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Regex Software

Data Engineering (BigData)

(Batches Start in November, December 2025 & January 2026)

About The Program

With the belief to build a healthy ecosystem as per the Industry Standards REGex Software brings a Industrial Internship & Training Program on “Data Engineering (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.

Key Benefits & Perks

  • Get Summer Internship Offer Letter
  • Need to Spend Min. 5 hours with REGex
  • Get Internship Project Completion Certificate
  • No Previous Knowledge Required
  • Get Summer Training Certificate
  • Get Performance based Letter of Recommendation (LOR)

November Batches Dates

Batch 1: 03rd November 2025
Batch 2: 10th November 2025
Batch 4: 17th November 2025
Batch 4: 24th November 2025

December Batches Dates

Batch 1: 01th December 2025
Batch 2: 08th December 2025
Batch 3: 15th December 2025
Batch 4: 22th December 2025

January Batches Dates

Batch 1: 05th January 2026
Batch 2: 12th January 2026
Batch 4: 19th January 2026
Batch 4: 26th January 2026

Weekly Duration

Location

Participants

20 Hours Per week

Physical (Jaipur)
or 
Online (Google Meet)
25 – 30 per Batch

What you will Learn

  • Linux basics 
  • Big Data Analytics & Hadoop
  • HDFS [ Hadoop Distributed File System ]
  • Map-Reduce [ Data Processing ]
  • HIVE
  • Apache Spark on Azure DataBricks
  • Neo4j Graph Analytics & NoSQL DataBase
  • Amazon EMR
  • Learn how to use these tools in the field of Data Analytics

Study Material

  • E-Notes
  • Assignments per day
  • Poll test per day
  • Live Video Lectures
  • Access of Lecture Videos & Notes
  • 24*7 Mentorship Support
  • Working on Live Projects 

Output

  • Help you in Data Analytics Domain
  • Able to think out of the box
  • Expertise in different Big Data Tools like HDFS, Hive, Apache Spark, Amazon EMR
  • Able to solve many Interview Questions of Top MNCs
  • Able to get package of Data Analyst in Big MNCs upto 30 LPA

Why Choose Us

Live Sessions

Live Sessions by Expertise Trainers and Access of Recorded Session is also available.

Live Projects
Get a chance to work on Industry Oriented Projects to implement your learning.
24*7 Support
24*7 Mentorship Support available for all Students to clear all of your doubts.
Opportunities
REGex provides Internship / Job opportunities to the best Students in different Companies.

Placed Students//Partnership

amazon
wipro
capgemini
google
microsoft
myntra
paytm
ibm
Cognizant
infosys
intel
hcl
hp
honeywell
oracle1
dell
fractal
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What People Tell About Us

Best IT Training and Internship Company in Jaipur. Highly recommended. Supportive faculties, Management, online and offline sessions access with recording access help every student to concentrate more on learning. Practical Learning and working on live projects with team is a main key highlights of REGEX.

Drishti Khandelwal Ex-Student, Django Batch

The experience of learning in the Institute is really good. I've joined the MERN full stack course doing well. Thanks to the mngt. To provide certified facility. Very helping in solving my queries and Institute provide me to practical knowledge and demo project to improve my skills..... Thnks to Regex software service

Gulshan S Arya Ex-Student, Mearn Stack

This training center is exceptional, providing me with extensive knowledge in various domains and technologies. I enrolled in the Python Django course eight months ago, where I learned website development. Prior to joining this coaching, I struggled with speaking English, but now I have gained the ability to communicate effectively. My experience has been extremely positive, and I strongly recommend joining The Regex Software Services at the earliest opportunity.

Mohit Sharma Ex-Student, python django

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

Yaman Singh Ex-Student, CP Batch

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

Josh Well Ex-Student, BigData Batch

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

Salman Khan Ex-Student, Django Batch

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!!

