Datascience Specialization Program

(Batches Start from 24th December 2021, 7th & 13th January 2022)

About The Program:

With the belief to build a healthy ecosystem as per the Industry Standards REGex Software brings an Industrial Training/Internship Program on “Datascience Specialization”. We organize Datascience Specialization Program for improving the knowledge and skills of the Students/Professionals, so that they can become specialized in the field of Datascience and get their Dream Job in Software Development Field in Big MNCs.

REGex Software Services’s “DataScience Specialization” program is a valuable resource for beginners and experts. This program will introduce you to Machine Learning, Deep Learning, Docker, Kubernetes, Hadoop, Spark, Map Reduce, Ansible, Power BI etc. from Basics to Advance. If you want to become Data Scientist, REGex introduce this program for you.

Timing

06:30 PM – 08:30 PM (IST)
or
09:00 PM – 11:00 PM (IST)

Platform

Google Meet

Duration

24 – 26 Weeks

Participants

50 per Batch

Pause Your Program

You can pause your program if you have any Medical Emergency or if you have Exams and join again our new program within next 3 Months

What People Tell About Us

What you will Learn

Python

Duration: 40 Hours

Machine Learning

Duration: 40 Hours

Deep Learning

Duration: 40 Hours

SQL

Duration: 10 Hours

Power BI

Duration: 30 Hours

Hadoop

Duration: 25 Hours

Apache Spark

Duration: 20 Hours

Ansible

Duration: 10 Hours

Docker

Duration: 10 Hours

Kubernetes

Duration: 10 Hours

Django Full Stack

Duration: 60 Hours

AWS

Duration: 5 Hours - For Deployment

Study Material

  • E-Notes
  • Assignments & Poll test
  • 300+ hours on demand 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, Hadoop, Map Reduce, Apache Spark, Ansible, Docker, Kubernetes 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

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

Package Offered So Far

Minimum Package

4.4 LPA

Average Package

6.2 LPA

Highest Package

32 LPA

Placement Process

  • We’ll train you from first week and TEAM will analyze your performance according to your Assignments & projects.

  • You will work on different projects with your team with Mentorship Support.

  • After Completion of 3.5th – 4th month, TEAM will guide you about resume making and Team will take your resumes and analyze it accordingly.

  • After this process you will get direct calls and in house placement calls directly or for the further process of exam after looking minimum Qualification of particular company.

  • You will get Opportunities back to back from REGex End via a mail according to your performance.

Our Students Placed In

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Course Content

Machine Learning

  • Machine learning applications
  • ML vs DL
  • 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
  • What is actual machine learning
  • Various Aspects of Data – type, Variables & Category
  • Machine Learning & its Various types
  • About Supervised & Unsupervised Learning
  • Understanding Simple Linear Regression
  • Understanding the P -Value
  • Support Vector Regression
  • K nearest neighbours
  • Logistic regression
  • Naive Bayes
  • Decision trees
  • Random forests
  • Bagging Boosting
  • Maximum likelihood classifier
  • Support vector machines
  • Principal Component analysis (PCA – Theory)

  • PCA with Case-Study

  • Linear Discriminant Analysis(LDA) for Dimension Reduction

  • Feature Selection to Select the Most Relevant Predictors

  • Confusion matrix

  • Accuracy Paradox

  • CAP Curve

  • K-Mean Clustering Intuition

  • K-Mean selecting Numbers of Cluster

  • About Reinforcement Learning

Deep Learning

  • NLP Intuition

  • Types of NLP

  • Classification vs Deep Learning Models

  • The Neuron

  • Activation function

  • How Neural network work & learn by itself

  • Gradient Descent

  • Stochastic Gradient Descent

  • Ethics of Deep Learning

  • What are convolutional neural networks [CNN] ?

  • CNN Architecture

  • CNN Code preparation

  • Recurrent Neural Networks

  • Several layers

    ■ ReLLu Operation

    ■ Pooling

    ■ Flattering

    ■ Full Connection

  • Statistics

  • Sample Selection

  • Probability Theory

  • Hypothesis

  • Model Relationship

  • Model Fit

  • Descriptive Statistics

  • Types of Data

  • Qualitative Data

  • Histograms

  • Different Plots

  • Centrality and Spread

  • Outliers

  • Median, Mean, Mode

Computer Vision

  • What is computer vision & its application

  • Face Detection

    ■ Adding more features & Categorization

    ■ Object Detection & Image creation

    ■ Working with Images & vectors

  • Facial Expression Recognition in Code (Binary / Sigmoid /Logistic Regression)

