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Data Analytics Course

80,663 Ratings

Become a Data Analyst by mastering Data Analysis tool and techniques with our Data Analytics Course.

  • Data Analytics Course by iHUB IIT Roorkee (An Innovation Hub of IIT Roorkee)
  • Learn Data Analysis from eminent IIT Faculty & top Industry Experts
  • Master SQL, Python, Machine Learning algorithms, MS. Excel and PowerBI.
  • 2 Days Campus Immersion at IIT Roorkee
  • Get Placement Support upon Data Analyst Course completion

Ranked #1 Data Analyst Course by Economic Times

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  • Data Analytics Courses
    • Course 1

    • Course 2

    • Course 3
      Statistics And Probability

    • Course 4
      Machine Learning

    • Course 5
      Performance Metrics

    • Course 6
      Time Series Forecasting

    • Course 7
      Business Problem Solving Insights and Storytelling

    • Course 8
      Data Modeling

    • Course 9
      Data Analytics Capstone Project

    • Course 10
      Business Case Studies

    • Course 11
      Microsoft Excel

    • Course 12
      Visualizations using PowerBI

Key Highlights

50+ Live sessions across 7 months
218 Hrs Self-paced Videos
200 Hrs Project & Exercises
Learn from IIT Faculty and Industry Practitioners
One-on-one with Industry Mentors
Resume Preparation and LinkedIn Profile Review
24*7 Support
No-cost EMI Option
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Online Data Analytics Course Overview

Why become a Data Analyst?

Data Analysts are among the most sought-after career options in today’s technologically advanced world. There are numerous job opportunities available in this domain, which is one of the main reasons why you can opt for this career option. Also, check the stats below:

  • According to recent data from IBM, the number of job openings in Data Analytics in 2030 is estimated to be 49.2 million. Hence, the data represents a promising growth of 15% per year from the year 2020 to 2030.

Through our Data Analyst Courses you will be able to master the mentioned skills

  • SQL
  • Python
  • Statistics And Probability
  • Machine Learning
  • Performance Metrics
  • Time Series Forecasting
  • Business Problem Solving, Insights and Storytelling
  • Data Modeling
  • PowerBI
  • Microsoft Excel

After completing this Data Analyst Certification Training program, you will be able to work on solving complex business problems through the use of machine learning algorithms and create value out of raw data.

You will get an excellent chance to work on multiple case studies, hands-on exercises, and project work to master the skills required to become a successful Data Analyst.

Advanced Data Analyst Certification for business will be awarded by iHUB IIT Roorkee upon successful completion of the Data Analyst Course. Career assistance services will be provided by Intellipaat, which include mock interviews, resume preparation, and three guaranteed interviews with top employers.

There are no prerequisites for taking Data Analyst Courses online. Basic knowledge of Data Analysis, statistics, and probability is beneficial for taking a Data Analyst Course.

According to Glassdoor, the average income of a Data Analyst in the United States is about US$62,453 per year. This may increase to US$95,000 per year with more experience and better work quality.

In India, the average salary of these professionals is approximately ₹503,000 per annum, and with more experience, it can rise to ₹1,005,000 per annum

Data Analysts perform the complete life-cycle of Data Analysis, whereas business analysts implement, build, analyze, and report the capabilities of the business. Data scientists, on the other hand, perform statistical analysis to build machine learning systems

Here are some compelling reasons to look for:

  • A Data Analyst at Microsoft Corporation earns an average salary of $115,000 per year – Indeed
  • The USA faces a shortage of 165,000 Data Analysts and 1.5 managers with Data Analysis skills – McKinsey
  • There are over 30,000 jobs available for Data Analysts in the United States alone – LinkedIn

Today, Data Analytics is one of the top domains, as we are living in a data-driven world. If you want to get ahead in your career, then you need to learn Data Analytics, as it is being deployed in every organization, regardless of the industry. Intellipaat’s Data Analyst Course have been created to give you an edge in this data-driven world. Through this Data Analyst Training program, you will work on real-world Data Analytics projects and case studies so that you can get hands-on experience in this domain.

