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Advanced Certification in Data Analytics for Business

Jumpstart your career with IIT Madras & Intellipaat’s advanced certification in Data Science & Business Analytics course. Master the domain with multiple business case studies and industry-relevant projects under the guidance of the esteemed IIT Madras faculty.

Only Few Seats Left No Programming Knowledge Required

Upskill for Your Dream Job

Learning Format

Online Bootcamp

Live Classes

7 Months

Career Services

by Intellipaat

CCE IIT Madras



Hiring Partners

About Program

The program led by the IIT Madras faculty aims at helping learners develop a strong skillset including descriptive statistics, probability distributions, predictive modeling, Time Series forecasting, Data Architecture strategies, Business Analytics, and other skills to excel in this field.

Key Highlights

400 Hrs of Applied Learning
218 Hrs of Self-Paced Learning
50+ Industry Projects & Case Studies
One-on-One with Industry Mentors
24*7 Support
Soft Skills Essential Training
50+ Live sessions for a period of 7 months
Learn from IIT Madras Faculty & Industry Practitioners
Career Services by Intellipaat
3 Guaranteed Interviews by Intellipaat
Designed for Working Professionals & Fresher's
No Cost EMI Option
2 Days campus immersion at IIT Madras

Free Career Counselling

We are happy to help you 24/7

About IIT Madras Digital Skills Academy

IIT Madras Digital Skills Academy has initiated various programs in partnership with NASSCOM. The courses offered by them aim to upskill millions of students and professionals in trending technologies through a blend of theoretical and hands-on knowledge and are taught by leading academicians.

Upon Completion of this course, you will:

  • Receive an Advanced Certification in Data Analytics for Business from IIT Madras center for continuing education
  • Receive live lectured from IIT Madras Faculty & Industry Experts

Who Can Apply for the Course?

  • Individuals with a bachelor’s degree and a keen interest to learn Data Science and Business Analytics
  • IT professionals looking for a career transition to Data Scientists and Business Analysts
  • Professionals aiming to move ahead in their IT career
  • Data Science and Business Analysis professionals willing to validate and develop skills in the domain.
  • Developers and Project Managers
  • Fresher’s who aspire to build their career in the field of Business Analysis and Data Science
Who can aaply

What roles can a Data Science & Business Analysis professional 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 application.

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


Advanced Statistics

Data Mining

R Programming

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Tools to Master

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Meet Your Mentors


Live Course

Learn how to do data analysis, data transformation and other important data analysis functions. Basic fundamental of Python and learn how to do data analytics using the same.

2.1 Introduction to SQL
2.2 Database normalization
2.3 Entity-relationship model
2.4 SQL operators
2.5 Join, tables, and variables
2.6 SQL functions
2.7 Subqueries
2.8 SQL functions, views, and stored procedures
2.9 User-defined functions
2.10 SQL performance and optimization
2.11 Advanced concepts

  • Correlated subquery
  • Grouping sets

3.1 What is Data Science
Significance of Data Science in today’s data-driven world, its applications of the lifecycle, and its components Introduction to R programming and RStudio

Hands-on Exercise:
1. Installation of RStudio
2. Implementing simple mathematical operations and logic using R operators, loops, if statements, and switch cases

3.2 Data Exploration

  • Introduction to data exploration
  • Importing and exporting data to/from external sources
  • What are data exploratory analysis and data importing?
  • DataFrames, working with them, accessing individual elements, vectors, factors, operators, in-built functions, conditional and looping statements, user-defined functions, and data types

Hands-on Exercise:
1. Accessing individual elements of customer churn data
2. Modifying and extracting results from the dataset using user-defined functions in R

3.3 Data Manipulation

  • Need for data manipulation
  • Introduction to the dplyr package
  • Selecting one or more columns with select(), filtering records on the basis of a condition with filter(), adding new columns with mutate(), sampling, and counting
  • Combining different functions with the pipe operator and implementing SQL

Hands-on Exercise:
1. Implementing dplyr
2. Performing various operations for manipulating data and storing it

4.1 Descriptive Statistics

  • Mean,
  • Median,
  • Mode,
  • Tables,
  • Charts

4.2 Introduction to Probability

  • Probability in Business Analytics
  • Probability Distributions
  • Binomial distribution
  • Poisson distribution
  • Normal distribution
  • Hypothesis Testing and Estimation
  • Hypothesis testing
  • Estimation

Hands-on Exercise:
1. Building a statistical analysis model that uses quantification, representations, and experimental data
2. Reviewing, analyzing, and drawing conclusions from the data

5.1 Business domains

  • Finance
  • Marketing
  • Retail
  • Supply Chain

5.2 Understanding the business problem and formulating hypotheses
5.3 Exploratory data analysis
5.4 Data storytelling: Narrate stories in a memorable way
5.5 Project on deriving business insights and storytelling

6.1. Regression

  1. linear & logistics
  2. EDA
  3. Handling unbalanced data
  4. Dimension reduction techniques
  5. Model validation
  6. Bias variance trade-off”

6.2. Trees (Decision & Random Forest)

  1. Modeling the relationship within data using linear predictor functions
  2. Implementing linear and logistics regression in R by building a model with ‘tenure’ as the dependent variable
  3. Implementing predictive analytics by describing data
  4. Explaining the relationship between one dependent binary variable and one or more binary variables
  5. Using glm() to build a model, with ‘Churn’ as the dependent variable
  6. Implementing random forest for both regression and classification problems
  7. Building a tree, pruning it using ‘churn’ as the dependent variable, and building a random forest with the right number of trees
  8. Using ROCR for performance metrics
  9. k means clustering, Applications of Unsupervised (Market Basket Analysis, Segmentation)