  • Object detection

  • Neural style transfer

  • YOLO

  • RCNNs

  • Resnet 50

  • Tensorboard

  • What are Vectors

  • Working with word Analogy

  • Text Classification

  • Pre Trained word vectors from word2vec

  • Language Models

  • Introduction to Tensorflow / Keras

  • Most used right now

  • Resources gathering

  • Keras dealing with Missing Data

  • Dealing with Categorical data

Database

  • 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
  • MongoDB – Overview
  • CRUD Operations
  • Basic Operations
  • Aggregations
  • Indexing
  • Replication and Sharding

Power BI

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

 

 

    • 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
  • 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
  • FILTER Function
  • LOGICAL Functions
  • MATHEMATICAL Functions
  • STATISTICAL Functions
  • TEXT Functions
  • TIME INTELLEGENT Functions
  • Other Functions
  • Power Query Editor
  • Power BI Aggregation & Template
    • 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 Tools

● 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

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

● Spark SQL Overview
● Spark SQL Architecture

● What is Spark streaming?
● Spark Streaming example

● What are dataframe
● Manipulating Dataframes
● Reading new data from different file format
● Group By & Aggregations functions

● 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

Talend Data Integration

● Installation and Configuration
● Repository
● Projects
● Metadata Connection
● Context Parameters
● Jobs / Joblets
● Components
● Important components
● Aggregation & working with Input & output data

DevOps

  • Configuration Management (Ansible)
    • What & Why ?
    • Ad-hoc Commands
    • Playbooks
    • Facts
    • Handlers
  • Introduction
  • Docker Basics
  • Networking
  • Storage
  • Dockerfile
  • Managing Containers
  • Docker Compose
  • Introduction to Docker Swarm
  • Security
  • Introduction
  • Basic Concepts
  • Pods
  • Replication controller and Replica-Sets
  • Deployment
  • Services
  • Kubernetes in cloud
  • Networking
  • Storage
  • Scaling
  • Authentication

Frontend Technologies

● HTML Level One Introduction
● HTML Part One Basics
● Basic Tagging
● Paragraph, Styles, Formating, Quotation, Lists
● Color, Links, Images Divs and Spans
● Blocks & Inline, Ids, Classes, Attributes
● Tables, IFrames
● Forms Basics, Input types and Attributes
● Form Elements and Labels
● Forms and Selections
● Some Advanced Topics

● Introduction
● Color, Background, Padding
● Border, Margin, Box, Model
● Outline, Text, Icons
● Position, Float, Opacity
● Creating Navigation
● Creating Dropdown
● CSS Forms, Counters
● Website Layout
● Some Advanced Topics

● Bootstrap Introduction
● Colors, Buttons, Table, Jumbotron, Containers
● Alert, Badges, Spinner, Lockdown
● Input Groups, Nav Bar, Dropdown
● Grid System
● Some Advanced Topics

● Introduction
● Basics, Connecting Javascript
● Data Type, Solutions, Operators, Control Flow
● Conditions, Boolean, Comparison
● While Loops, For Loops

Django Framework

● Django Installation and Configuration
● MVC Applied to Django and Git
● Basic Views, Django Command Overview

• First View: Dynamic Content
• Mapping URLs to Views
• Processing a Request
• URL configurations and Loose Coupling
• 404 Errors
• Second View: Dynamic URLs
• A Word About Pretty URLs
• Wildcard URL patterns
• Django’s Pretty Error Pages

• Template System Introduction
• Creating & Rendering Template Objects
• Multiple Contexts, Same Template
• Basic Template Tags and Filters Tags
• Using Templates in Views
• Template Loading
 get_template()
• The include Template, Template Inheritance Tag

• Defining Models in Python
• Installing the Model
• Basic Data Access
• Adding Model String Representations
• Inserting, Filtering & Updating Data
• Selecting Objects
• Retrieving Single Objects
• Ordering & Slicing Data
• Deleting Objects
• Making Changes to a Database Schema
• Adding Fields
• Removing Fields
• Removing Many to Many Fields
• Removing Models

