Enter your keyword

Post Graduate Program In Data Science Design & Visualization


A report from McKinsey forecasts that 800,000 Analytics jobs will be available in the next 5 years and only 200,000 professionals will be trained to do those jobs. This will create a vast need for trained analytics professionals in the global talent pool.

Bridge School of Management is a leader in the field of analytics education in India. Our flagship analytics program – Predictive Business Analytics (PBA) program (offered in partnership with Northwestern University School of Professional Studies, (USA) is among the top analytics programs in the country.

The Data Science and Strategic Analytics Program is a 9 month, end-to-end program offered in partnership with Northwestern University School of Professional Studies, USA. The program has been designed for working professionals and fresh graduates who intend to:

  • Enter the world of analytics
  • Use data-driven decision making in their current area of work
  • Upgrade their skills in the analytics domain

The program covers all the basics of analytics, and also provides domain-specific, application-oriented training.

To Be Announced
9 Months
Virtual learning 24×7 weekend classes
with industry facility

About Instructor

Anuj Batta

Principal Data Scientist – Matrix Nodes, Professor of Analytics and Data Science – NU Qualifications – EPBA – SDA Bocconi, EPBM – IIM Calcutta, MBA – NIMS, Jaipur, MCA – U.P. Technical University,

Ayan Dutta

Head – Portfolio & Collections Risk, Sbi Card Predictive Business Analytics Qualification:MS tat From Indian Statistical Institute, Kokata

Course Structure

The Structure of the course is as follows:-

  • The total program duration is 9 months.
  • Learning Methodology – Blended Mode with Face to Face Classes on weekends and online learning during weekdays (via advanced state-of-the-art Virtual Learning Environment (VLE).
  • Tools Covered During the program – MS Excel, R, d3.js and Tableau.

The program is designed to be delivered across four core courses along with one advanced specialization.

  • DSDV Module 1 – Database Systems and Technologies
  • DSDV Module 2 – Introduction to Data Analytics and R
  • DSDV Module 3 – Applied Analytics for Business
  • DSDV Module 4 – Data Visualization and Communication

All courses streams are compulsory and students will need to attain a passing grade in each module to ensure certification and participation in the placement.


DSDV Module 1: Database Systems and Technologies

Database systems are at the core of modern information systems. In this course, students will explore the principles of data management and data extraction. Database design, modeling, and implementation concepts will be reviewed and discussed. Students will learn how the different forms of data such as structured data in SQL databases, and unstructured data in NoSQL database systems are stored and accessed. Students will also learn how to query a database and extract useful information to support the decision making process for information design and strategy. The course has hands-on modules to provide students with SQL and NoSQL programming skills in order to extract and process data from a database engine, and present the information in forms suitable for end-users.

Session Details:

  • Session 1: Foundations for Database Systems and Information Systems
  • Session 2: Database Design and Information Analysis and Design
  • Session 3: Database Systems and Data Model
  • Session 4: Relational Database and Entity Relationship Modeling
  • Session 5: Normalization of Database Relations/Tables
  • Session 6: Structured Query Language (SQL)
  • Session 7: Designing Effective Output Reports and Data Storytelling for Business
  • Session 8: Storing and Exchanging Data (CSV, JSON, XML)
  • Session 9: Emerging Trends – Introduction to Big Data Analytics and NoSQL
  • Session 10: Business Intelligence, Data Mining, and Data Warehouses

DSDV Module 2: Introduction to Data Analytics and R

This course will introduce students to their primary tool R. It will teach them appropriate uses of analytics and define how to approach the various stakeholders within an organization with analytic information. There will be a review of the ethical, regulatory, and compliance issues related to a given business problem and/or solution. Focus will be given on interpreting performance-based organizational issues while concurrently identifying solutions. In addition, time will be spent identifying best practices to plan for engaging, implementing, and sustaining organizational changes.

Session Details:

  • Session 1: Analytics in Today’s Business World
  • Session 2: Intro to Statistics
  • Session 3: Sampling & Distributions
  • Session 4: Intro to R
  • Session 5: Using R
  • Session 6: Data
  • Session 7: Descriptive Analysis
  • Session 8: Data Distribution and Probability
  • Session 9: Opportunities and Analysis
  • Session 10: Data Collection and Preparation

DSDV Module 3: Applied Analytics for Business

Students learn to apply statistical techniques to the processing and interpretation of data from various industries and disciplines. This course introduces statistical models as they are used in predictive analytics. It addresses issues of statistical model specification and model selection, as well as best practices in developing models for management.

Session Details:

  • Session 1: Organizational Intelligence
  • Session 2: Linear Regression
  • Session 3: Linear Regression Model Validation
  • Session 4: Logistic Regression
  • Session 5: Logistic Regression Model Validation
  • Session 6: Decision Trees
  • Session 7: Advanced Decision Tree Concepts
  • Session 8: Segmentation and Clustering

DSDV Module 4: Analytics Communication & Management

This course entails learning by doing—working with data and text, utilising models of text and data, working within an open-source programming environment, and building interactive visualizations for the web. It reviews the psychology of human perception and cognition and best practices in visualization and web design. Assignments involve reviewing and developing interactive visualizations of text, time series, networks, and maps. This is a project-based course with individual and team assignments.

In addition to the core Program, Bridge School of Management will provide three free add-on modules to enable students to perform better in the job market.

1) Introduction to Advanced MS Excel

One of the key tools in the program will be the all-powerful and popular MS Excel. While R will be covered in the core program, a certain level of prerequisite knowledge in Excel is required. The module on Excel will cover all the key elements of applying MS Excel for both analytics and otherwise. This is a skill that, in itself, is useful for anyone in their current roles as well.

2) Business Communication

To help students train and groom for a successful career, we realize, soft skills are as important as knowledge in data science and analytics. This module in Business Communication covers a variety of topics related to communication, professionalism, getting your message across to groups, interviewing, presenting to groups among others.

3) Capstone Project

This project is a key part of the course and students get to use a variety of models and tools that they have learnt during the modules on a single dataset. The project is performed as a mentored class under the guidance of a faculty member.


The student will be awarded with a Certificate from Northwestern University, School of Professional Studies and Bridge School of Management. The certification will require a minimum level of academic performance and also cover areas such as attendance, discipline and adherence to school policies.

The Data Science and Strategic Analytics program aims to train students for a successful career in business analytics, across a range of functions. The hands-on program ensures end-to-end, application-oriented learning and execution of concepts essential in the industry.

Career opportunities after this program could range from (indicative, but not conclusive or limited to):

a) A descriptive analytics or diagnostic analytics (building reports and dashboards) role.

b) Role of a business analyst in a variety of product/service organisations.

c) Analytical roles in existing function/domain. For Example: Moving from a marketing role to a marketing analytics role or moving from accounting to a analytics roles within accounting function like revenue forecasting in the budgeting group.


Eligibility Criteria:

Students applying for this program can be Graduates in any discipline, with an aptitude for numbers and the willingness to learn.

Selection Process

Step 1: Candidates will have a short self-assessment quiz.

Step 2: The quiz will be followed by a personal interview with a senior member of the academic team.

Step 3: All successful candidates in Interview and Assessment quiz will be issued the Letter of Offer from the Registrar, Bridge School of Management.

Center Info

1st Floor, Tower B Infinity Towers,
DLF Cyber City
Gurgaon – 122001
Contact – 9821622722

Enquiry Now