Data Science and Analytics specialization course in Jaipur

(Batches Start in August, September & October 2025)

About The Program

Looking for the best Data Science courses with placement guarantee in Jaipur? At Regex Software, we offer industry-focused Data Science specialization courses in Jaipur designed to help you master AI, Machine Learning, Big Data, and Analytics. Our Data Science training institute in Jaipur provides hands-on training with real-world projects, expert mentorship, and 100% placement assistance. Whether you’re a fresher, IT professional, or career switcher, our Data Science and Analytics courses in Jaipur equip you with the skills to land a high-paying job in top companies. Enroll now and start your journey with the best Data Science coaching centre in Jaipur!

At Regex Software, we take pride in being a leading Data Science training institute in Jaipur, offering top-notch education and career support. With increasing demand for data scientists, this field offers some of the most lucrative career opportunities. Join the best Data Science course in Jaipur with Regex Software and take the first step towards a successful career. Limited seats available – enroll today!

Our course stands out among the top Data Science engineering courses in Jaipur, covering essential skills like Python, Machine Learning, Statistics, SQL, Big Data tools, and advanced data visualization. Learners also get exposure to real-world projects and tools used by top companies, giving them a competitive edge in the job market.

Whether you’re a beginner or an engineering graduate aiming to upskill, our Data Science and Analytics courses in Jaipur are structured to meet different learning needs. We go beyond theory by focusing on case studies, real datasets, and cloud-based labs.

What truly sets us apart is our best Data Science courses with placement guarantee. With 100% placement support, resume building, and mock interviews, we ensure every learner walks out industry-ready. We also offer flexible learning options through our Data Engineering online courses with placement, allowing you to learn from anywhere while still receiving expert guidance and career support.

August Batches Dates

Batch 1: 04^th August 2025Batch 2: 11^th August 2025Batch 3: 18^th August 2025Batch 4: 25^th August 2025

September Batches Dates

Batch 1: 01^st September 2025Batch 2: 08^th September 2025Batch 3: 15^th September 2025Batch 4: 22^nd September 2025Batch 5: 29^th September 2025

October Batches Dates

Batch 1: 06^th October 2025Batch 2: 13^th October 2025Batch 4: 27^th October 2025

Weekly Duration

20 Hours Per week

Location

Physical (Jaipur)or Online (Google Meet)

Duration

10 Months + 6 Months Additional Support

Participants

18 – 20 per Batch

What you will Learn

Study Material

E-Notes
Assignments & Poll test
Live Video Lectures
Access of Recordings & Study Material
Mentorship Support
Work on multiple Minor Projects & Use Cases
Work on Live Projects

Output

Able to think out of the box
Become expert in multiple technology domains like: Python, Machine Learning, Deep Learning, Map Reduce, Apache Spark, Generative Ai, Agentic AI, Kafka, and AWS(for deployment)
Understand working of ML models deployment with AWS
Build projects on multiple technology domains
Work on more than 25 Use CASES & Projects
Learn to deploy your models on AWS Sagemaker or Google cloud Platform

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.

Placement Opportunities in Companies

You can get Internship/Training Opportunities to get placed in HP, DELL, Honeywell, Rightpoint, Frontdoor, Fractal and many more according to your performance.