Jack Ryan Ex-Student, CP Batch

Placed Students

Gunjan Saini National Instruments
Gunjan Saini
National Instruments
Prem Wipro & IBM
Prem
Wipro & IBM
Purnima ponrajkumar Indium software
Purnima ponrajkumar
Indium software
sonal Wipro
sonal
Wipro
Mohammad Atash Shaikh Wipro
Mohammad Atash Shaikh
Wipro
Ayush Kumar srivastava Sopra
Ayush Kumar srivastava
Sopra
Sourav Dash Tek System
Sourav Dash
Tek System
Simran Khatri Techmatrix jaipur
Simran Khatri
Techmatrix jaipur
Madhav Sharma Cognizant
Madhav Sharma
Cognizant
Rajkishor. P. Game Redington India Ltd
Rajkishor. P. Game
Redington India Ltd
Bhuvan Nucleus software
Bhuvan
Nucleus software
Akshay Kachave Talent Sikha
Akshay Kachave
Talent Sikha
Vasavi Uppala NCR coperation
Vasavi Uppala
NCR coperation
Ashish Chauhan wipro
Ashish Chauhan
wipro
Pratik Choubey TCS
Pratik Choubey
TCS
Debarya Pal Accenture
Debarya Pal
Accenture
Vritika Vijay Kamra Larsen and toubro infotech
Vritika Vijay Kamra
Larsen and toubro infotech
Mihir Vatsa Infosys
Mihir Vatsa
Infosys
Divyansh Singh Sengar Infosys
Divyansh Singh Sengar
Infosys
Harsha Kumari Bank Of America
Harsha Kumari
Bank Of America
Vatan Gupta Accenture
Vatan Gupta
Accenture
Fardeen Khan Deloitte us
Fardeen Khan
Deloitte us
Divyanshi jain Deloitte
Divyanshi jain
Deloitte
Hritick goyal Ranjio
Hritick goyal
Ranjio
Sumodh c Sabu TCS
Sumodh c Sabu
TCS
Swati Accenture
Swati
Accenture
Nishant Kumar cognizant
Nishant Kumar
cognizant
Saquib Mansuri Circulants
Saquib Mansuri
Circulants
Dhanisha sharma TCS
Dhanisha sharma
TCS
Aditya Prasad Capgemini
Aditya Prasad
Capgemini
Sathvika Chekuri Barclays
Sathvika Chekuri
Barclays
Priyanshu Lasod Barclays Arcgate
Priyanshu Lasod
Barclays Arcgate
Jaya Mendhe Accenture
Jaya Mendhe
Accenture
Dipali Jp Morgan Chase & Co.
Dipali
Jp Morgan Chase & Co.
Meenal Hewlett-Packard
Meenal
Hewlett-Packard
Riya Khanna HSBC
Riya Khanna
HSBC
Muskan Hewlett-Packard
Muskan
Hewlett-Packard
Praveen Jangid Celebal Tech
Praveen Jangid
Celebal Tech
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Course Content

  • Basics of Python 
  • OOPs Concepts
  • File & Exception Handling
  • Working with Pandas, Numpy & Matplotlib
    ■ Working with Missing Data
    ■ Data Grouping
    ■ Data Subsetting
    ■ Merging & Joining Data Frames
  • Importing Libraries & Datasets

● 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

 Note: Content may Subject to Change by REGex as per Requirement

Download Program Brochure

Extra Sessions

Additinal Session on GIT, Linux, Docker, AWS Basics, Jenkins and many more for all students.

Projects you may work on

Live Client Projects With Development Team Under The Guidance Of Mentor
Project Use Cases

Fee Structure

Indian Fee (Physical)

Price: ₹75,000/- (Flat 66% off) => ₹25,000/-  
(Limited Period Special Offer)

Indian Fee (Online)

Price: ₹75,000/- (Flat 66% off) => ₹25,000/-  
(Limited Period Special Offer)

International Fee

Price: $1200 (Flat 66% off) => $400
(Limited Period Special Offer)

Fee Can be Paid as No Cost EMI of 6 Months @2500/Month.

Cashback Policy

  • You will get your Unique Referral Code after successful paid registration.
  • You will get Upto ₹1000 Cashback directly in your account for each paid registration from your Unique Referral Code (After Closing Registrations of this program) .
  • For Example:- If we received 10 paid registration from your Unique Referral Code then you will receive Upto ₹1000*10 = ₹10,000.
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(Batches Start from November, December 2025 & January 2026)

*It will help us to reach more
*Extra off is applicable on 1 time payment only. Seats can be filled or Price can be increased at any time. Refund policy is not available*