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Data Science Course in India

92,113 Ratings

Become a Data Scientist in 7 months by working on real-world case studies and projects through Data Science Course in India!

  • Data Science Certification in India from iHUB, IIT Roorkee (An Innovation Hub of IIT Roorkee)
  • Master Data Science Tools and Techniques in India
  • Get Data Science Training from eminent IIT Faculty & top Industry Experts
  • 2 Days Campus immersion at IIT Roorkee
  • For Graduates and early Professionals in India

Ranked #1 Data Science Course by India TV

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Data Science Training in India Key Highlights

50+ Live sessions across 7 months
218 Hrs Self-paced Videos
200 Hrs Project & Exercises
Learn from IIT Roorkee Faculty and Industry Practitioners
1:1 with Industry Mentors and 24*7 Support
Resume Preparation and LinkedIn Profile Review
Campus Immersion at IIT Roorkee
No-cost EMI Option
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Data Science Course in India Overview

What can I expect from this data science course in India?

In this online data science course in India, you can expect several benefits, including the following:

  • Free course upgrade throughout a lifetime
  • Anytime online assistance
  • Industry-recognized course completion certification from Intellipaat and IIT Roorkee
  • Lifelong access to the entire courseware

In this data science course in India, you will master important concepts, given below: 

  • Microsoft Excel for data analysis and data transformation
  • Techniques of evaluation, experimentation, and project deployment
  • Analysis segmentation using clustering and the technique of prediction
  • Machine Learning algorithms
  • Data analysis, project life cycle, and Data Science in the real world
  • Python with Data Science
  • Git, Storytelling
  • Data science at scale with PySpark, AI with TensorFlow
  • Deploying Machine Learning models on Clouds ( MLOps)
  • Data visualization with Tableau
  • Natural Language Processing and its Applications
  • Data Science projects, analytics, and recommender systems

Data science can help you upgrade your career if you have access to the right course in this domain. Today, almost all industry verticals, regardless of their customer orientation, are actively hiring data scientists, and thus, getting certified is very worthwhile. .

  • As per Glassdoor, the average income of Data Scientists in India is about  ₹13,07,500 per year
  • LinkedIn hasover 84,000+ Data Science job opportunities in India
  • Data Scientist is the best job of the 21st century – Harvard Business Review
  • The global big data market in terms of revenue was estimated to be worth $162.6 billion in 2021 and is poised to reach $273.4 billion by 2026, growing at a CAGR of 11.0% from 2021 to 2026. – MarketsandMarkets
  • The number of jobs for all the US Data Professionals will increase to 2.7 million per year – IBM

Top companies that hire data scientists are:

  • Fidelity Investments
  • Accenture
  • Aon
  • Oath
  • MSD
  • Intel
  • Amazon
  • Google
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Talk To Us

We are happy to help you 24/7

With data collection, ‘the sooner, the better’ is the best answer. - The CEO of Yahoo
Everything is going to be connected with data and mediated by software - The CEO of Microsoft
The world is now awash in data, and we can see consumers more cleanly - The Co-founder of PayPal

Career Transition

55% Average Salary Hike

$1,20,000 The Highest Salary

12000+ Career Transitions

500+ Hiring Partners

Career Transition Handbook

*Past record is no guarantee of future job prospects

Meet the Data Science Mentors

Who can Apply for the Data Science Course in India?

  • Information Architects and Statisticians
  • Developers looking to master Machine Learning and Predictive Analytics
  • Big Data, Business Analysis, Business Intelligence, and Software Engineering Professionals
  • Aspirants who are looking to work as Machine Learning Experts, Data Scientists, etc.
  • Anyone who wants to learn machine learning, artificial intelligence, data visualization, data analytics, data structures, and algorithms (DSA).
Who can apply

What Role Does a Data Scientist Play?

Data Scientist

Design and implement scalable codes alongside effectively developing high-quality applications.

Analytics and Insights Analyst

Develop solutions for fixing quality issues in the data upon investigating the reported errors in the data.