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Who can apply for this Data Analyst Training?

  • Non-IT Professionals in sectors such as HR, banking, marketing, sales, etc.
  • BI Professionals
  • Data Analytics Professionals
  • Project Managers
  • Software Developers
  • Information Architects
  • Freshers and Undergraduates can apply for the course

What role does a Data Analyst play?

Data Analyst

Create predictive models like churn likelihood, and customer lifetime value, and help the team implement these models accordingly.

Data Scientist

Develop models concerning the numerous cost components that power the various margin awareness initiatives.

Data Analytics Specialist

Maintain the specifications of data engineering and meet the objectives of online data visualization platforms, such as Alteryx and Tableau.

Visualization and Reporting Analyst

Build attractive, interactive, and intuitive data visualizations, including reports, graphs, presentations, and dashboards.

Business Intelligence Analyst

Identify, build, and execute the techniques of Data Analysis to allow the team to make significant impacts on the business.

Business Analyst

Generate detailed reports and dashboards of high quality, and give presentations.

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Skills to Master


Data Wrangling

Data Analysis

Prediction algorithms

Data visualization

Time Series

Machine Learning


Advanced Statistics

Data Mining

R Programming

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Tools to Master

R Adv-Excel SQL Power-BI-1 Presto python Knime
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Data Analytics Syllabus

Live Course Industry Expert Academic Faculty
  1. Introduction to SQL
  2. Database Normalization and Entity Relationship Model(self-paced)
  3. SQL Operators
  4. Working with SQL: Join, Tables, and Variables
  5. Deep Dive into SQL Functions
  6. Working with Subqueries
  7. SQL Views, Functions, and Stored Procedures
  8. Deep Dive into User-defined Functions
  9. SQL Optimization and Performance
  10. Advanced Topics
  11. Managing Database Concurrency
  12. Practice Session

Case Study

Writing comparison data between past year to 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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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.

Data Manipulation with Numpy, Pandas, and Visualization – Using large datasets, you will learn about various techniques and processes that will convert raw unstructured data into actionable insights for further computations i.e. machine learning models, etc.

Case Study – The culmination of all the above concepts with real-world problem statements for better understanding.

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Descriptive Statistics

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


  1. Probability Distributions, Probability in Business Analytics
  2. Probability Distributions, Binomial distribution, Poisson distribution, bayes theorem, central limit theorem.

Inferential Advanced Statistics (by Academic Facutly)

  1. Correlation, covariance, confidence intervals, hypothesis testing, F-test, Z-test, t-test, ANOVA, chi-square test, etc.

Case Study

This case study will cover the following concepts:

  1. Building a statistical analysis model that uses quantification, representations, and experimental data
  2. Reviewing, analyzing, and drawing conclusions from the data
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Introduction to Machine learning

  1. Supervised, Unsupervised learning.
  2. Introduction to scikit-learn, Keras, etc.


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


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


  1. Introduction to clustering problems, Identification of a clustering problem, dependent and independent variables.
  2. How to train the model in a clustering problem.
  3. How to evaluate the model for a clustering problem.
  4. How to optimize the efficiency of the clustering model.

Supervised Learning

  1. Linear Regression – Creating linear regression models for linear data using statistical tests, data preprocessing, standardization, normalization, etc.
  2. 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.

Unsupervised Learning

  1. K-means – The k-means algorithm that can be used for clustering problems in an unsupervised learning approach.
  2. Dimensionality reduction – Handling multi dimensional data and standardizing the features for easier computation.
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  1. Classification reports – To evaluate the model on various metrics like recall, precision, f-support, etc.
  2. Confusion matrix – To evaluate the true positive/negative, false positive/negative outcomes in the model.
  3. r2, adjusted r2, mean squared error, etc.
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Making use of time series data, gathering insights and useful forecasting solutions using time series forecasting.

