PG Diploma in Data Science

Online11 MonthsRs. 2,25,000 (Incl. Taxes)

PG Diploma from IIIT-Bangalore

Upon successful completion of the program, you will be awarded a Post Graduate Diploma Degree from IIIT-Bangalore.

Learn. Experience. Master.

For the Industry, By the Industry

Learn how Uber matches cab supply and demand, how Cognizant predicts customer churn for telecom service providers & more.


Domain Specialisation

Choose between BFS, E-commerce or Healthcare & build a resume showing expertise in one of the largest sectors in the world.


Career Guidance

Apply for suitable data analytics and Data Science profiles through our career support. Your career mentor will help you select and prepare for interviews.


Program Vitals

Course Duration

31st Oct'17 - Sept'1811 Months

Time Commitment

10 hoursper week

Program Fee

Rs. 2,25,000(Incl. taxes)Flexible EMI options

Learn from the best Data Science Leaders

This program has been designed in collaboration with some of the most influential analytics leader and top academician in data science.

Hindol Basu, Partner, Tata iQ

Hindol Basu

Partner

Tata iQ

Prof. S. Sadagopan, Director, IIIT Bangalore

Prof. S. Sadagopan

Director

S. Anand, CEO,

S. Anand

CEO

Dr. Chandrashekar Ramanatha, Associate Dean (Academics), IIIT Bangalore

Prof. R. Chandrashekar

Associate Dean (Academics)

Sameer Dhanrajani, CSO, Fractal Analytics

Sameer Dhanrajani

Chief Strategy Officer

Tricha Anjali, Associate Professor, IIIT Bangalore

Prof. Tricha Anjali

Associate Professor

Ujjyaini Mitra, Head of Analytics, Viacom 18

Ujjyaini Mitra

Head of Analytics

G Srinivasaraghavan, Professor, IIIT Bangalore

G Srinivasaraghavan

Professor

Vinit Vishal, Head - BI & Analytics, Arvind Lifestyle Brands Limited

Vinit Vishal

Sr. Manager

Dinesh Babu Jayagopi, Assistant Professor, IIIT Bangalore

Dinesh Babu Jayagopi

Assistant Professor

Kalpana Subbaramappa, Ex - AVP, Decision Sciences, GENPACT

Kalpana Subbaramappa

Ex - AVP, Decision Sciences

Anshuman Gupta, PhD, Head - Data Science Program, Cognizant Technology Solutions

Anshuman Gupta, PhD

Director - Data Science

Ankit Jain, Data Scientist, Uber

Ankit Jain

Data Scientist

Sai Alluri

Sai Alluri

PRO Analytics & Strategy Manager - Uber India

Saurabh Agarwal, Head- Information Management & Engineering, TATA IQ

Saurabh Agarwal

Head- Information Management & Engineering

TATA IQ

Shrikanth Soundurrajan, Chief Architect, InMobi

Srikanth Sundarrajan

Chief Architect



Program Syllabus

7 Courses11 Months
  • Languages of Data Science

    Learn tools and languages used for data analysis - R, Excel, SQL, Python & Tableau.These modules are also part of preparatory course

  • Introduction to Data Warehousing and OLAP

    Equip yourself with the knowledge to extract and pre-process data before analysis

  • Data Preparation

    Learn how to prepare data before you analyse them

  • Case Study- Investments

    Implement your learnings to find sectors in which different companies ought to invest

  • Data Visualization

    Make your data alive with visuals using R and tools like Tableau

  • Descriptive Statistics

    Summarize and describe data sets using a measures such as Central tendency and variability

  • Inferential Statistics

    Learn probability, Central Limit Theorem and much more to draw inferences

  • Exploratory Data Analysis

    Derive initial insights from the data using R and other visualization tools

  • Hypothesis Testing

    Understand how to formulate & test hypotheses to solve various business problems

  • Case Study- Uber Supply Demand Gap

    Apply Statistics and understand how you can solve the supply-demand gap of Uber cabs

  • Linear Regression

    Learn to implement linear regression and predict continuous data values

  • Classification

    Understand and implement algorithms like K-NN*, Naive Bayes and Logistic Regression

  • Clustering

    Learn how to create segments based on similarities using K-Means and Hierarchical clustering

  • Case Study - Telecom Churn

    Help a telecom giant predict if a customer will churn or not. Apply multiple algorithms simultaneously to see which one works the best

  • Time Series

    Learn how to make predictions using time dependent/variant data

  • Decision Trees

    Tree-based model that is simple and easy to use. Learn the fundamentals on how to implement them

  • Support Vector Machines

    Learn to classify data points using support vectors

  • Neural networks*

    Master Feed-forward, Recurrent and Gaussian Neural Networks. This is your way into AI!

  • Association Rule Mining*

    Ever wondered why beer is kept next to diaper in superstores? Find out in this module

  • Introduction to Big Data And Hadoop

    Understand the basic concepts of Big Data and Hadoop as processing platforms for Big Data

  • Managing Big Data

    Learn and Use Hadoop Ecosystem tools for data ingestion, extraction and management. Hadoop ecosystem tools namely Sqoop, Hive will be covered in this Module

  • Introduction to Spark

    Understand and use Spark, a fast Big Data processing platform

  • Big Data Analysis

    Learn how to analyze Big Data using SparkR, SparkSQL

  • BFS

    Learn Customer analytics and Risk Analytics within BFS

  • E-Commerce

    Learn customer marketing analytics and recommendations engines

  • Health Care

    Understand analytics usage in Healthcare improvement and drug discovery

Build your expertise in one of the largest sectors in the world by taking up a 2-month capstone project.

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