AI & ML Engineer

Use Lambda functions and API Gateway to integrate machine learning models into web apps and deploy models in SageMaker.

Data Engineer & Data Analyst

Perform data cleansing, and data transformation, analyze the outcomes, and present the insights in reports and dashboards.

Junior Data Scientist

Analyze the operating behavior using advanced statistical techniques and tools. Also, create algorithms with prescriptive and descriptive methods.

Applied Scientist

Derive intelligence for business products through designing and developing machine learning models.

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Skills Covered

Python

Data Science

Data Analysis

AI

GIT

MLOps

Data Wrangling

SQL

Story Telling

Machine Learning

Prediction algorithms

NLP

PySpark

Model

Data visualization

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Tools Covered

pyspark python jupyter Scipy numpy pandas matplotlib tensorflow SQL tableau excel git SparkSQL
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Data Science Course Fees in India

Online Classroom Preferred

  • Live Classes from iHUB IIT Roorkee Faculty & Industry Experts
  • Certification from iHUB IIT Roorkee
  • Career Services (Mock Interviews, Resume Preparation)
  • Placement Assistance upon clearing PRT
  • Dedicated Learning Manager
31 Mar

SAT - SUN

10:00 AM TO 01:00 PM IST (GMT +5:30)

06 Apr

SAT - SUN

08:00 PM TO 11:00 PM IST (GMT +5:30)

13 Apr

SAT - SUN

08:00 PM TO 11:00 PM IST (GMT +5:30)

20 Apr

SAT - SUN

08:00 PM TO 11:00 PM IST (GMT +5:30)

$1,229 10% OFF Expires in

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  • Customized Learning
  • Enterprise grade learning management system (LMS)
  • 24x7 Support
  • Enterprise grade reporting

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Course Curriculum

Live Course Self Paced Industry Expert Academic Faculty

Module 1 – Preparatory Session - Linux and Python

Preview

Python 

  • Introduction to Python and IDEs – The basics of the Python programming language, how you can use various IDEs for python development like Jupyter, Pycharm, etc. 
  • Python Basics – Variables, Data Types, Loops, Conditional Statements, functions, decorators, lambda functions, file handling, exception handling ,etc.
  • Object Oriented Programming – Introduction to OOPs concepts like classes, objects, inheritance, abstraction, polymorphism, encapsulation, etc.
  • Hands-on Sessions And Assignments for Practice – The culmination of all the above concepts with real-world problem statements for better understanding. 

Linux

  • Introduction to Linux  – Establishing the fundamental knowledge of how Linux works and how you can begin with Linux OS. 
  • Linux Basics – File Handling, data extraction, etc.
  • Hands-on Sessions And Assignments for Practice – Strategically curated problem statements for you to start with Linux. 
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Module 2 – Data Wrangling with SQL

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SQL Basics – 

  • Fundamentals of Structured Query Language
  • SQL Tables, Joins, Variables 

Advanced SQL –  

  • SQL Functions, Subqueries, Rules, Views
  • Nested Queries, string functions, pattern matching
  • Mathematical functions, Date-time functions, etc. 

Deep Dive into User Defined Functions

  • Types of UDFs, Inline table value, multi-statement table. 
  • Stored procedures, rank function, SQL ROLLUP, etc.

SQL Optimization and Performance

  • Record grouping, searching, sorting, etc. 
  • Clustered indexes, common table expressions.

Hands-on exercise: 

Writing comparison data between the past year and the present year with respect to top products, ignoring the redundant/junk data, identifying the meaningful data,  and identifying the demand in the future(using complex subqueries, functions, pattern matching concepts).

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Extract Transform Load

  • Interacting with APIs

Data Handling with NumPy

  • NumPy Arrays, CRUD Operations, etc.
  • Linear Algebra – Matrix multiplication, CRUD operations, Inverse, Transpose, Rank, Determinant of a matrix, Scalars, Vectors, Matrices.

Data Manipulation Using Pandas

  • Loading the data, data frames, series, CRUD operations, splitting the data, etc.

