ipl school of data science

Become a Data Driven Leader

Move from Data to Decisions

Post Graduate Program in Data Science and Business Analytics

(No prior coding experience is required)

7 Months | 7 Courses

Assignments & Capstone
Weekly Live Faculty Sessions

Unlimited Labs

Industry Projects
1:1 Coaching & Mentoring

Career Assistance

Career Labs
Hiring Talentathons

June 04, 2022

Next Cohort Starts

Program Overview

Industry recognised certification in Data Science and Business Analytics


Multiple Case Studies and Assignments | 7 Capstone Industry Projects

Team Building

Weekly Faculty Sessions - Live Online

hands on learning

Learning Library with Toolkits, Frameworks & Templates

build your idea

Focused New Age Curriculum


Unlimited 1:1 Mentorship with Mentors & Faculty


Career Assistance & Hiring Talentathons


Networking Opportunities on Campus and Off Campus

Career Labs - Career Coaching & Mentoring, Portfolio Building, Interview Preparation

Industry wants to hire professionals who not only understand the depth of data science but can leverage that to business outcomes.
atul batra
Atul Batra
CTO, Manthan Systems

Program Designed for

Career Acceleration

Unlimited Career Support

Access to multiple
job openings


Personalized Resume & LinkedIn review

Career Coaching & Mentoring

Guidance from Industry Practitioners


Career Planning & Mock Interviews

Top Skills You Will Learn

Business Problem Framing, Insight mining, Business Inferencing using statistical techniques, Business Analytics, Exploratory Data Analytics and Feature Engineering, Prescriptive & Predictive Analytics, Data Analytics with Python, Data Visualization and Storytelling.

Who Is This Program for?

Domain Experts, Engineers, Marketing and Sales Professionals, Software and IT Professionals, Project Managers, Product Managers, Business Analysts, Consultants, Entrepreneurs.

Minimum Eligibility

■ The applicant should have at least 1 year of work experience in a technical or business-related space and an undergraduate degree.
■ Prior knowledge of programming is not mandatory but preferred.

Job Opportunities

Data Analyst, Data Science Manager, Entry-level Data Scientist, Business Analyst, Technical Product Manager, Marketing Analyst, Quality Analyst.

Do you have the skills to crack a Data Science Interview?

Tools Covered


Data Analytics Certification Program

Get a certificate issued by the C. T. Bauer College of Business at the University of Houston and Institute of Product Leadership.

Bauer College’s Cyvia and Melvyn Wolff Center for Entrepreneurship ranked No. 2 in U.S. on the Top 25 Best Undergrad Programs for Entrepreneurs in 2019. (Top 10 since 2007; No. 1 in 2008, 2010 and 2011)

Course audited and approved by the Bauer College.

Preparing you for Global Certification


Data Science and Business Analytics Certification Program

Get a certificate issued by the C. T. Bauer College of Business at the University of Houston and Institute of Product Leadership.

Bauer College’s Cyvia and Melvyn Wolff Center for Entrepreneurship ranked No. 2 in U.S. on the Top 25 Best Undergrad Courses for Entrepreneurs in 2019. (Top 10 since 2007; No. 1 in 2008, 2010 and 2011)

Course audited and approved by the Bauer College.

One Program, Ten Outcomes

#1Data-led decisions
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Provide a data-driven viewpoint on strategic decisions by applying business analytics & data analytics to real-world situations
#2Data Vizualization & Storytelling
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Influence others with storytelling using data and insights
#3Business Problem Framing
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Identify, define and formulate hypotheses for key business questions that require analytics, data science to solve
#4Discover Opportunities
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Use data exploration techniques to discover new questions or opportunities within your problem area
#5Actionable Insights
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Find and analyze the patterns in business data to infer insights that influence product and service improvements
#6Models Evaluation
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Evaluate, and tune machine learning models
#7Forecast Outcomes
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Apply statistical analysis and technologies to identify trends and forecast business outcomes
#8Cost/Benefit Tradeoffs
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Make cost-effective decisions with cost-benefit analysis through business analytics
#9Persuasive Business Case
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Use data & metrics to create an irresistible quality approval case for your projects, initiatives
#10Accelerate Career
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Move faster and higher to decision making roles by differentiating yourself with data & business analytics skills

