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Executive Post Graduate Certification in Data Analytics

3,593 Ratings

Learn from IIT Faculty & Industry Experts with Guaranteed Job Interviews.
Campus Immersion at IIT Roorkee.

Master machine learning and artificial intelligence with this data analytics course from iHub Divya Sampark IIT Roorkee and Intellipaat. This advanced online boot camp features 1:1 mentorship by Intellipaat instructors. The top 2 performers from every batch will be awarded a scholarship of Rs. 80,000. iHub Divya Sampark will also provide funds of up to Rs. 50 Lakhs and incubation support to candidates with great ideas.

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Ranked #1 Data Science and Analytics Program by India TV



Course Preview

Learning Format

Online Bootcamp

Live Classes

11 Months

iHub IIT Roorkee


Campus Immersion

IIT Roorkee


Hiring Partners

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About Program

This program by iHub Divya Sampark, IIT Roorkee helps you gain the data analytics, machine learning, and artificial intelligence skills sought after by top employers.

Key Highlights

620 Hrs of Applied Learning
90+ Live Sessions Across 11 months
218 Hrs of Self-Paced Learning
Learn from IIT Faculty & Industry Practitioners
50+ Industry Projects & Case Studies
One-on-One with Industry Mentors
24*7 Support
Dedicated Learning Management Team
Designed for Working Professionals & Freshers
1:1 Mock Interview
No-Cost EMI Option
iHub Divya Sampark - IIT Roorkee Certification
Designed for Working Professionals and Freshers
2 Days Campus Immersion at IIT Roorkee
3 Guaranteed Interviews upon movement to Placement Pool
Free Career Counselling
Up to Rs. 50 Lakhs startup Incubation Support*
Top 2 performers will receive Rs.80,000 in Scholarships *

About iHub Divya Sampark

iHub Divya Sampark is an initiative of the Department of Science and Technology (DST), the Government of India, and the Indian Institute of Technology (IIT Roorkee). It was launched to promote research on tomorrow's technologies and contribute to areas such as healthcare, industry, and smart cities.

Key Achievements of IIT Roorkee:

Executive-Post-Graduate-Certification-in-Data-Analystics Click to Zoom

Program in Collaboration with Microsoft

Benefits for students from Microsoft:

  • Free Voucher for Exam AZ-900: Microsoft Azure Fundamentals worth $99
  • Industry-recognized certification from Microsoft
  • Real-time projects and exercises
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Career Transition

55% Average Salary Hike

$1,27,000 Highest Salary

800+ Career Transitions

300+ Hiring Partners

Career Transition Handbook

*Past record is no guarantee of future job prospects

Who Can Apply for the Course?

  • Individuals with a bachelor’s degree and a strong interest in learning Data Analytics
  • IT professionals looking to make a career transition as Data Analyst and Data Scientists
  • Professionals looking to advance in their careers in IT
  • Business Intelligence professionals
  • Developers and Project Managers
  • Entry-level professionals looking to build their careers in Data Analysis
  • Undergraduate freshers with an interest in Data Analytics
  • Anyone who wants to become an entrepreneur

What roles can a data analyst play?

Data Scientist

Use data analysis and data processing to understand business challenges and offer the best solutions to the organization.

Business Analyst

Extract data from the respective sources to perform business analysis, and generate reports, dashboards, and metrics to monitor the company’s performance.

Data Architect

Create blueprints for managing data so as to facilitate easy integration, centralization, and protection of the database, along with due security precautions.

Data Analyst

Build a cross-brand and robust strategy of data acquisition and analytics, along with designing raw data transformation for analytical applications.

Applied Scientist

Design and build machine learning models to derive intelligence for the numerous services and products offered by the organization.

Machine Learning Engineer

With the help of several machine learning tools and technologies, build statistical models with huge chunks of business data.