Data Preprocessing

  • Exploratory Data Analysis, Feature engineering, Feature scaling, Normalization, standardization, etc.
  • Null Value Imputations, Outliers Analysis and Handling, VIF, Bias-variance trade-off, cross-validation techniques, train-test split, etc.

Data Visualization

  • Bar charts, scatter plots, count plots, line plots, pie charts, donut charts, etc. with Python matplotlib.
  • Regression plots, categorical plots, area plots, etc, with Python seaborn.
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Descriptive Statistics – 

  • Measure of central tendency, the measure of spread, five points summary, etc. 

Probability 

  • Probability Distributions, Bayes’ theorem, central limit theorem. 

Inferential Statistics –  

  • Correlation, covariance, confidence intervals, hypothesis testing, F-test, Z-test, t-test, ANOVA, chi-square test, etc.
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Introduction to Machine Learning 

  • Supervised, Unsupervised Learning.
  • Introduction to scikit-learn, Keras, etc.

Regression 

  • Introduction classification problems, Identification of a regression problem, dependent and independent variables.
  • How to train the model in a regression problem.
  • How to evaluate the model for a regression problem.
  • How to optimize the efficiency of the regression model.

Classification 

  • Introduction to classification problems, Identification of a classification problem, and dependent and independent variables.
  • How to train the model in a classification problem.
  • How to evaluate the model for a classification problem.
  • How to optimize the efficiency of the classification model.

Clustering 

  • Introduction to clustering problems, Identification of a clustering problem, dependent and independent variables.
  • How to train the model in a clustering problem.
  • How to evaluate the model for a clustering problem.
  • How to optimize the efficiency of the clustering model.
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  • Linear Regression – Creating linear regression models for linear data using statistical tests, data preprocessing, standardization, normalization, etc.
  • Logistic Regression – Creating logistic regression models for classification problems – such as if a person is diabetic or not, if there will be rain or not, etc.
  • Decision Tree – Creating decision tree models on classification problems in a tree like format with optimal solutions.
  • Random Forest – Creating random forest models for classification problems in a supervised learning approach.
  • Support Vector Machine – SVM or support vector machines for regression and classification problems.
  • Gradient Descent – Gradient descent algorithm that is an iterative optimization approach to finding the local minimum and maximum of a given function.
  • K-Nearest Neighbors – A simple algorithm that can be used for classification problems.
  • Time Series Forecasting – Making use of time series data, gathering insights and useful forecasting solutions using time series forecasting.
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  • K-means – The k-means algorithm that can be used for clustering problems in an unsupervised learning approach.
  • Dimensionality reduction – Handling multi dimensional data and standardizing the features for easier computation.
  • Linear Discriminant Analysis –  LDA or linear discriminant analysis to reduce or optimize the dimensions in the multidimensional data.
  • Principal Component Analysis – PCA follows the same approach in handling the multidimensional data.

Performance Metrics

  • Classification reports – To evaluate the model on various metrics like recall, precision, f-support, etc.
  • Confusion matrix – To evaluate the true positive/negative, and false positive/negative outcomes in the model.
  • r2, adjusted r2, mean squared error, etc.
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Artificial Intelligence Basics 

  • Introduction to keras API and TensorFlow

Neural Networks

  • Neural networks
  • Multi-layered Neural Networks
  • Artificial Neural Networks 

Deep Learning 

  • Introduction to Deep Learning (by Academic Faculty)
  • Deep neural networks
  • Convolutional Neural Networks 
  • Recurrent Neural Networks
  • GPU in deep learning
  • Autoencoders, restricted boltzmann machine 
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The Data Science capstone project focuses on establishing a strong hold of analyzing a problem and coming up with solutions based on insights from the data analysis perspective. The capstone project will help you master the following verticals: 