Its very simple - those with actionable skills will get promoted faster. End to End Understanding of the business context, customer context and innovation context is key for decision making senior roles.
Amit Phadnis
Chief Digital Officer, GE Healthcare


Data Science and Business Analytics Courses created and curated by industry CXOs with case studies, simulations, real-life projects, assignments and personalized coaching.

Core Courses

Course 1: DSC401F - Data Analytics Foundations

■ Descriptive Statistics & Probability
■ Inferential Statistics & Hypothesis Formulation using methods like T-test, ANOVA, Chi-Square
■ Sampling distributions, estimation
■ Simple, Multivariate regression & Time Series
■ A/B Testing
■ Goodness of Fit

Introduction to DBMS
■ ER diagram
■ Schema design
■ Key constraints & basics of normalization
■ Joins
■ Subqueries involving joins & aggregations
■ Sorting
■ Independent subqueries
■ Correlated subqueries
■ Analytic functions
■ Set operations
■ Grouping and filtering
■ SQL Aggregate & Rank Functions
■ SQL Analytics Functions

Course 2: BAN403F - Business Problem Framing

■ Understanding, Framing the Problem, and Formulating a Hypotheses
■ Asking the Right Question
■ Framework for Problem Formulation
■ Transformative Problem Formulation

■ Business Problem Solving with Data Science
■ Scoping your Solution
■ Planning the Analysis

■ What is Data Collection?
■ Sources of Data
■ Methods of Data Collection
■ Process of acquiring, collecting, extracting, and storing

Course 3: DSC402F - Data Science Techniques

■ Overview
■ What is EDA?
■ The EDA Workflow
■ Characterizing Data
■ Univariate and Multivariate Distribution Plots
■ Univariate and Multivariate Comparison Plots
■ Univariate and Multivariate Composition Plots
■ Structuring your Report
■ Extracting Features
■ Demo Principal Component Analysis
■ Factor Analysis
■ Clustering
■ Selecting Features
■ Engineering Features

■ Importing Datasets
■ Cleaning the Data (Data Wrangling)
■ Data frame manipulation. (Exploratory Data Analysis)
■ Summarizing the Data
■ Model Development & Evaluation (optional)

Course 4: DSC403F - Predictive and Prescriptive Analytics for Business Decision Making

Introduction to Time Series
■ Correlation
■ Forecasting
■ Autoregressive Moving
Average (ARMA) models
■ Autoregressive Integrated
Moving Average(ARIMA) models

■ Simple Linear Regression and Multiple Linear Regression
■ Regression Fundamentals
■ The linear regression equation
■ Linear Regression explained
■ Linear Regression with independent variable
■ Interpreting R -Squared
■ Evaluating Model Performance
■ Key assumptions of Linear Regression
■ Residual Analysis
■ Statistical tests to validate assumptions
■ Correlation and Causation
■ Heat map and Scatter plots
■ Multiple Linear Regression use case
■ Interpreting regression outputs
■ Regression use cases

Course 5: BAN401F - Visualization and Storytelling

Introduction to Data Visualization
■ Visualization in Business Analytics
■ Introduction to Tableau
■ Basic charts and dashboard
■ Descriptive Statistics, Dimensions and Measures
■ Visual analytics
■ Dashboard design & principles
■ Advanced design components/ principles: Enhancing the power of dashboards
■ Special chart types

■ The Art of Storytelling in Business Analytics & Data Science
■ Effective Data Storytelling for Business Impact
■ Storytelling and the Human Brain
■ Brining Data to Life: Emotions and Data Storytelling
■ Emotion Modulators: Color, Language and Other Design Elements
■ Story Considerations
■ Preparation of the story points
■ Setting up the story
■ Create a data story in a static presentation

