fact and Dimension tables
● Database schema
● Schema Design for Modeling
● Star, SnowFlake
● Fact Constellation schema
● Use of Data mining
● Data mining and Business Intelligence
● Types of data used in Data mining
● Data mining applications
● Data mining products
● What’s Big Data?
● Big Data: 3V’s
● Explosion of Data
● What’s driving Big Data
● Applications for Big Data Analytics
● Big Data Use Cases
● Benefits of Big Data
● History of Hadoop
● Distributed File System
● What is Hadoop
● Characteristics of Hadoop
● RDBMS Vs Hadoop
● Hadoop Generations
● Components of Hadoop
● HDFS Blocks and Replication
● How Files Are Stored
● HDFS Commands
● Hadoop Daemons
● Difference between Hadoop 1.0 and 2.0
● New Components in Hadoop 2.x
● YARN/MRv2
● Configuration Files in Hadoop 2.x
● Major Hadoop Distributors/Vendors
● Cluster Management & Monitoring
● Hadoop Downloads
● What is distributed computing
● Introduction to Map Reduce
● Map Reduce components
● How MapReduce works
● Word Count execution
● Suitable & unsuitable use cases for MapReduce
● Architecture
● Basic Syntax
● Import data from a table in a relational database into HDFS
● import the results of a query from a relational database into HDFS
● Import a table from a relational database into a new or existing Hive table
● Insert or update data from HDFS into a table in a relational database
● Define a Hive-managed table
● Define a Hive external table
● Define a partitioned Hive table
● Define a bucketed Hive table
● Define a Hive table from a select query
● Define a Hive table that uses the ORCFile format
● Create a new ORCFile table from the data in an existing non-ORCFile Hive table
● Specify the delimiter of a Hive table
● Load data into a Hive table from a local directory
● Load data into a Hive table from an HDFS directory
● Load data into a Hive table as the result of a query
● Load a compressed data file into a Hive table
● Update a row in a Hive table
● Delete a row from a Hive table
● Insert a new row into a Hive table
● Join two Hive tables
● Use a subquery within a Hive query
● An overview of functional programming
● Why Scala?
● REPL
● Working with functions
● objects and inheritance
● Working with lists and collections
● Abstract classes
● What is Spark?
● History of Spark
● Spark Architecture
● Spark Shell
● RDD Basics
● Creating RDDs in Spark
● RDD Operations
● Passing Functions to Spark
● Transformations and Actions in Spark
● Spark RDD Persistence
● Pair RDDs
● Transformations on Pair RDDs
● Actions Available on Pair RDDs
● Data Partitioning (Advanced)
● Loading and Saving the Data
● Accumulators
● Broadcast Variables
● Piping to External Programs
● Numeric RDD Operations
● Spark Runtime Architecture
● Deploying Applications
● Spark SQL Overview
● Spark SQL Architecture
● What are dataframe
● Manipulating Dataframes
● Reading new data from different file format
● Group By & Aggregations functions
● What is Spark streaming?
● Spark Streaming example
● Introduction of HBase
● Comparison with traditional database
● HBase Data Model (Logical and Physical models)
● Hbase Architecture
● Regions and Region Servers
● Partitions
● Compaction (Major and Minor)
● Shell Commands
● HBase using APIs
● Pre-requisites
● Introduction
● Architecture
● Installation and Configuration
● Repository
● Projects
● Metadata Connection
● Context Parameters
● Jobs / Joblets
● Components
● Important components
● Aggregation & working with Input & output data
● Pseudo Live Project (PLP) program is primarily to handhold participants who are fresh into the technology. In PLP, more importance given to “Process Adherence”
● The following SDLC activities are carried out during PLP
o Requirement Analysis
o Design ( High Level Design and Low Level Design)
o Design of UTP(Unit Test Plan) with test cases
o Coding
o Code Review
o Testing
o Deployment
o Configuration Management
o Final Presentation
Fee can be paid in 2 installments of 6k + 5k
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