Course Content

Introduction to Data Management
• Language of Data Analytics 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 Preperation 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
Statistics and EDA
• 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
Introduction to Predictive Analysis I
• Linear Regression Learn to implement linear regression and predict continuous data values • Supervised 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
Introduction to Predictive Analysis II
• 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 Analytics
• 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
Domain Electives**
• 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
Capstone Project
Build your expertise in one of the largest sectors in the world by taking up a 2-month capstone project.