Pacakage Offered So Far

IT Candidates

4 LPA

4 – 6 LPA

39 LPA

Non-IT Candidates

3 LPA

3.5 – 5 LPA

14.5 LPA

Placement Process

At REGex Software, we are committed to providing a structured and results-driven training approach to ensure your career success.
- 🔹 Training & Performance Analysis:
  - Your training will begin from day 1 of your joining, focusing on hands-on learning and practical implementation.
  - Our team will analyze your performance based on assignments, projects and weekly assessments from the second week onwards and we will provide weekly feedback to help you improve.
  🔹 Mandatory Criteria for Placement Opportunities:
  To be eligible for placement opportunities, you must meet the following criteria:
  ✅ 80% attendance in live training sessions.
  ✅ 80% completion and timely submission of assignments & projects.
  ✅ 80% attendance in assessments, including tests, mock interviews, HR interviews and group discussions.
  🔹 Resume Preparation & Placement Process:
  - Between 6.5 to 7 months, our team will provide guidance on resume building and evaluate your resumes accordingly.
  - After completing 75-80% of the program, you will receive details about the placement opportunities based on your performance and company requirements.
  - Placement opportunities will be provided continuously via email, calls and WhatsApp groups, depending on your performance.
  🔹 Placement Assurance & Refund Policy (Applicable only for Indian Students Only):
  - This is a Placement Assured Program, with an additional 6-month post-program assistance.
  - IT Graduates who passed out in 2025 or later (Regular B.tech, BCA, M.tech, MCA programs) are assured a minimum salary package of 4LPA upon placement. However, for IT Graduates who passed out in 2024 or earlier, having gaps in their academics, as well as for Non-IT Graduates (graduates other than regular B.tech, BCA, M.tech, MCA programs), the minimum guaranteed package will be 3LPA.
  - In the event that you have attended & completed at least 80% of the program, submitted and finished at least 80% of the assignments, Tests, Mock Interviews & HR Interview and still do not secure a placement then REGEX will refund your fees with a 9% Annual interest rate. Furthermore, Refunds are applicable only within the first 3 days of the demo period and solely in cases where a specific concern is raised regarding the quality of the learning experience provided. You will receive an official notification email from our team on the third day at 7:30 PM, confirming the completion of your demo period. Requests for a refund of the registration amount must be submitted prior to the issuance of this email. No refund requests will be entertained after this time and Even if you discontinue the program prematurely, you are still obligated to pay the full fee to REGex.
  🔹 Our Commitment to Your Success:
  At REGex Software, Placement Assurance = Skills + Opportunities.
  We equip you with industry-relevant skills and provide continuous job opportunities based on your performance. However, it is the student’s responsibility to crack interviews and enhance their skills based on feedback.
  For additional support, we offer the flexibility to rejoin previous batches to reinforce concepts and improve understanding.We are dedicated to your career success! 🚀

Placed Students//Partnership

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

Purnima ponrajkumar Indium software — Purnima ponrajkumar
Indium software

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

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

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

Muskan Hewlett-Packard — Muskan
Hewlett-Packard

Praveen Jangid Celebal Tech — Praveen Jangid
Celebal Tech

Python

Introduction to Python

What is Python?
History and evolution of Python.
Python’s popularity and use cases.
Setting up Python (installation).
Running Python scripts and using the interactive shell.

Operators in python

Arithmetic Operators(+,-,*,/,//,%,**)
Comparison / Relational Operators (== ,!=)
Assignment Operators
Logical Operators
Bitwise Operators
Identity Operators

Control Flow Structures

Conditional statements (if, elif, else).
Looping structures (for and while loops).
Iterating through sequences (lists, strings, dictionaries).
Range and enumeration.
Using break and continue.

Sequence Data Types

Lists: creation, manipulation, and methods.
Tuples: creation, immutability, and uses.
Dictionaries: key-value pairs and operations.
Sets: unique elements and set operations.
List comprehensions.

Problem Solving on LeetCode

Problem Solving on LeetCode question

Walkthrough on Function

Python Modules & Packages

What is a Module?
Types of Modules
Why Use Modules?
Importing Modules
What is a Package?
Why Use Packages?
Namespace Management
Popular Python Packages (numpy, pandas, flask, django, requests, matplotlib, etc.)

File Handling / Exception Handling

Reading from and writing to files.
Working with different file modes (read, write, append).
Using context managers with files.
Handling errors with try and except.
Raising exceptions.
Handling multiple exceptions.
Using the ‘finally’ block.

Object-Oriented Programming (OOP)

Classes and objects.
Attributes and methods.
Inheritance and encapsulation.
Polymorphism and method overriding.
Constructors and destructors.

Advanced Python

NumPy basics & array manipulations
Pandas Series, DataFrames, indexing, merging,
– Grouping
Matplotlib & Seaborn (basic plots, customization)

Python in the Real World

Real-world case studies.
Job opportunities and career paths.
Contributing to open-source projects.
Staying up to date with Python developments.