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Business Domains – Learn about various business domains and understand how one differs from the other.

  1. Finance
  2. Marketing
  3. Retail
  4. Supply Chain

Understanding the business problems and formulating hypotheses – Learn about formulating hypotheses for various business problems on samples and populations.

Exploratory Data Analysis to Gather insights – Learn about the exploratory data analysis and how it enables a fool proof producer of actionable insights.

Data Storytelling: Narrate stories in a memorable way – Learn to narrate business problems and solutions in simple relatable format that makes it easier to understand and recall.

Case Study
This case study will cover the following concepts:

  1. Create actionable insights from raw unstructured data to solve real world business problems.
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Feature Selection – Feature selection techniques in python that includes recursive feature elimination, Recursive feature elimination using cross validation, variance threshold, etc.

Feature Engineering – Feature engineering techniques that help in reducing the best features to use for data modeling.

Model Tuning – Optimization techniques like hyperparameter tuning to increase the efficiency of the machine learning models.

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Problem Statement and Project Objectives – You will learn how to formulate various problem statements and understand the business objective of any problem statement that comes as a requirement.

Approach for the Solution – Creating various statistical insights based solutions to approach the problem will guide your learnings to finish a project from scratch.

Optimum Solutions – Formulating actionable insights backed by statistical evidence will help you find the most effective solution for your problem statements.

Evaluation Metrics – You will be able to apply various evaluation metrics to your project/solution. It will validate your approach and point towards shortcomings backed by insights, if any.

Gathering Actionable insights – You will learn about how a problem’s solution isn’t just creating a machine learning model, the insights that were gained from your analysis should be presentable in the form of actionable insights to capitalize on the solutions formulated for the problem statement.

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Customer Churn – The case study involves studying the customer data for a given XYZ company, and using statistical tests and predictive modeling, we will gather insights to efficiently create an action plan for the same.

Sales Forecasting – By studying the various patterns and sales data for a firm/store, we will use the time series forecasting method to forecast the number of sales for the next given time period(weeks, months, years, etc.)

Census – After studying the population data, we will gather insights and through predictive modeling try to create actionable insights on the same, it could be average income of an individual, or most likely profession, etc.

Predictive Modeling – Various case studies on categorical and continuous data, to create predictive models that will predict specific outcomes based on the business problems.

HR Analytics – Based on the data provided by a firm, we will study the HR analytics data, and create actionable insights using various statistical tests and hypothesis testing.

Dimensionality Reduction – To understand the impact of multidimensional data, we will go through various dimensionality reduction techniques and optimize the computational time on the same that will eventually be used for various classification and regression problems.

Housing – A case study that will give you insight into how real estate firms can narrow down on the pricing, customer choices, etc. using various predictive modeling techniques.

Customer Segmentation – Using unsupervised learning techniques, we will learn about customer segmentation, which can be quite useful for e-commerce sectors, stores, marketing funnels, etc.

Inventory Management – In this case study, you will learn about how meaningful insights can be used to drive a supply chain, using predictive modeling and clustering techniques.

Disease Prediction – A medical endeavor that is achieved through machine learning will give you an insight into how the predictive model can prove to be a great marvel in early detection of various diseases.

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Excel Fundamentals

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

Excel For Data Analytics

  1. 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

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

Ensuring Data and File Security

  1. Data and file security in Excel, protecting row, column, and cell, the different safeguarding techniques.

Getting started with VBA Macros

  1. Learning about VBA macros in Excel, executing macros in Excel, the macro shortcuts, applications, the concept of relative reference in macros, In-depth understanding of Visual Basic for Applications, the VBA Editor, module insertion and deletion, performing action with Sub and ending Sub if condition not met.

Statistics with Excel

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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.


