Post Graduate Program in
Data Science

From

Eligibility : - Any graduate or student pursuing a technical, non-technical degree.
- No coding experience required.

Highlights of Our 10-Month Post Graduate Programs with IBM

Our Students are Placed in

Key Highlights

  • Industry recognized
    IBM badge

  • 1 day networking session with
    IBM team

  • 100+ hours of
    live classes

  • 1 on 1 mentorship from
    industry experts

  • Capstone
    Projects

  • Dedicated career
    assistance team

Who can apply
  • Any student pursuing a technical or non-technical degree
  • Graduates, freshers, IT professionals, domain experts, engineers, marketing & sales professionals
  • Software developers, project managers and professionals aiming to fast track their IT career
  • Applicants need to have knowledge of high school level mathematics, especially statistics.
  • No coding experience required
Career Prospects
  • Data Analyst
  • Business Analyst
  • Financial Analyst
  • Business Intelligence Analyst
  • Infrastructure architect
  • Business Intelligence Developer
  • Marketing Analyst
  • Quantitative analyst
  • Data Visualization Specialist.
Skills Covered
  • Deep Learning
  • Big Data & Data Mining
  • Rstudio
  • Statistics & Probability
  • Neural Network
  • Data Analysis
  • Machine Learning
  • Jupyter notebooks
  • Data Visualization
Programming Languages and Tools Covered


Detailed Curriculum in Data Science

Best-in-class content by highly experienced faculty and eminent industry leaders. Live online classes, case-studies, projects, and assignments.

This module introduces the concept of Business Analysis. It gives a glimpse of the reference architecture in Business Analytics. Build the fundamental knowledge required to use Excel spreadsheets to perform basic data analysis. IT covers the basic workings and key features of Excel to help students analyse their data.

  • Business Analytics - An Overview
  • Data Analysis with Excel – Introduction
  • Advanced Data Analysis with Excel

Descriptive Analytics is the examination of data or content, usually manually performed, to answer the question “What happened?” (or What is happening?), characterized by traditional business intelligence (BI) and visualizations such as pie charts, bar charts, line graphs, tables, or generated narratives.


This module on Data visualization is the discipline of trying to understand data by placing it in a visual context so that patterns, trends and correlations that might not otherwise be detected can be exposed. Python offers multiple great graphing libraries that come packed with lots of different features.

  • Business intelligence (Descriptive Analytics) – Introduction
  • Data Support Science
  • Building a BI Project
  • Building Reports
  • Descriptive Analytics – Case Studies on Functional Areas & Industrial Verticals
  • Data Visualization – Introduction
  • Principles of Data Visualization
  • Exploratory Data Analytics
  • Distribution and Statistical Interference
  • Visualizing Business Intelligence
  • Data Visualization using Python
  • Web Based Visualization
  • Latest and Advanced Visualization

Data mining is the process of discovering useful patterns and trends in large data sets. Predictive analytics is the process of extracting information from large datasets in order to make predictions and estimates about future outcomes.

  • Predictive analytics – Introduction
  • Data Mining
  • Data Understanding and Preparation
  • Model Development and Techniques
  • Model Evaluation and Deployment
  • Web Mining and Usage
  • Predictive Analytics - Case Studies on Functional Areas & Industrial Verticals

Big data analytics is the use of advanced analytic techniques against very large, diverse data sets that include structured, semi-structured and unstructured data, from different sources, and in different sizes from terabytes to zettabytes.

  • Introduction to Big Data Analytics
  • Hadoop
  • Query Languages for Hadoop
  • Hive & Pig: Hadoop Reporting and Analysis
  • NoSQL
  • Analytics for Big Data at Rest & in Motion
  • Bigdata Analytics - Case Studies on Functional Areas & Industrial Verticals

Social & Web analytics is the process of collecting and analyzing audience data shared on social networks to improve an organization's strategic business decisions.

  • Introduction to Web and Social Analytics
  • Relevant Data and its Collection & KPIs/ metrics
  • Manage Web and Social Media with Analytics
  • Future of Social Media Analytics and Monitoring

Projects based on challenges industries viz. Retail, Banking, Supply Chain, Healthcare, Social Media, etc.

PG program in Data Science Certification

After completing the course, get PGP Certificate from IBM.

  • IBM was ranked 8th in 50 Most Innovative Companies By BCG ,The Boston Consulting Group 2021.
  • Future-proof your career and showcase your expertise with IBM certification and specialty credentials.
Post Graduate Programme in Data Science
  • Future-proof your career and showcase your expertise with IBM certification and specialty credentials.
  • Career Services Support.
Live Interactive classes
£ 2000
Start Date : August, 2022

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Program Cohorts

Next Cohorts

Post Graduate Program in Data Science August, 2022 Cohort

1. Program Induction August, 2022 09:00 IST
2. Regular Classes August, 2022 - May, 2023 09:00 - 13:00 IST Weekend (Sat - Sun)  
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Frequently asked questions

Why should I study this postgraduate program in a data science course?

Our PG program course in partnership with IBM will fast track your career with the help of globally recognized industry certificate. Unlike the crowded space of one-sided knowledge, we offer an interactive LIVE program with IBM faculties to give you an amazing learning experience.

What certifications will I get after the data science course?

You will earn industry recognized IBM data science professional certificate.

What are the benefits of the IBM data science professional certificate?

  • All live classes taken by IBM faculties
  • Globally recognized IBM digital badge to give your career an unbeatable edge
  • Guaranteed job interview and internship with IBM for top performers in each cohort
  • Edology-IBM Award For Top Performers
  • 300+ prestigious hiring partners

What is the time commitment for the Post Graduate Program in Data Science?

4-5 hours per week for consistent 10 months

What are the prerequisites for taking this IBM Post Graduate Program in Data Science?

None. IBM shares a helpful illustrative kit to start with before the batch starts which will help you to be prepared.

What is the data science course eligibility?

  • Any graduate or student pursuing a technical or non-technical degree, with a knowledge of mathematics, especially statistics.
  • No coding experience required