Machine Learning

Introduction

Machine learning applications
ML vs DL

Data Cleaning & Munging with – Python

Basics of Python [Syntax]
Working with Pandas, Numpy & Matplotlib
■ Working with Missing Data
■ Data Grouping
■ Data Subsetting
■ Merging & Joining Data Frames
Importing Libraries & Datasets
Munging & handling missing data
Splitting the dataset into Training set & Test set

Understanding all concepts of ML

What is actual machine learning
Various Aspects of Data – type, Variables & Category
Machine Learning & its Various types

Supervised & Unsupervised Learning

About Supervised & Unsupervised Learning

Simple Linear Regression

Understanding Simple Linear Regression

Multiple Linear Regression Intuition

Understanding the P -Value

What is Regression with its use cases

Support Vector Regression

Classification

Evaluating Classification Models Performance

Confusion matrix
Accuracy Paradox
CAP Curve

K-Mean Clustering

K-Mean Clustering Intuition
K-Mean selecting Numbers of Cluster

Deep Learning

NLP

NLP Intuition
Types of NLP
Classification vs Deep Learning Models

Understanding about Deep Learning

The Neuron
Activation function
How Neural network work & learn by itself
Gradient Descent
Stochastic Gradient Descent
Ethics of Deep Learning

Deep Dive with ANN

What are convolutional neural networks [CNN] ?
CNN Architecture
CNN Code preparation
Recurrent Neural Networks
Several layers
■ ReLLu Operation
■ Pooling
■ Flattering
■ Full Connection

Mathematics Operations

Detailed Statistics

Descriptive Statistics
Types of Data
Qualitative Data
Histograms
Different Plots

More Mathematics Concepts

Centrality and Spread
Outliers
Median, Mean, Mode

Advance NLP

What are Vectors
Working with word Analogy
Text Classification
Pre Trained word vectors from word2vec
Language Models

TensorFlow / Keras

Introduction to Tensorflow / Keras
Most used right now
Resources gathering
Keras dealing with Missing Data
Dealing with Categorical data

Generative AI

Generative AI Introduction

Introduction to Generative AI
Applications of GenAI:(Text generation, Image generation,Code generation)
Evolution of GenAI(From GANs to Transformers and beyond)

RAG

Introduction to RAG,Retriever,Generator
RAG ARCHITECTURE(Input query processing,Retrieval phase,Fusion of retrieved information with the LLM,Response generation)
Types of RAG models(RAG-Sequence,RAG-Token)
Project(Customer support bots with real-time information retrieval)

Vector DataBase

Introduction to Vector Databases , Key concepts(Vectors and embeddings,High-dimensional space representation)
Core Concepts(Indexing and searching vectors,Scalability challenges,Vector quantization techniques)
Popular Vector Databases(FAISS (Facebook AI Similarity Search),Milvus,Weaviate)

Transformers

Transformer architecture:(Encoder and Decoder blocks, Multi-Head Attention,Scaled Dot-Product Attention,Positional Encoding)

Google Gemini for LLMs

Gemini architecture and its key features , Differences between Gemini and other LLMs (e.g., GPT, BERT)
Use cases of Gemini(Multimodal AI (text, images, audio),Content creation, Code generation and debugging)
APIs and Tools for Gemini:(Accessing the Gemini API, Authentication and integration)
Project (Create Chabot and Deploy it on Streamlit Cloud)
Agentic AI Using LangChain and LangGraph project(Business Start up Idea using current businesses in India )

Database

SQL / NoSQL

Defining Database
Type of databases
Functional Dependency
Closure of Attributes
Types of Keys: PrimaryKey CandidateKey & Super Key in DBMS
Normalization
Indexing
Transaction and Concurrency Control
Transaction in DBMS
ACID Propertise in DBMS
Joins in DBMS
Create & Alter Table
Constraints in SQL
Sql Queries & Sub Queries
SQL Stored Procedure
View, Cursor & Trigger in SQL
Common Table Expession
Replace Null and Coalesce Function
Running Total In SQL
Subquery
Joins
Analytical functions
Introduction to Indexes]
Views in SQL
PL/SQL

Power BI

Introducing Microsoft Power BI

Introduction
Meet Microsoft Power BI Desktop
Interface & Workflow
Helpful Power BI Resources
New Power BI Ribbon

Connecting & Shaping Data with Power BI Desktop

- Introduction
- Types of Data Connectors in Power BI Desktop
- The Power BI Query Editor
- Demo: Basic Table Transformations in Power BI
- Power BI Demo:

Working with Text Tools

Numerical Values

Date & Time Tools

Creating a Rolling Calendar

Grouping & Aggregating Records

Pivoting & Unpivoting Data

- Merging Queries in Power BI Desktop
- Appending Queries in Power BI Desktop
- Configuring Power BI Data Source Settings
- Configuring Power BI Query Refresh Settings
- Additional Data Types & Categories in Power BI
- Defining Hierarchies in Power BI Desktop