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Skills to Master


Data Wrangling

Data Analysis

Prediction algorithms

Data visualization

Time Series

Machine Learning

Power BI

Advanced Statistics

Data Mining

R Programming

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Tools to Master

R excel SQL Power-BI python Knime
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Meet Your Mentors


Live Course Industry Expert Academic Faculty
  • Introduction to SQL
  • Database Normalization and Entity Relationship Model(self-paced)
  • SQL Operators
  • Working with SQL: Join, Tables, and Variables
  • Deep Dive into SQL Functions
  • Working with Subqueries
  • SQL Views, Functions, and Stored Procedures
  • Deep Dive into User-defined Functions
  • SQL Optimization and Performance
  • Advanced Topics
  • Managing Database Concurrency
  • 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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Excel Fundamentals

  • Reading the Data, Referencing in formulas , 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

Ensuring Data and File Security

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

Getting started with Macros

  • Learning about 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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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, 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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Statistics and Descriptive Analytics using MS Excel

  • Measure of central tendency, measure of spread, five points summary, etc.
  • Probability Distributions, Probability in Business Analytics
  • Probability Distributions, Binomial distribution, Poisson distribution, bayes theorem, central limit theorem.

Python for Descriptive, Diagnostic, and Inferential Statistics

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

Prescriptive Analytics

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Introduction to Machine learning

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


  • 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.


  • Introduction to classification problems, Identification of a classification problem, 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.


  • 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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Supervised Learning

  • 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.

Unsupervised Learning

  • 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.
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  • Classification reports – To evaluate the model on various metrics like recall, precision, f-support, etc.
  • Confusion matrix – To evaluate the true positive/negative, false positive/negative outcomes in the model.
  • 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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  • Regression and Multivariate Analysis 
  • Classification problems in machine learning 
  • Data Multidimensionality and Linear Algebra
  • Feature engineering and Feature selection 
  • Hyperparameter Tuning and other optimization techniques
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Business Domains – Learn about various business domains and understand how one differs from the other.

  • Finance
  • Marketing
  • Retail
  • 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:

  • Create actionable insights from raw unstructured data to solve real world business problems.
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  • Introduction to KNIME – learn about the KNIME tool that can be quite efficient for data analytics, creating workflows, etc.
  • Working with data in KNIME – Learn about creating workflows, loading datasets in KNIME, etc.
  • Loops in KNIME – Learn about the loops in KNIME that enables efficient data transformation in KNIME
  • Feature Selection, Hyperparameter optimization in KNIME – Learn about hyperparameter optimization, feature selection in KNIME that will enable efficient machine learning models.
  • Case Study: Using KNIME to create end to end machine learning models with various algorithms like linear regression, logistic regression, decision tree, random forest, etc.
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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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Power BI Basics

  • Introduction to Power BI, 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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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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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.

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.

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.)

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.

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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  • 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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  • Introduction to R
  • R Packages
  • Sorting DataFrame
  • Matrices and Vectors
  • Reading Data from External Files
  • Generating Plots
  • Analysis of Variance (ANOVA)
  • K-Means Clustering
  • Association Rule Mining
  • Regression in R
  • Analyzing Relationship with Regression
  • Advanced Regression
  • Logistic Regression
  • Advanced Logistic Regression
  • Receiver Operating Characteristic (ROC)
  • Kolmogorov–Smirnov Chart
  • Database Connectivity with R
  • Integrating R with Hadoop
  • R Case Studies
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Intellipaat reserves the right to modify, amend or change the structure of module & the curriculum, after due consensus with the university/certification partner.

Program Highlights

400 Hrs of Applied Learning
90+ Live Sessions Across 11 months
218 Hrs of Self-Paced Learning
24*7 Support


Projects will be a part of your Certification in Data Analytics to consolidate your learning. It will ensure that you have real-world experience in Data Analytics.


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Career Services By Intellipaat

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 and that will help you stay on track with your up skilling objective.


Resume & LinkedIn Profile Building

After 70% of course completion

Get assistance in creating a world-class resume and Linkedin Profile from our career services team and learn how to grab the attention of the hiring manager at 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 learners’ educational background, past experience, and future career aspirations.


3 Guaranteed Interviews

Upon movement to the Placement Pool

Guaranteed 3 job interviews upon movement to the placement pool after clearing the Placement Readiness Test ( PRT). Get interviewed by our 400+ hiring partners.


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.

Our Alumni Works At


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!