  • Introduction to Admin
    • Admin Templates
    • Ordering Fields
    • Adding Search
    • Adding Filters
    • Adding Fields
    • Editable List View
  • Creating a User Authentication
    • Setting Up A Simple User Authentication System
    • Login and Session Variables
    • Cookies
    • Permissions
    • Social Registration
    • Form Validation
  • Frontend
    • URL Template Inheritance
    • Template Filters and Custom Filters
    • Template Language and Static Files
    • Twitter Bootstrap Integration
    • Static File Compression and Template Refactoring
  • Upload Image
    • Add Pillow requiremen
    • Modify recipe model
    • Add tests for uploading image to recipe
    • Add feature to upload image
  • Preparing The Storefront
    • Product Display
  • Adding a Shopping Cart
    • Images
    • Dynamic Content/Page Creation
  • Payment Gateway
    • PayPal Integration / Paytm / Google Pay / PhonePe

• Search
• Creating a Feedback Form
• Processing the Submission
• Custom Validation Rules
• A Custom Look 
• Creating Forms from Models

• URL configuration Tricks
• Streamlining Function Imports
• Using Multiple View Prefixes
• Special-Casing URLs in Debug Mode
• Using Named Groups
• Understanding the Matching/Grouping Algorithm
• Passing Extra Options to View Functions
• Using Default View Arguments
• Special-Casing Views
• Capturing Text in URLs
• Including Other URL configurations
• Captured Parameters Working with include()
• Extra URL configurations Options Working with include()

• Using Generic Views
• Generic Views of Objects
• Extending Generic Views
• Making “Friendly” Template Contexts
• Adding Extra Context
• Viewing Subsets of Objects
• Complex Filtering with Wrapper Functions
• Performing Extra Work

● Serializers, views and URL
● Creating API and Web ServiceS
● Working on POSTMAN
● GET
● POST
● PUT
● DELETE
● PATCH
● Testing our API

AWS (For Deployment)

  • Create your own ML models
  • Deploy ML models
  • AWS Recognition
  • 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

Extra Sessions

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

Fee Structure

Indian Fee

Price: ₹29999/- (Flat 75% off) => ₹7499/- 

International Fee

Price: $1000 (Flat 75% off) => $250 
Fee can be paid in 2 installments of 4.5k + 3.5k

Goodies

You will get Goodies like: REGex T-shirt, REGex Stickers, REGex Key Chain, REGex Cap, REGex Bag etc. after successfully enrollment in this program

Cashback Policy

  • You will get your Unique Referral Code after successful paid registration.
  • You will get ₹750 Cashback directly in your account for each paid registration from your Unique Referral Code on 15th February, 2022(After Closing Registrations of this program) .
  • For Example:- If we received 10 paid registration from your Unique Referral Code then you will receive ₹750*10 = ₹7500 on 15th February, 2022.
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Enroll Now

(Batches Start from 24th December 2021, 7th & 13th January 2022)

*It will help us to reach more
*Seats can be filled or Price can be increased at any time. Refund policy is not available*
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course (at checkout).
4.2 Payments
You agree to pay the fees for the Services that you purchase. To achieve this, you agree to share
with us/ our authorized payments partners with your personal and financial information that may
be necessary, and authorize us to charge your debit or credit card or process other means of
payment (such as direct debit, or mobile wallet) for such fees.
You agree that you are authorized to use the payment instrument or payment method by which
you make any payment to us, and that such payment method has been duly and validly issued.
We may continue to provide you access to a Course or any other Services, even if your payment
to us fails, subject to you making the payment within the time period prescribed by us. We
reserve the right to disable access to any Service for which we have not received adequate
payments.
We may also issue you credits for high performance, your participation in contests, referral
programs, events, or other activities on the Platforms. You may use such ‘credits’ towards
paying for a Service on the Platform. We would request you to refer to the Credits Policy to
know more about the term, duration, and nature of such Credits.
PLEASE NOTE THAT ANY CREDITS ISSUED BY US ARE NOT REDEEMABLE FOR
CASH AND CANNOT BE TRANSFERRED TO ANY THIRD PARTY AS PAYMENT FOR
ANY GOOD OR SERVICE.
4.3 Refunds
REGex will not provide any type for any Course. If you want to claim a refund, please do so by:
a. Drop an email on: contact@regexsoftware.com in case you have any trouble with the
instructor.
Please do not forget to provide the registered email ID in the subject
b. Please ensure that the email is received within one day of the batch start date.
For example: If a batch starts on 15 July 2019, you should send the refund email on or
before 12:00 am, 16 July 2019.
c. The refund process is not applicable on any standalone courses, combo courses, and
career track courses. The refund will not be processed for individual modules of combo
course or career track course

