PG Program in Data Science and Business Analytics

Certificate from The University of Texas at Austin

PG Program in Data Science and Business Analytics

Online | 7 Months
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#2nd worldwide

Business Analytics Rankings, 2018

Why Join PGP-DSBA?

Certificate from UT Austin

Ranked #2 worldwide in Business Analytics

Rated 4.5+/5

60% career transition within 6 months of program completion

Unique Mentored Learning

Customized learning in small learning groups

Data Science and Analytics are impacting businesses worldwide and companies are on the lookout for professionals who are business ready in analytics.

The PGP-DSBA program combines the McCombs School of Business’ proven academic leadership in the field of business analytics with Great Learning’s unique mentored learning model that combines a live interactive online classroom experience, program support and career coaching to ensure successful learning outcomes. The program provides an unmatched opportunity for individuals to begin or shift their career into the exhilarating field of business analytics and data science.

PGP-DSBA is a specially designed variant for global markets of the PGP-BABI Program, India's number 1 analytics Program for the last 5 years.

Upon successful completion of the course, participants will receive a verified digital certificate from the McCombs School of Business at The University of Texas at Austin that is ranked #2 in the world for Business Analytics by the QS World University Rankings 2018.

Read more about the PGP-DSBA program on The University of Texas at Austin website: www.mccombs.utexas.edu

2nd Worldwide

Business Analytics Rankings 2018

Certificate from The University of Texas

All certificate images are for illustrative purposes only. The actual certificate may be subject to change at the discretion of the University.

KUMAR MUTHURAMAN

Faculty Director, PGP-DSBA

H. Timothy (Tim) Harkins Centennial Professor Faculty Director, Center for Research and Analytics

MS & PhD: Stanford University

Watch the video to know more about the program

Unique Mentored Learning

Personalized Attention:
Mentoring in Small Groups

Self-study online is difficult.
Our unique Mentored Learning model supports you at every step

  • 2 hours of live mentoring sessions every weekend
  • Mentors are industry experts who bring real-world insights
  • Mentors are matched to your domain and experience level
  • A passionate mentor can motivate you to learn!

Mentoring is interactive and happens in small groups

Our 400+ Mentors work at the best companies

Program Structure

A 7-month structured online program with hands-on projects and weekend mentorship sessions

Online content

Best-in-class recorded content from expert faculty and industry mentors

Hands-on projects

Practical assignments, case studies, and instructor-led practice sessions on data sets

Weekend mentoring sessions

48 hours of personalised mentorship from analytics professionals working in leading companies

Get Certificate from The University of Texas at Austin

Online Content | Weekly Mentorship

PGP-DSBA Learning Experience

Personalized learning

Each module has recorded content that is followed by a session with one of the 100+ distinguished industry mentors, in a small group of participants. These mentors are thought leaders in different domains with several years of industry experience that enables them to impart practical knowledge and real-world insights.

Industry exposure sessions

Each week, participants get access to industry videos and webinars conducted by industry experts, in addition to the usual mentoring sessions. These resources provide insights into current industry trends & real-life business problems.

Experiential learning projects

An experiential learning project at the end of every module helps candidates internalize their understanding of the content consumed. Our coursework and practical assignments are designed to enable candidates to apply what they have learned during self-study and industry sessions.

Career enhancement sessions

The program includes career development sessions which help candidates identify their strengths and empower them to clear analytics interviews. Interacting with industry practitioners provides exposure and experience that helps them in transitioning to business analytics roles.

ePortfolio

As you complete your experential projects we will automatically create a document to showcase your learning & projects in a snapshot that we call an ePortfolio. This can also be easily shared on social media channels to establish your credibility in Business Analytics with potential employers.