Importing Models from Excel to Power BI

Creating Table Relationship & Data Models

- Introduction
- What is a “Data Model”?
- Principles of Database Normalization
- Understanding Data Tables vs. Lookup Tables
- Understanding Table Relationships vs. Merged Tables
- Creating Table Relationships in Power BI Desktop

Snowflake Schemas in Power BI

Managing & Editing Table Relationships in Power BI Desktop
Managing Active vs. Inactive Relationships
Understanding Relationship Cardinality
Connecting Multiple Data Tables in Power BI Desktop
Understanding Filter Flow
Two-Way Filters in Power BI Desktop (USE WITH CAUTION!)
Hiding Fields from the Power BI Report View
New Power BI Desktop “Model” View

Analyzing Data with DAX Calculations in Power BI

Introduction
Meet Data Analysis Expressions (DAX)
Intro to DAX Calculated Columns
Intro to DAX Measures
Adding Columns & DAX Measures in Power BI Desktop
Implicit vs. Explicit DAX Measures
Filter Context Examples in Power BI
Understanding DAX Syntax & Operators
Common DAX Function Categories
DAX Demo:
- Basic Date & Time Functions
- Conditional & Logical Functions (IF/AND/OR)
- Common Text Functions
- Joining Data with RELATED
- Basic Math & Stats Functions
- COUNT Functions (COUNTA, DISTINCTCOUNT, COUNTROWS)
- CALCULATE
- CALCULATE & ALL
- CALCULATE & FILTER
- Iterator Functions (SUMX, RANKX)
- Time Intelligence Formulas

Functions

Visualizing Data with Power BI Reports

- Introduction
- Exploring the “Report” View in Power BI Desktop
- Adding Simple Objects to the Power BI Report Canvas
- Inserting Basic Charts & Visuals in Power BI
- Conditional Formatting
- Power BI Report Formatting Options
- Power BI Report Filtering Options
- Power BI Demo:
  - Exploring Data with Matrix Visuals
  - Filtering with Date Slicers

Showing Key metrics with Cards & KPI Visuals

- Inserting Text Cards
- Visualizing Geospatial Data with Maps
- Visualizing Data with Treemaps
- Showing Trends with Line & Area Charts
- Adding Trend Lines & Forecasts
- Goal pacing with Gauge Chart
- Adding Drillthrough Filters
Editing Power BI Report Interactions
Managing & Viewing Roles in Power BI Desktop

Visualizing Data with Power BI Reports

- Introduction
- Exploring the “Report” View in Power BI Desktop
- Adding Simple Objects to the Power BI Report Canvas
- Inserting Basic Charts & Visuals in Power BI
- Conditional Formatting
- Power BI Report Formatting Options
- Power BI Report Filtering Options
- Power BI Demo:
  - Exploring Data with Matrix Visuals
  - Filtering with Date Slicers

Showing Key metrics with Cards & KPI Visuals

- Inserting Text Cards
- Visualizing Geospatial Data with Maps
- Visualizing Data with Treemaps
- Showing Trends with Line & Area Charts
- Adding Trend Lines & Forecasts
- Goal pacing with Gauge Chart
- Adding Drillthrough Filters
Editing Power BI Report Interactions
Managing & Viewing Roles in Power BI Desktop

Big Data

Introduction to Big Data

BigData Overview

Map-Reduce Architecture

What is distributed computing
Introduction to Map Reduce
Map Reduce components
How MapReduce works
Word Count execution
Suitable & unsuitable use cases for MapReduce
HDFS vs Map-Reduce
MV1 vs MV2
Wordcount problem

Apache Spark - New generation DE tool

● What is Spark? ● History of Spark ● Spark Architecture ● Spark Shell Working with RDDs in Spark ● RDD Basics ● Creating RDDs in Spark ● RDD Operations ● Passing Functions to Spark ● Transformations and Actions in Spark ● Spark RDD Persistence Working with Key/Value Pairs ● Pair RDDs ● Transformations on Pair RDDs ● Actions Available on Pair RDDs ● Data Partitioning (Advanced) ● Loading and Saving the Data Spark Advanced ● Accumulators ● Broadcast Variables ● Piping to External Programs ● Numeric RDD Operations ● Spark Runtime Architecture ● Deploying Applications