5. REGex Software’ RIGHTS TO CONTENT YOU POST

You retain ownership of content you post to our Platform, including your feedback, messages,
notes, text, documents, presentations, , and other content that you upload, publish or display.
We’re allowed to share your content to anyone through any media, including promoting it via
advertising on other websites. You agree that you own the rights to any content shared on the
Platform.
We may, at our discretion, delete or remove (without notice) any user content in its sole
discretion, for any reason or no reason, including without limitation user content that in the sole
judgment of the Company violates these Terms.
By signing up to our website or through any physical medium, you will provide your details with
a consent that REGex Software can use your contact details for their marketing & promotional
activities to reach out to the candidates through any third part application or user.
The user or person or you will automatically give consent that:
““I agree to receive promotional and marketing material’’
You also hereby grant each user of the Platform (subject to such limitations, if any, that may
apply with respect to Private Content) a non-exclusive license to access your content through the
Platform, and to use, reproduce, distribute, prepare derivative works of, and display such content
as permitted through the functionality of the Platform and under these Terms.

6. USING PLATFORM AT YOUR OWN RISK

We do not provide any warranty or guarantee relating to any of our Services, and they are
provided on an ‘as-is’ basis. You agree to use the Platform and avail any Service at your own
risk.
We request you to be careful and prudent in your interactions with Instructors, or support
officers. Please do not share any information, including personal details such as where you live,
your financial information or other details. We are not liable for disputes, claims, losses, injuries,
or damage of any kind that might arise out of or relate to the conduct of instructors or students.
When you use our Services, you will find links to other websites that we don’t own or control,
such as payment service providers, advertisers, recruitment platforms. We are not responsible for
availability, reliability, accuracy of any third party services. We strongly recommend that you
read the applicable terms and conditions for their use prior to accessing them.

7. OUR ROLE

We are not a University, Institute or any form of a registered or accredited institution. We
provide access to online training software and content. We do not recommend use of the REGex
Software platform in substitution of an educational institution such as a school college or
university.
We may provide you with rewards, credentials or acknowledgements based on your completion
of a Course, or performance while availing a Service. Any such recognition is given by REGex
Software at its discretion. Such recognitions are provided by an educational institution and nor
are they equivalent to an award, degree, certificate or other recognitions provided by an
educational institution.
We do not provide any guarantee admission in any educational institution or procurement of a
job, or any other remunerative opportunity by accessing the Platform and availing the Services.
We partner with educational institutes from time to time, to provide you access to educational
programs, and Courses. These educational institutes may provide you with, through our platform,
degrees, certificates upon fulfilling the criteria notified in the Courses. Enrolment in a Course or
a Service provided in partnership with such educational partner does not grant you the right to
any other association with such education partner (other than as specifically provided on the
Platform).

8. TERMINATION, SUSPENSION

We may terminate your membership, delete your Account and any content or information that
you have posted on the Site and/or prohibit you from using or accessing the Service or the Site
(or any portion, aspect or feature of the Service or the Site) at our discretion, including if we
identify any potential violation of these Term.
All terminations shall be made in our sole discretion and that we shall not be liable to you nor
any third-party for any termination of your Account or access to our Service.