  • 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

Case Study:

This case study will cover the following concepts:

  • Creating a dashboard to depict actionable insights in sales data.
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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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Data Analytics Projects

Projects will be a part of your Data Analyst Master’s program to consolidate your learning. It will ensure that you have real-world experience in Data Analytics.

Data Analytics Career Transition

55% Average Salary Hike

$1,22,000 Highest Salary

10000+ Career Transitions

300+ Hiring Partners

Career Transition Handbook

*Past record is no guarantee of future job prospects

Data Analyst Certification

Our Data Analytics Training is created by experts from top MNCs for professionals to get the most suitable jobs in the best organizations. Further, these Data Analytics Online Courses includes real-time projects and case studies that are highly valuable in the corporate world.

You will receive the Data Analyst Course certification from Intellipaat and iHUB IIT Roorkee after completing the Data Analyst Course. Along with that, you will also be able to clear the following certifications:

  • SQL Certification
  • Power BI Certification
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Industry Trends

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!


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 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, are hiring our learners. Mentored support on job search and relevant jobs for your career growth.

Meet the Data Analytics Mentors

Our Alumni Work At


Data Analyst Course Fees

Online Classroom Preferred

  • Everything in Self-Paced Learning, plus
  • 50+ Live sessions across 7 months of Instructor-led Training
  • One to one doubt resolution sessions
  • Attend as many batches as you want for Lifetime
  • Job Assistance
20 Apr


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

20 Apr


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

23 Apr


07:00 AM - 09:00 AM IST (GMT +5:30)

$1,229 10% OFF Expires in

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  • Enterprise Grade Learning Management System (LMS)
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  • Enterprise Grade Reporting

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Data Analytics Courses FAQ

Why should I enroll in best Data Analytics Certification Course?

Our Data Analytics Certification Course, in association with iHUB IIT Roorkee, is industry-designed, and developed for you to fast-track your career in the domain of Data Analytics. If you don’t want to get into the nitty-gritty of programming and spend long hours coding, then these Data Analytics Courses are for you.

This online Data Analyst Course involves the following:

  1. You will work on real-life projects
  2. You will work on industry-grade assignments with high relevance in the corporate world
  3. You can apply for the best Data Science and Data Analyst Jobs in top MNCs
  4. You will get lifetime access to the Data Analyst Course and the course material, along with a lifetime upgrade and 24/7 support

If you are looking for free resources on Data Analytics then read our blogs on Data Analytics TutorialData Analytics Interview Questions, and also visit our YouTube channel for free videos.

Data Analysis is the process of data cleaning, transformation, and reporting carried out to generate valuable information that can enable business decision-making.

The tools used for Data Analysis make the tasks of data processing, data manipulation, Data Analysis, and pattern and trend identification much easier. Some of the top Data Analysis tools are:

  • R programming
  • Tableau Public
  • QlikView
  • RapidMiner
  • Excel
  • Apache Spark
  • Splunk
  • SAS

Here are the significant differences between Data Analytics, Data Analysis, and Data Analysts:

Data Analytics: Data Analytics involves the process of discovering, interpreting, visualizing, and reporting the patterns in data that can drive business strategy, decisions, and outcomes.

Data Analysis: Data Analysis is a subset of the broader field of Data Analytics. Data Analysis consists of specific actions such as data cleaning, transformation, modeling, and questioning to help find useful information from a single and already prepared set of data.

Data Analysts: Data Analysts are those professionals who come up with meaningful insights from the data. They have both the technical expertise and the communication skills to derive and present quantitative findings to technical and non-technical teams, clients, and stakeholders.

A career in the Data Analytics domain is not just a good career option but also one of the most popular careers today. You can find jobs in this domain across a diverse range of industries and companies around the globe by completing this training in Data Analytics.

As per the Bureau of Labour Statistics, the estimated growth rate for Data Analytics professionals will shoot up by 23% by the year 2026.