  • Extracting, loading and transforming data into usable format to gather insights. 
  • Data manipulation and handling to pre-process the data.
  • Feature engineering and scaling the data for various problem statements. 
  • Model selection and model building on various classification, regression problems using supervised/unsupervised machine learning algorithms.
  • Assessment and monitoring of the model created using the machine learning models.
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  • Recommendation Engine – The case study will guide you through various processes and techniques in machine learning to build a recommendation engine that can be used for movie recommendations, restaurant recommendations, book recommendations, etc.
  • Rating Predictions – This text classification and sentiment analysis case study will guide you towards working with text data and building efficient machine learning models that can predict ratings, sentiments, etc.
  • Census – Using predictive modeling techniques on the census data, you will be able to create actionable insights for a given population and create machine learning models that will predict or classify various features like total population, user income, etc.
  • Housing – This real estate case study will guide you towards real world problems, where a culmination of multiple features will guide you towards creating a predictive model to predict housing prices.
  • Object Detection – A much more advanced yet simple case study that will guide you toward making a machine learning model that can detect objects in real-time.
  • Stock Market Analysis – Using historical stock market data, you will learn about how feature engineering and feature selection can provide you with some really helpful and actionable insights for specific stocks.
  • Banking Problem – A classification problem that predicts consumer behavior based on various features using machine learning models.
  • AI Chatbot – Using the NLTK python library, you will be able to apply machine learning algorithms and create an AI chatbot.
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  • LSTM – What is LSTM?, How does LSTM work, Applications of LSTM, etc.
  • Transformers – What are transformers, how does a transformer work in deep learning, applications of transformers, types of transformers, encoder-decoded, self-attention, etc.
  • BERT – Language Models, What is BERT, How does BERT work, how is BERT different from LSTM, applications of BERT, etc.
  • GPT – What are generative pre-trained models (GPT), how does a GPT work?, real life examples of GPT, etc.
  • LLM – NLP and Language models, what are LLMs, how does a LLM work, applications of LLM, etc.
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Elective

Power BI Basics

  • Introduction to PowerBI, Use cases and BI Tools , Data Warehousing, Power BI components, Power BI Desktop, workflows and reports , Data Extraction with Power BI.
  • SaaS Connectors, Working with Azure SQL database, Python and R with Power BI
  • Power Query Editor, Advance Editor, Query Dependency Editor, Data Transformations, Shaping and Combining Data ,M Query and Hierarchies in Power BI.

DAX 

  • Data Modeling and DAX, Time Intelligence Functions, DAX Advanced Features

Data Visualization with Analytics  

  • Slicers, filters, Drill Down Reports
  • Power BI Query, Q & A and Data Insights
  • Power BI Settings, Administration and Direct Connectivity
  • Embedded Power BI API and Power BI Mobile
  • Power BI Advance and Power BI Premium

Hands-on Exercise:

Creating a dashboard to depict actionable insights in sales data.

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Introduction to MLOps 

  • MLOps lifecycle
  • MLOps pipeline 
  • MLOps Components, Processes, etc

Deploying Machine Learning Models 

  • Introduction to Azure Machine Learning 
  • Deploying Machine Learning Models using Azure
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Version Control 

  • What is version control, types, SVN.

GIT

  • Git Lifecycle, Common Git commands, Working with branches in Git
  • Github collaboration (pull request), Github Authentication (ssh and Http)
  • Merging branches, Resolving merge conflicts, Git workflow
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  • Job Search Strategy
  • Resume Building
  • Linkedin Profile Creation
  • Interview Preparation Sessions by Industry Experts
  • Mock Interviews
  • Placement opportunities with 400+ hiring partners upon clearing the Placement Readiness Test.
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Excel Fundamentals 

  • Reading the Data, Referencing in formulae , Name Range, Logical Functions, Conditional Formatting, Advanced Validation, Dynamic Tables in Excel, Sorting and Filtering 
  • Working with Charts in Excel, Pivot Table, Dashboards, Data And File Security 
  • VBA Macros, Ranges and Worksheet in VBA 
  • IF conditions, loops, Debugging, etc.

Excel For Data Analytics 

  • Handling Text Data, Splitting, combining, data imputation on text data, Working with Dates in Excel, Data Conversion, Handling Missing Values, Data Cleaning, Working with Tables in Excel, etc.  