8. MISCELLANEOUS TERMS

8.1 REGex Software Communications
You agree to receive communications from the Company if you as a user have created an
account or have signed up or have shown interest for any course in connection with your
use of Services in the form of email or SMS messages, including without limitation account
activity notification, service updates, and reminders.
8.1 Member Disputes
You are solely responsible for your interactions with other Members. REGex Software reserves
the right, but has no obligation to monitor disputes between you and other Members.
8.2 Privacy
Use of the Services is also governed by our Privacy Policy, which is incorporated into this
Agreement by this reference. By accepting this Agreement, you agree to indemnify and
otherwise hold harmless the Company, its officers, employees, agents, subsidiaries, affiliates
and other partners from any direct, indirect, incidental, special, consequential or exemplary
damages resulting from your use of the Service, unauthorized access to or alteration of your
communications with or through the Service, or any other matter relating to the Service.
Any business transactions which may arise between users from their use of the Platform are
the sole responsibility of the users involved. Without limitation of the terms set forth in our
Privacy Policy, you understand and agree that the Company may disclose personally
identifiable information if required to do so by law or in the good faith belief that such
disclosure is reasonably necessary to comply with legal process, enforce this Agreement, or
protect the rights, property, or safety of the Company, its users, and the public.
8.3 Disclaimer of Warranties
YOU UNDERSTAND AND AGREE THAT THE SERVICE IS PROVIDED ON AN (AS IS)
AND (AS AVAILABLE) BASIS AND THAT THE COMPANY DOES NOT ASSUME ANY
RESPONSIBILITY FOR PROMPT OR PROPER DELIVERY, OR RETENTION OF ANY
USER INFORMATION OR COMMUNICATIONS BETWEEN USERS. THE COMPANY
ASSUMES NO RESPONSIBILITY FOR THE ACCURACY OR EXISTENCE OF ANY
COMMUNICATIONS BETWEEN USERS. THE COMPANY EXPRESSLY DISCLAIMS
ALL WARRANTIES OF ANY KIND, WHETHER EXPRESSED OR IMPLIED,
INCLUDING, BUT NOT LIMITED TO THE IMPLIED WARRANTIES OF
MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. THE COMPANY MAKES NO WARRANTY THAT THE SERVICE
WILL MEET YOUR REQUIREMENTS THAT THE SERVICE WILL BE
UNINTERRUPTED, TIMELY, SECURE, OR ERROR-FREE AND THAT THE RESULTS
THAT MAY BE OBTAINED FROM USE OF THE SERVICE WILL BE ACCURATE OR
RELIABLE THE QUALITY OF ANY PRODUCTS, SERVICES, INFORMATION, OR
OTHER MATERIAL PURCHASED OR OBTAINED BY YOU THROUGH THE SERVICE
WILL MEET YOUR EXPECTATIONS OR ANY ERRORS IN THE SOFTWARE WILL BE
CORRECTED. ANY MATERIAL DOWNLOADED OR OTHERWISE OBTAINED
THROUGH THE USE OF THE SERVICE IS DONE AT YOUR OWN DISCRETION AND
RISK AND THAT YOU WILL BE SOLELY RESPONSIBLE FOR ANY DAMAGE TO
YOUR COMPUTER SYSTEM OR LOSS OF DATA THAT RESULTS FROM THE
DOWNLOAD OF ANY SUCH MATERIAL. NO ADVICE OR INFORMATION, WHETHER
ORAL OR WRITTEN, OBTAINED BY YOU FROM THE COMPANY OR THROUGH OR
FROM THE SERVICE SHALL CREATE ANY WARRANTY NOT EXPRESSLY STATED
IN THIS AGREEMENT. SOME JURISDICTIONS DO NOT ALLOW THE EXCLUSION OF
CERTAIN WARRANTIES OR THE LIMITATION OR EXCLUSION OF LIABILITY FOR
INCIDENTAL OR CONSEQUENTIAL DAMAGES. ACCORDINGLY, SOME OF THE
ABOVE LIMITATIONS MAY NOT APPLY TO YOU.
8.4 Limitation of Liability
YOU EXPRESSLY UNDERSTAND AND AGREE THAT THE COMPANY SHALL NOT BE
LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, CONSEQUENTIAL OR
EXEMPLARY DAMAGES, INCLUDING BUT NOT LIMITED TO DAMAGES FOR LOSS
OF PROFITS, GOODWILL, USE, DATA OR OTHER INTANGIBLE LOSSES (EVEN IF
THE COMPANY HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES).
SOME JURISDICTIONS DO NOT ALLOW THE EXCLUSION OF THE LIMITATION OR
EXCLUSION OF LIABILITY FOR INCIDENTAL OR CONSEQUENTIAL DAMAGES.
ACCORDINGLY, SOME OF THE ABOVE LIMITATIONS MAY NOT APPLY TO YOU. IN
NO EVENT WILL REGex Software TOTAL CUMULATIVE DAMAGES EXCEED INR
1000.
8.5 Governing Law and Dispute Resolution
The Agreement between you and Company will be governed by, and construed in accordance
with the laws of the India without regard to conflict of laws principles.
Subject to specific agreements relating to dispute resolution, disputes shall be subject to the laws
of India and the courts of New Delhi shall have exclusive jurisdiction over all such disputes.
8.6 Mechanism for Complaints
In case any transaction or attempted transaction in violation of these Terms and/or any
applicable law, rules, regulations, etc. come to your knowledge, or if you have any queries or
concerns regarding the Terms, please feel free to reach out to our grievance officer Mr. Sushil
Kumar at: contact@regexsoftware.com
8.7 Assignment
These Terms, and any rights and licenses granted hereunder, may not be transferred or assigned
by you, but may be assigned by the Company without restriction.