The eligibility criteria for the online Data Analysis Certification course typically include a minimum educational qualification, often a bachelor’s degree in a related field such as computer science, statistics, or mathematics. Furthermore, it’s frequently necessary to have a fundamental understanding of statistical ideas, data processing tools, and programming languages like Python or R. Certain courses can require previous knowledge of Data Analysis or similar fields. Possessing database and data visualization tool expertise may also be helpful. Before participating in the program, potential participants should confirm that they meet the prerequisites, which may differ depending on the course provider.

To become a Data Analyst, you must have the following qualifications:

  • For entry-level jobs, you need to have a Bachelor’s degree
  • For jobs at a higher-level position, you must have a Master’s degree
  • You should have a degree in the field of statistics, mathematics, computer science, or other similar domains.

For becoming a Data Analyst, you should meet the following criteria:

  • Gain a bachelor’s or master’s degree in statistics, computer science, or in the IT field
  • Acquire the skills required to become a Data Analyst
  • Gain experience in the Data Analytics field
  • Consider getting a Data Analysis Certification from a reputed institute

You can attain all the necessary skills, gain real-time experience, and receive a certification with the help of Intellipaat’s Data Analytics Certification Course.

Having a college degree in the fields of mathematics, probability, or computer science can definitely be beneficial. However, it is not mandatory for you to have the same. The main requirement for becoming a Data Analyst is that you need to possess the necessary skills in this domain. So, having a degree can help you immensely; however, it is still a secondary requirement.

Intellipaat offers self-paced training to those who wish to learn at their own pace. This training also gives you benefits like query resolution through email, live sessions with trainers, round-the-clock support, and access to the learning modules on the LMS for an entire lifetime. Also, you will get the latest version of the Data Analyst Course material at no additional cost.

Intellipaat’s self-paced training is priced 75% less compared to the online instructor-led training. If you face any problems while learning, our team can always arrange a virtual live class with the trainers as well.

To be eligible to get into the placement pool, the learner has to complete the Data Analyst Certification online along with the submission of all projects and assignments. After this, he/she has to clear the Placement Readiness Test (PRT) to get into the placement pool and get access to our job portal as well as the career mentoring sessions.

Intellipaat helps fresh college graduates with its placement assistance programs. Once you clear the PRT you will be moved to the placement pool.

Intellipaat’s Data Analyst course, in collaboration with IIT Roorkee, aims to equip learners with a comprehensive understanding of statistical techniques, regression analysis, data blending, extraction, and forecasting methodologies. It focuses on mastering data visualization tools like Tableau and Power BI, organizing data effectively, designing insightful dashboards, and acquiring practical skills through real-world case studies and projects to enhance career prospects in data analytics.

This Data Analyst Certification Course covers all the essential topics from scratch, including programming languages like SQL and Python, statistical concepts like probability, and machine learning algorithms. It also covers data modeling approaches, a capstone project to apply the learnings, real-world business case studies, and optional modules on tools like Microsoft Excel and PowerBI for data visualization.

The total duration of the Data Analyst course is 7 months.

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

Intellipaat offers learners the most updated, relevant, and high-value real-world projects in the respective training program. In this way, aspiring candidates can apply the knowledge they have gained in real-world industry settings. Each training includes multiple projects that extensively assess your skills, learning, and practical knowledge, ensuring you are industry-ready.

Intellipaat provides placement assistance to all learners who have completed the training and moved to the placement pool after clearing the PRT (Placement Readiness Test). More than 500 top MNCs and startups hire Intellipaat learners. Our alumni work with Google, Microsoft, Amazon, Sony, Ericsson, TCS, Mu Sigma, and other renowned brands.

Learners are required to submit the mandatory assignments, project work, and quizzes to receive the Intellipaat-verified certificates.

Apparently, no. Our goal with job assistance is to get you into the career of your dreams. It gives you opportunities to explore various competitive positions in the corporate world and find a well-paid job, matching your profile. The recruiters requirements and your performance during the interview will always be taken into consideration when making the hiring choice.

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