Elective Courses (Optional)

Electives are recommended add-on courses for those who want to have a broader coverage

Product Analytics and Metrics

■ Product analytics definition
■ Differences between product and “classic” web analytics
■ Common questions and mistakes

■ Where, when, and how to collect data correctly
■ Data formatting and standards
■ Implications of incorrect data

■ Overview of the tools available
■ Gathering requirements and defining use cases
■ Evaluating tools for your use cases

■ Customer Acquisition Cost, Customer Lifetime Value, Churn Rate
■ Leading vs. lagging metrics
■ Benefits and drawbacks of core metrics
■ SaaS Metrics

■ How to understand users
■ Cohort creation and analysis
■ Sample user-based metrics used in product analytics

■ A selection of metrics for product analytics
■ Setting up reporting and fundamental data visualization principles
■ Setting up monitoring

Social and Web Analytics

■ Which metrics can be monitored
■ Which metrics matter and how they’re related
■ How marketing strategy or editorial decisions are effected by web data
■ Why SEO is relevant

■ Introducing: Social Media Measurement
■ Social Media Analytics: Subscribers, Engagement, Reach, Velocity and Sentiment
■ Measuring Likes and Followers and Subscribers on Facebook, Twitter, Instagram
■ What is Engagement and How to Measure Engagement on Facebook & Twitter
■ Reach – Can Actual Exposure and Reach be Measured on Facebook and Twitter?

■ Post success – impressions, reach, engagement and the difference between them.
■ Understanding Engagement – engagement metrics and how they relate to strategy.
■ Tracking and understanding audiences – who are your followers and why, what is their reach and how it affects strategy.
■ Downloading reports – how to track and measure analytics month-on-month.

■ Tweet impressions v engagement and how to track success.
■ Follower data and how to apply that to strategy.

■ Velocity in Social Media – Facebook Virality and Twitter Trends
■ Marketing Intel and Social Media Measurement: Analytics and Psychographics
■ Measuring ROI (Return on Investment) and the Ecosystem of Apps, widgets, mashups

Typical Learning Path for each course

Weekly Live Online Sessions
Plus Curated Video Lessons
Self & Group Submissions
Capstone Project
Live Presentations with Jury
Course Certificate

Average Days to complete each course

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Instructors & Mentors

Learn from India’s leading Product Practitioners.

Chief Executive Officer
Native AI
Manohar Rao
ex. Director,
RainMan Consulting
Amit Sharma
Director - Global AI Accelerator,
Yogesh K. Potdar
Executive Leader,
GE Global Research
Manjunath Subramanian
Manjunath Subramanian
Senior Principal Product Manager,
Oracle India