Curriculum

Introduction to Analytics
  • Welcome to the Program
  • Orientation ( Structure of the Program)
  • Analytics Landscape
  • Industry Session
  • Assessment 1
  • Introduction to Linear Programming
  • Sensitivity Analysis
  • Mentoring Session 1
  • Assessment 2
  • Introduction to R
  • Getting and Cleaning Data using R
  • Mentoring Session 2
  • Self Study
  • Project Brief (Twitter Data)
  • Project Submission
  • Project Debrief
  • Mentoring Session 3
Fundamentals of Business Statistics
  • Overview of the Course and Problem 2 - Brief (Continue with Twitter Data)
  • Presentation of Data
  • Measures of Central Tendency and Variation
  • Correlation
  • Industry Session
  • Self Study
  • Basic Probability Concepts
  • Probability Distribution
  • Mentoring Session 1
  • Self Study
  • Estimation
  • Hypothesis Testing
  • Mentoring Session 2
  • Self Study
  • Project Brief - Healthcare Problem
  • Project Submission
  • Project Debrief
  • Mentoring Session 3
Advanced Statistics
  • Overview of the Course and Problem 3 - Brief (Continue Healthcare Data)
  • Introduction to Regression
  • Simple Linear Regression
  • Multiple Linear Regression
  • Industry Session
  • Self Study
  • Purpose of ANOVA
  • Assumptions of ANOVA
  • One way ANOVA
  • Two way ANOVA
  • Mentoring Session 1
  • Self Study
  • Factor Analysis
  • Principal Component Method
  • Dimension Reduction Problems
  • How to Select an Analysis Method?
  • Mentoring Session 2
  • Self Study
  • Project Brief - Marketing Problem
  • Project Submission
  • Project Debrief
  • Mentoring Session 3
Machine Learning
  • Overview of the Course and Problem 4 - Brief (Continue with Marketing Problem )
  • Unsupervised Learning: Clustering
  • Unsupervised Association Rules
  • Industry Session
  • Self Study
  • Decision Tree
  • CART
  • CHAID
  • Random Forest
  • Mentoring Session 1
  • Self Study
  • Linear Discriminant Analysis
  • Quadratic Discriminant Analysis
  • SVM
  • K nodes Classification
  • Mentoring Session 2
  • Self Study
  • Project Brief - Finance Problem
  • Project Submission
  • Project Debrief
  • Mentoring Session 3
Predictive Modelling
  • Overview of the Course and Problem Brief 5 (Finance Problem)
  • Introduction to NN
  • Basic Structure
  • Application of NN
  • Industry Session
  • Self Study
  • Predictive Continuous Response
  • Non-Linear Regression 1
  • Non-Linear Regression 2
  • Non-Linear Regression 3
  • Mentoring Session 1
  • Self Study
  • Machine Learning Techniques
  • GBM
  • Model Validation
  • Model Comparison and Further Improvement
  • Mentoring Session 2
  • Self Study
  • Project Brief - Supply Chain Problem
  • Project Submission
  • Project Debrief
  • Mentoring Session 3
Data Visualization in Tableau
  • Getting started with Effective and Ineffective visual
  • Design best practices and exploratory analysis
  • Getting started and charting
  • Mapping
  • Mentoring Session 1
  • Key metrics indicator and decision triggers
  • Dashboard and storytelling with data
  • Mentoring Session 2
  • Project Brief
  • Project Submission
  • Project Debrief
  • Mentoring Session 3
Time Series Forecasting (Self-paced)
  • Overview of the course and problem brief 6 (Continue supply chain)
  • Time series analysis (Components of time series)
  • Holt-Winters Model
  • Industry session (self study)
  • Exponential Smoothing Techniques
  • Exponential Moving Average
  • Forecasting (Construction an ETS model)
  • Mentoring session - 1 (Self study)
  • Stationarity
  • Estimating ARIMA
  • SVM (Structured Break Collinearity
  • Mentoring session - 2 (Self study)
  • Project brief - Macro problem
  • Project submission
  • Project debrief
  • Mentoring session - 3
  • Project Brief
  • Project Debrief
Introduction to Big Data (Self-paced)
  • Big Data era
  • Applications: What make Big Data valuable
  • Introduction to Hadoop ecosystem
  • Map reduce
  • Programming with Spark
  • Project Brief
  • Project Debrief
Business Foundations (Self-paced)
  • Core concepts of marketing
  • Customer Life Time Value
  • Marketing metrics for CRM
  • Fundamentals of Finance
  • Working Capital Management
  • Capital Budgeting
  • Capital Structure
  • Project Brief
  • Project Debrief
Domain Exposure (Self-paced)
  • Marketing and Retail Terminologies: Review
  • CustomerAnalytics
  • KNIME
  • Retail Dashboards
  • Customer Churn
  • Association Rules Mining
  • WebAnalytics: Understanding the metrics
  • Basic & Advanced Web Metrics
  • Google Analytics: Demo & Hands on
  • CampaignAnalytics
  • Text Mining
  • Why Credit Risk-Using a market case study
  • Comparison of Credit Risk Models
  • Overview of Probability of Default (PD) Modeling
  • PD Models, types of models, steps to make a good model
  • Market Risk
  • Value at Risk- using stock case study
  • Fraud Detection
  • Introduction to Supply Chain
  • Demand uncertainty
  • Inventory Control & Management
  • Inventory classification Methods
  • Inventory Modeling (Reorder point, Safety stock)
  • Advanced Forecasting Methods
  • Procurement analytics
  • Project Brief
  • Project Debrief