  1. Deploying unsupervised learning with R to achieve clustering and dimensionality reduction
  2. K-means clustering for visualizing and interpreting results for the customer churn data
  3. Hyperparameter optimization
  4. Handling Unstructured Data
  5. Deploying association analysis as a rule-based Machine Learning method
  6. Identifying strong rules discovered in databases with measures based on interesting discoveries

7.1 Introduction to KNIME
7.2 Working with data in KNIME
7.3 Loops in KNiME
7.4 Webscraping in KNIME
7.5 Hyperparameter optimization in KNIME
7.6 Hyperparameter optimization for Machine Learning Models using loops in KNIME
7.7 Feature Selection in KNIME

8.1 Programming with R
8.2 Advance Statistics

  • Regression analysis
  • Dimension reduction techniques

8.3 Data Mining

  • Supervised and unsupervised learning
  • Clustering
  • Market Basket Analysis
  • Decision trees
  • Random forest
  • Neural networks

9.1 Multiple linear regression
9.2 Logistic regression
9.3 Linear discriminant analysis

10.1 Introduction to time-series
10.2 Correlation
10.3 Forecasting
10.4 Autoregressive models

11.1 Handling unstructured data
11.2 Machine Learning algorithms
11.3 Bias variance trade-off
11.4 Handling unbalanced data
11.5 Boosting
11.6 Model validation

12.1 Hyper parameter optimization
12.2 Advance Machine Learning Libraries – XGBoost
12.3 Solving Problems on Kaggle

13.1 Framework to Data Science strategy
13.2 Mapping Data Science with data architecture strategy
13.3 Executing Data Science strategy

14.1 Marketing & retail analytics
14.2 Social analytics
14.3 Logistics & supply chain
14.4 Financial analytics

15.1 Introduction to Power BI
15.2 Data Extraction
15.3 Data Transformation – Shaping & Combining Data
15.4 Data Modelling & DAX
15.5 Data Visualisation with analytics
15.6 Power BI Service (Cloud), Q&A, and Data Insights
15.7 Power BI Settings, Administration & Direct Connectivity
15.8 Embedded Power BI with API & Power BI
15.9 Power BI Advance & Power BI Premium

16.1 Introduction to Presto
16.2 Writing Queries in Presto on large data sets.
16.3 Data Transformation using Presto

In the Data Science & Business Analytics Capstone project, you will use all the knowledge and skills you have acquired throughout this advanced certification program and get real world Industry project exposure.

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Program Highlights

50+ Live Sessions for a period of 7 months
218 Hrs of Self-Paced Learning
30+ Industry Projects & Case Studies
24*7 Support

Interested in This Program? Secure your spot now.

The application is free and takes only 5 minutes to complete.


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

Practice 20+ Essential Tools

Designed by Industry Experts

Get Real-world Experience

Career Transition

55% Average Salary Hike

$1,20,000 Highest Salary

12000+ Career Transitions

400+ Hiring Partners

Career Transition Handbook

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 By Intellipaat

Career Services

Career Oriented Sessions

Throughout the course

Over 20+ 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 & 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

After 80% of the course completion

Guaranteed 3 job interviews upon submission of projects and assignments. 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 Work At

Master Client Desktop



Admission Details

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

Submit Application

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

Application Review

Application Review

An admission panel will shortlist candidates based on their application


Application Review

Selected candidates will be notified within 1–2 weeks

Program Fee

Total Admission Fee

$ 1,799

Upcoming Application Deadline 23rd Jan 2022

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 23rd Jan 2022 08:00 PM IST Weekend (Sat-Sun)
Regular Classes 23rd Jan 2022 08:00 PM IST Weekend (Sat-Sun)

Frequently Asked Questions

What is the ranking of IIT Madras?

IIT Madras has been ranked no.1 as per the NIRF 2020 ranking list in both the ‘overall’ and ‘engineering’ colleges category. The institute has been receiving 1st rank for 5 consecutive years.

Upon completion of the Data Science and Business Analytics training and execution of the various projects in this program, you will receive a joint Advanced Certification in Data Science and Business Analytics from Intellipaat and IIT Madras.

This certification in Data Science and Business Analytics is conducted by leading experts from IIT Madras and Intellipaat who will assist you in kick-starting your career in these domains through the vast industry-relevant experience that they carry.

Also, the course curriculum along with videos, live sessions, and assignments will help you gain in-depth knowledge in Data Science and Business Analytics, apart from providing hands-on experience in these domains through real-time projects.

If you fail to attend any of the live lectures, you will get a copy of the recorded session in the next 12 hours. Moreover, if you have any other queries, you can get in touch with our course advisors or post them on our community platform.

To register for the program, you can reach out to our learning consultants or contact us through the above-given details on this page.

There will be a 2-day campus immersion module at IIT Madras during which learners will visit the campus. You will learn from the faculty as well as interact with your peers. However, this is subject to COVID-19 situation and guidelines provided by the Institute. The cost of travel and accommodation will be borne by the learners. However, the campus immersion module is optional.

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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

I’m Interested in This Program

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