Industry Projects and Assignments

Learn through real-life projects and assignments across industries

Price Match Guarantee
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In this competition, you’ll apply your machine learning skills to build a model that predicts which items are the same products. Your contributions to product matching could support more accurate product categorization and uncover marketplace spam. Customers will benefit from more accurate listings of the same or similar products as they shop. Perhaps most importantly, this will aid you and your fellow shoppers in your hunt for the very best deals.
Song Popularity Challenge
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In this challenge you will use a song’s attributes to predict a track’s ‘popularity’? The better the App can quantify music, the better they can tune their systems and algorithms to generate more revenue for themselves and their stakeholders.The goal is to see whether hit songs shared similar features, and if so, whether those features could be used to predict which songs would be hits in the future.
Cab Aggregator - Supply Demand Gap
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We may have some experience of travelling to and from the airport. We have used different cab services for this travel? Did you at any time face the problem of cancellation by the driver or non-availability of cars? The aim of analysis is to identify the root cause of the problem (i.e. cancellation and non-availability of cars) and recommend ways to improve the situation. As a result of your analysis, you should be able to present to the client the root cause(s) and possible hypotheses of the problem(s) and recommend ways to improve them.
Predicting Used Car Prices
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Deciding whether a used car is worth the posted price when you see listings online can be difficult. Several factors, including mileage, make, model, year, etc. can influence the actual worth of a car. From the perspective of a seller, it is also a dilemma to price a used car appropriately. Determine whether the listed price of a used car is a challenging task, due to the many factors that drive a used vehicle’s price on the market. The focus of this project is developing machine learning models that can accurately predict the price of a used car based on its features, in order to make informed purchases.
Cab Traffic Data Visualization
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Managing traffic problems in the metro cities. Modern cities are changing. The rise of vehicular traffic has been changing the design of our cities. It is very important to know how traffic moves in a city and how it changes during different times in a week. Hence it is very important to analyse and gain insights from traffic data. The challenge is to analyse the traffic data from Bengaluru. The data gives us some information about how traffic moves from source to destination under various circumstances.
Taxi Cab Fare Prediction Machine Learning in Real Time
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Do you remember the days before Uber, Lyft, or Gett? Standing in the street trying to hail a taxi waiting for the moment a free cab might drive by and spot you? These days that world seems so far away. And you might often wonder: how do these apps work? After all, that set price is not a random guess. Given data from past rides, you are required to design the best taxi fare prediction machine learning model.
Stay Listing Price Prediction Challenge
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Predict the price of the listing. Company is an online marketplace for arranging or offering lodging, primarily homestays, or tourism experiences. Help the company’s data science team to predict prices of stay in the US based on attributes present in the dataset.
Stay Listing New User Bookings
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New users on this stay listing platform can book a place to stay in 34,000+ cities across 190+ countries. By accurately predicting where a new user will book their first travel experience, they can share more personalized content with their community, decrease the average time to first booking, and better forecast demand. In this challenge, you are given a list of users along with their demographics, web session records, and some summary statistics. You are asked to predict which country a new user's first booking destination will be. All the users in this dataset are from the USA.
Email Sentiment Analysis
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In this challenge you need to determine the emotional background for a given letter (or a set of letters?). Testing will be performed on prepared sample letters, which will be provided to the teams directly during the final presentation. The results will depend on: 1) quality of the sentiment predicted by the model for given emails (during the presentation); metric - MAE (1 - Very negative, …, 5 - Very positive) 2) idea behind the proposed method 3) quality of the presentation.
Customer Segmentation and Churn Model for Telecom
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Customer acquisition and retention is a key concern for many industries, especially acute in the strongly competitive and quick growth telecommunications industry. The primary goal of churn analysis is usually to create a list of contracts that are likely to be cancelled in the near future. The customers holding these contracts are then targeted with special incentives designed to deter cancellation.

Program Advantage

Strong hand-holding with dedicated support to guide you in your journey in Data Science and Business Analytics.

Assurance of Skills v/s Knowledge
Assurance of Skills v/s Knowledge
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Unlike eLearning and online leadership courses, our program has continuous faculty interactions with feedback on projects & 1:1 personalized coaching that will build real skills.
Expensive doesnt mean Effective
Expensive doesnt mean Effective
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Unlike Ivy League branded programs which will give you bragging rights, this will actually generate ROI and build YOUR brand.
Focussed on Career Transition
Focussed on Career Transition
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Unlike generic Executive MBA or MDP programs, focus is on building actionable skills for  senior roles in the digital economy
Learning by Doing
Learning by Doing
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Work on real world industry challenges and projects to build skills and present to hiring managers at skillathons.

Career Impact

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Average Salary Hike

Corporate Partners


Corporate Partners



Career Transitions



Highest Salary

Career Impact

Corporate Partners






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Our Students work at

Boston Consulting Group

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0% EMI

+ 8 Monthly Payments of ₹8000/mo
  • Start learning today! with a Pay as you go model

Our Students work at

Program Fee covers

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₹99000 75000
+ GST (Includes ₹30,000 Admission Fee)
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