Capstone - The Cornerstone

The Capstone Project is an application-oriented industry project where candidates are mentored and evaluated by Great Learning faculty and Industry Experts. It allows them to apply their learning to real life projects and add it to their portfolio as a tangible 'body of work' for potential employers to see. It is a growth enabler that instills both confidence and conviction in our candidates.

Hackathons

Participate in company sponsored hackathons and establish your expertise. Apply your new skills to solve real-world business problems. Here are some of our recent hackathons
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Hackathon: 20th Jan 2019

Real Estate

Predict the monetary value of a house using machine learning based on features of the house

40 Teams
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Hackathon: 16th Dec 2018

Inventory Management

Predict the total number of customers visiting each store of a pharmacy chain to plan inventory effectively

38 Teams
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Hackathon: 28th Oct 2018

Airline Industry

Predict the factors that will contribute to a passenger's positive in-flight experience.

27 Teams

Hands-on Projects

Work on real-world analytics projects and showcase them to potential employers through the ePortfolio

Meet Your Faculty

Meet Some of our Mentors

Learner Profiles

10000+ Learners from 17 countries across 5 continents

Batch Industry Diversity

Batch Work Experience Distribution

PGP-DSBA alumni work for world-class companies

Admission Details

Eligibility

  • done Bachelor's degree with a minimum of 50% aggregate marks or equivalent. Final year students can also apply to the program.
  • done Preference will be given to candidates with Engineering, Mathematics, Statistics, and Economics background.

Selection Process

Every year, thousands of professionals apply to the PGP-DSBA program. We believe it is our responsibility to give enough time and attention to every candidature even if it means going through hundreds of profiles to select one professional that could benefit from our program. So here is a glimpse into our rigorous selection process:
Step 1

Fill an application form

Interested candidates need to apply by filling up an Online Application Form.

Step 2

Shortlisting and Panel Review

A panel of 2 to 3 faculty members reviews every application in detail to identify candidates suitable for the program. They shortlist based on your profile – which comprises (but is not limited to) your undergraduate or bachelor’s stream, percentage, post qualification work experience, and relevance for analytics.

Step 3

Call from Program Advisor

You can expect your Program Advisor to contact you shortly to inform you about your review result. If you have been short-listed you will receive a call from your Program Advisor to schedule your interview call.

Step 4

Interview/Screening

The shortlisted candidates then go through a telephonic interview/screening. (Interview may be waived for candidates with strong profiles and experience)

Step 5

Offer Stage

After a final admissions committee and faculty review, an offer is made for a seat in the upcoming cohort of the program.

