New Batch On Data Science

Introduction to Data Science :

•  What is data science? How Data Science differ from BI and Reporting
•  Who are data scientist? What skill sets are required?
•  What are roles in a data science in project?
•  What is Analytics and Predictive Analytics?
•  Challenges in Using Predictive Analytics.

Setting Up the Problem :

•  Stages of a data science project.
•  Setting Expectation.
•  Overview with case study

Business Statistics :

•  Data types
•  Descriptive Statics

Measure of Variability:

• Histogram
•  Box Plot
•  Skewness

ANOVA :

•  Statistical test for equality of mean
•  F-distribution
•  Interview questions

R Programming :

•  R Data Types in R
•  What is R?
•  Types of objects in R – Lists, matrices, arrays, data. Frames etc.
•  Creating new variables or updating existing variables

Exploratory Data analysis and Visualization :

•  Getting data into R – reading from files
•  Importance of EDA in Data Science.
•  Exploring Numerical Data
•  Numerical Summary
•  Correlation vs causation
•  Case study and interview question

Predictive Analytics :

•  Supervised Learning
•  Simple Linear Regression.