The application process consists of three simple steps. An offer of admission will be made to selected candidates based on the feedback from the interview panel. The selected candidates will be notified over email and phone, and they can block their seats through the payment of the admission fee.


Submit Application

Tell us a bit about yourself and why you want to join this program


Application Review

An admission panel will shortlist candidates based on their application



Selected candidates will be notified within 1–2 weeks

Program Fee

Total Admission Fee

$ 2,790

Apply Now

Upcoming Application Deadline 22nd June 2024

Admissions are closed once the requisite number of participants enroll for the upcoming cohort. Apply early to secure your seat.

Program Cohorts

Next Cohorts

Date Time Batch Type
Program Induction 22nd June 2024 08:00 PM - 11:00 PM IST Weekend (Sat-Sun)
Regular Classes 22nd June 2024 10:00 AM - 01:00 PM IST Weekend (Sat-Sun)

Other Cohorts

Others Cohorts

Date Time Batch Type
Program Induction 25th June 2024 07:00 AM - 09:00 AM IST Weekday (Tue-Fri)

Frequently Asked Questions

How will I receive my certificate?

After completing the Executive Post Graduate Certification Data Analytics course and completing the various projects in this program, you will receive a joint certificate from Intellipaat and iHUB DivyaSampark.

Intellipaat offers career services that include 3 guaranteed interviews for all learners enrolled in this course upon movement to the placement pool. Learners will be moved to the placement pool once they clear the PRT (Placement Readiness Test).

The Executive Post Graduate Certification Data Analytics course is delivered by leading experts from iHUB DivyaSampark and Intellipaat. They will help you gain in-depth knowledge in data analytics, apart from giving you hands-on experience in these fields through real-time projects. The top 2 performers will be given a monthly stipend, and you will also get a chance to be incubated and funded by iHub Divya Sampark.

Upon completion of the course and successful completion of assignments and projects, you will receive advanced certification in data analytics from Intellipaat and iHUB DivyaSampark, recognized by top organizations around the world. In addition, our job assistance team will prepare you for your interview by conducting multiple mock interviews, preparing your resume, and more.

From each batch, 2 candidates will get the opportunity to be shortlisted to receive a scholarship of Rs. 80,000. Candidates will have to meet certain performance criteria to get selected. The selection of candidates who receive the scholarship will be at the discretion of the iHub Divya Sampark team. All the students will be informed about the performance criteria during the tenure of the program.

All candidates who apply for this course will be eligible to receive funding and incubation support from iHub Divya Sampark. Candidates who enroll will get the chance to pitch their ideas to the iHub Divya Sampark team. Ideas that get shortlisted may receive funding up to Rs. 50 Lakhs and incubation support. 

If you are unable to attend one of the live lectures, you will receive a copy of the recorded session within the next 12 hours. If you have any further questions beyond that, you can contact our course advisors or ask them in our community.

To be included in the placement pool, the learner must complete the course and submit all projects and assignments. He/she must then pass the PRT (Placement Readiness Test) to be accepted into the placement pool and gain access to our job portal and career mentoring sessions.

You will undergo the following sessions:

  • Job search strategy sessions
  • Creation of a resume
  • Creation of a LinkedIn profile
  • Preparation for interviews by industry experts
  • Mock interviews
  • Placement opportunities with more than 400 hiring partners after passing the employment test.

Please note that the course fees is non-refundable and we will be at every step with you for your upskilling and professional growth needs.

Due to any reason you want to defer the batch or restart the classes in a new batch then you need to send the batch defer request on [email protected] and only 1 time batch defer request is allowed without any additional cost.

Learner can request for batch deferral to any of the cohorts starting in the next 3-6 months from the start date of the initial batch in which the student was originally enrolled for. Batch deferral requests are accepted only once but you should not have completed more than 20% of the program. If you want to defer the batch 2nd time then you need to pay batch defer fees which is equal to 10% of the total course fees paid for the program + Taxes.

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What is included in this course?

  • Non-biased career guidance
  • Counselling based on your skills and preference
  • No repetitive calls, only as per convenience
  • Rigorous curriculum designed by industry experts
  • Complete this program while you work