Fee Details

5,000 USD

Reach out to our Program Advisor for flexible payment options

Payments

Candidates can pay the program fee through

account_balance
Bank Transfer
credit_card
Credit/Debit Cards

Fee Includes

Tution Fee

Learning Material

Mentorship Sessions

Upcoming Application Deadline

Today

We follow a rolling admission process and admissions are closed once the requisite number of participants enroll for the upcoming batch. So, we encourage you to apply early and secure your seat.

Apply Now

Frequently Asked Questions

The McCombs School of Business at The University of Texas at Austin is ranked No. 2 in the world by QS World University Business Analytics Rankings (2018)
The PGP-DSBA curriculum has been designed in collaboration with UT Austin. The teaching and content in the program is by faculty from UT Austin, Great Learning and other practicing data scientists and analytics experts. The capstone projects are approved by UT Austin Faculty.

Upon completion, all successful participants get Certificates from The University of Texas at Austin Executive Education.
The PGP-DSBA program is unique in the following aspects:
  • Personalised mentoring and industry interaction sessions every month
  • Learning happens in micro-classes of 5 learners
  • Covers industry-relevant topics in statistics and analytics in depth
  • Provides hands-on exposure to tools such as R, Python, Tableau and Advanced Excel. Datasets are also provided
  • Experiential learning projects at the end of every module enable the candidate to apply their learning to real-world business problems
  • Interactive live sessions with industry experts and mentors provide current industry knowledge and insights
  • The online delivery model makes it convenient for working professionals to pace their learning and get doubts cleared without having to quit their jobs or travel anywhere
Participants are guided through a unique mentored learning process which happens in a micro class. These micro classes take place in a group of 5 learners which is guided by a senior industry mentor. These classes are live classes where you will have a video interaction with your mentor and other 5 learners on 3 weekends every month.
PGP-DSBA is mostly pursued by working professionals planning to make a career transition into analytics roles. We also have students in their final year of graduation benefiting from the program. Graduation in a quantitative discipline like engineering, mathematics, sciences, statistics, economics, etc, would help participants get the most out of PGP-DSBA program.
The program includes career development sessions which help candidates identify their strengths and empower them to clear analytics interviews. Interacting with industry practitioners provides exposure and experience that helps them in transitioning to business analytics roles. We also provide our candidates and alumni with access to employment opportunities that analytics companies share with us. There are many examples of participants who have completed the program taking advantage of these opportunities to move to new roles or companies in analytics.
Yes. The program is covered using recorded content delivered by academic and industry faculty and live instructor led online micro classes which happens in a batch of 5-8 learners. All assessments will also be conducted online.
Yes. Upon completion, all successful participants get Certificates from The University of Texas at Austin Executive Education.
All the requisite learning material is provided online to candidates through the Learning Management System
We believe that learning should be continuous and hence, all the learning material in terms of lectures and reading content would be available to the candidates on the LMS even after the completion of the course.
PGP-DSBA is a holistic and rigorous program and follows a continuous evaluation scheme. Quizzes, assignments, and experiential learning projects help us evaluate a candidate's understanding of the concepts learned.
We accept corporate sponsorships and can assist you with the process. For more information, you can write to us at dsba.utaustin@greatlearning.in
We provide our candidates and alumni with access to employment opportunities that analytics companies share with us. There are many examples of participants who have completed the program taking advantage of these opportunities to move to new roles or companies in analytics. Please be informed that the PGP-DSBA does not offer any formal placement process as a part of the program.
You can apply through the online application form. If you need assistance from our team, write to us at dsba.utaustin@greatlearning.in and we shall guide you through the process.
Participants do several experiential projects on Time series forecasting, Predictive modeling, Advanced statistics, Estimation & Hypothesis testing, and Data mining and a Capstone project at the end which requires candidates to use concepts learnt across all the different modules in one project.
You will need to fill up a simple online application form. The admissions committee will review all the applications and shortlist candidates based on their profiles.
Our industry mentors work with some of the leading organizations in the world like Microsoft, Google, McKinsey, Boeing, HSBC, Citi Group, etc.
Fee once received will not be refunded.
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