Data Visualization with Excel

  • Charts, Pie charts, Scatter and bubble charts
  • Bar charts, Column charts, Line charts, Maps
  • Multiples: A set of charts with the same axes, Matrices, Cards, Tiles

Excel Power Tools 

  • Power Pivot, Power Query and Power View

Classification Problems using Excel

  • Binary Classification Problems, Confusion Matrix, AUC and ROC curve 
  • Multiple Classification Problems  

Information Measure in Excel

  • Probability, Entropy, Dependence 
  • Mutual Information 

Regression Problems Using Excel

  • Standardization, Normalization, Probability Distributions 
  • Inferential Statistics, Hypothesis Testing, ANOVA, Covariance, Correlation
  • Linear Regression, Logistic Regression, Error in regression, Information Gain using Regression

Hands-on Exercise:

Classification problem using excel on sales data, and statistical tests on various samples from the population.

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Project Work

Peer Learning

Via Intellipaat PeerChat, you can interact with your peers across all classes and batches and even our alumni. Collaborate on projects, share job referrals & interview experiences, compete with the best, make new friends — the possibilities are endless and our community has something for everyone!

class-notifications
Hackathons
career-services
major-announcements
collaborative-learning

Career Services

Career Services

Career Oriented Sessions

Throughout the course

Over 10+ live interactive sessions with an industry expert to gain knowledge and experience on how to build skills that are expected by hiring managers. These will be guided sessions that will help you stay on track with your up upskilling.

Resume & LinkedIn Profile Building

After 70% of course completion

Get assistance in creating a world-class resume & LinkedIn profile from our career services team and learn how to grab the attention of the hiring manager at the profile shortlisting stage

Mock Interview Preparation

After 80% of the course completion.

Students will go through a number of mock interviews conducted by technical experts who will then offer tips and constructive feedback for reference and improvement.

1 on 1 Career Mentoring Sessions

After 90% of the course completion

Attend one-on-one sessions with career mentors on how to develop the required skills and attitude to secure a dream job based on a learner’s educational background, past experience, and future career aspirations.

Placement Assistance

Upon movement to the Placement Pool

Placement opportunities are provided once the learner is moved to the placement pool upon clearing Placement Readiness Test (PRT)

Exclusive access to Intellipaat Job portal

After 80% of the course completion

Exclusive access to our dedicated job portal and apply for jobs. More than 400 hiring partners’ including top start-ups and product companies hiring our learners. Mentored support on job search and relevant jobs for your career growth.

Data Science Certification in India

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Key achievements of IIT Roorkee:

Participants completing this course successfully will be awarded by Advance certification in Data Science & Artificial Intelligence by IIT Roorkee and Intellipaat.

At the end of this Data Science certification course in India, there will be quizzes that perfectly reflect the type of questions asked in the respective certification exams. They will help you score better.

Data Science Course in India Reviews

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Data Science Course in India FAQs

What is Data Science?

Data Science operates as a detective for data. It uses scientific methods and computer skills to find valuable information in different types of data. It’s a mix of math, computer science, and special knowledge about specific topics. The goal is to analyze big sets of data, discover patterns, and help make better decisions in different industries.

Intellipaat is one of the most affordable e-learning providers today. The cost of this data science course in India is ₹100,035.

No Cost EMI options are available. For more detailed information, contact our team at: +91-7022374614

Since it involves various aspects of advanced technologies, such as machine learning, deep learning, and artificial intelligence, among others, it is comparatively difficult to learn. However, data scientist training from Intellipaat is offered by experts in this domain who have a lot of experience in the field. They make all concepts easier to understand as they explain each concept with the help of several real-life examples.

Intellipaat offers an exclusive online data science course in India with placement for professionals who want to expand their knowledge base and start a career in this field. There are many reasons for choosing Intellipaat:

  • A personal mentor to track your progress
  • Immersive online instructor-led sessions conducted by SMEs
  • Extensive LMS, allowing you to view recorded sessions within 3 hours
  • Real-time exercises, assignments, and projects
  • 24/7 learning support
  • Large community of like-minded learners
  • Industry-recognized Intellipaat badge
  • Personalized job support

According to Economics Time, India’s data science education market is expected to reach USD 1.391 billion by 2028, growing at a CAGR of 57.5%. The sector’s size in 2023 was USD 204.23 million and is projected to see a CAGR of 57.5% over the next five years. The report also predicts a 57% increase in data jobs by 2028.