Data lake vs Delta Lake vs Data Warehouse

Spark SQL Introduction
Spark SQL Overview
Spark SQL Architecture
What is Spark streaming?
Spark Streaming example

ETL pipeline using DataFrames

Data cleaning & transformation
Writing optimized queries
Creating and using UDFs
Performance implications
Serialization issues

Introduction to Structured Streaming & Kafka

Performance Tuning & Debugging

Job & Stage Analysis
Spark UI
Caching vs Persistence
Tuning joins, memory, partitions
End-to-end ETL on large dataset

Writing to Data Sinks from Spark Streaming

Sink Targets: Delta Tables, Parquet, PostgreSQL, S3
Streaming Aggregations

Airflow - The Workflow Orchestration

What is Workflow Orchestration?
Why Apache Airflow?
Use-cases: Data Pipelines, ML Pipelines, ELT
Airflow vs other tools
DAGs, Tasks, Operators
Scheduler, Webserver, Worker
Installation & Setup (Local and Cloud)
Install using pip/docker-compose
Set up Airflow UI
Airflow home & config

AWS (Deployment)

AWS Sagemaker

Create your own ML models
Deploy ML models
AWS Recognition

Capstone Projects & Use Cases

ML & DL Projects
- Titanic Classification
- Carbon Emissions
- Car price analysis
- Drug Prediction
- Hand written Digit Recognition
- CIFAR 10
- CIFAR 100
- Cats vs dogs
- Intel scene Classification
- Transfer Learning
- Object Detection
Power BI Projects & Use Cases
- Importing Models from Excel to Power BI
- Snowflake Schemas in Power BI
- Showing Key metrics with Cards & KPI Visuals
BigData Projects
- Zomato Analysis
- Cricket & Football Data Analysis
- Flipkart Product Data Analytics

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

Extra Sessions

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

Fee Structure

Indian Fee (Physical)

Price: ₹60,000/-

Indian Fee (Online)

Price: ₹60,000/-

International Fee

Price: $1500

Fee can be paid as No Cost EMI @5000/month

Cashback Policy

You will get your Unique Referral Code after successful paid registration.
You will get ₹2500 Cashback directly in your account for each paid registration from your Unique Referral Code on monthly basis(After Closing Registrations of this program) .
For Example:- If we received 10 paid registration from your Unique Referral Code then you will receive ₹2500*10 = ₹25,000 on monthly basis.

For Frequent Course Updates and Information, Join our Telegram Group

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(Batches Start from August, September & October 2025)

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College/University/Organization *

City *

State *

Country *

Qualification *

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Which program you want to join? *

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*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*

Website

Data Science and Analytics specialization course in Jaipur

About The Program

August Batches Dates

September Batches Dates

October Batches Dates

Weekly Duration

Location

Duration

Participants

What you will Learn

Python

Machine Learning

Deep Learning

Generative Ai

Agentic Ai

Airflow

HDFS

Hadoop

Kafka

Data Warehousing

ETL

Databricks

Snoflake

Map-Reduce

Power BI

Apache Spark

AWS

Study Material

Output

Why Choose Us

Live Sessions

Live Projects

24*7 Support

Opportunities

Placement Opportunities in Companies

Pacakage Offered So Far

IT Candidates

Non-IT Candidates

Placement Process

Placed Students//Partnership

What People Tell About Us

Drishti Khandelwal Ex-Student, Django Batch

Gulshan S Arya Ex-Student, Mearn Stack

Mohit Sharma Ex-Student, python django

Yaman Singh Ex-Student, CP Batch

Josh Well Ex-Student, BigData Batch

Salman Khan Ex-Student, Django Batch

Jack Ryan Ex-Student, CP Batch

Placed Students

Course Content

Python

Machine Learning

Deep Learning

Generative AI

Database

Power BI

Big Data

AWS (Deployment)

Extra Sessions

Fee Structure

Indian Fee (Physical)

Indian Fee (Online)

International Fee

Cashback Policy

Enroll Now

(Batches Start from August, September & October 2025)

Quick Links

What We Offer

Software Services

Address

B-35, 2nd floor next to vasantbahar colony, Gopalpura bypass, Jaipur

+91-9602880219, +91-7852071653

info@regexsoftware.com

+91-9602880219,
+91-7852071653