Intellipaat offers one of the best data science courses in India that will help you become a successful data scientist. The other top courses are Artificial Intelligence, Data Analytics, Machine Learning, R Certification, Data Science with Python, Python, Business Analytics, and others are comprehensive and tailor-made to suit you as per the industry’s needs.

If you are looking for some free resources on data science then read our blogs on Interview Questions and Answers, Tutorials and everything to know about data scientist

Yes. Intellipaat provides a data science master’s course for learners. It is designed by subject matter experts who will make you proficient in various concepts and techniques, like deep learning, SQL, statistical computation, real-time analytics, parsing machine-generated data, using Big Data Analytics with Spark, and more. The curriculum covers 10 significant courses and 53 real-world assignments and projects, along with 1 capstone project. Also, you will have complete access to the IBM Watson Cloud Lab for Chatbots.

This data science course in India is curated by top data scientists from India and the United States. These SMEs have designed the course in such a manner that even if you are from a non-technical background and have almost zero knowledge of this domain, you can still learn and adapt all concepts easily. Also, we provide practical experience through real-time projects that allow even freshers to easily grasp the concepts.

In the career mentoring session at Intellipaat, our domain experts offer solutions to all your queries that are based on career opportunities and the growth available in this domain.

Intellipaat selects subject matter experts from top MNCs, who have at least 8 to 12 years of experience in the domain as instructors. They are qualified data science instructors and are selected after going through our rigorous selection process and proving their capabilities.

Intellipaat’s teaching assistants are SMEs whose main aim is to make you a certified professional in the respective domain. The trainers conduct interactive video lectures to teach the latest technologies and enrich your experience with various industry-based projects. The teaching assistance provided by Intellipaat is only available during regular hours.

If you wish to enroll in our data science course in India , then you need to first make a choice between online instructor-led training and self-paced training. Once you do that, you can make the payment using any major credit card, debit card, or EMI option.

Intellipaat provides various group offers and discounts for its online training as per the size and type of the particular group. If you wish to avail the discount, you need to get in touch with our course advisors who will explain to you all the details regarding it.

Intellipaat is offering 24/7 query resolution, and you can raise a ticket with the dedicated support team at any time. You can avail of email support for all your queries. If your query does not get resolved through email, we can also arrange one-on-one sessions with our support team. However, 1:1 session support is provided for a period of 6 months from the start date of your course.

Intellipaat provides placement assistance to all learners who have successfully completed the training and moved to the placement pool after clearing the PRT( Placement Readiness Test) More than 500+ top MNC’s and startups hire Intellipaat learners. Our Alumni works with Google, Microsoft, Amazon, Sony, Ericsson, TCS, Mu Sigma, etc.

Apparently, no. Our job assistance is aimed at helping you land in your dream job. It offers a potential opportunity for you to explore various competitive openings in the corporate world and find a well-paid job, matching your profile. The final decision on hiring will always be based on your performance in the interview and the requirements of the recruiter.

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Data Science Course in India

India is often referred to as the “land of diversity”. It is a vast and culturally rich country located in South Asia. Geographically, it spans the Indian subcontinent and shares borders with Pakistan, China, Nepal, Bhutan, Bangladesh, and Myanmar, making it a central and prominent nation in the region.

India experiences a varied range of weather patterns due to its vast size and varied topography. The climate varies from the scorching arid deserts of Rajasthan to the tropical monsoons of Kerala’s coastal regions.

India is one of the world’s largest economies, driven by sectors such as information technology, manufacturing, agriculture, and services. The country’s dynamic business environment, coupled with a large and young workforce, positions India as a global economic powerhouse with immense potential for innovation and growth.

Some of the tourist attractions in India include: