1.1 Introductory Topics to Analytics Understanding the need for
1.1 Introductory Topics to Analytics Understanding the need for
1.2 Introduction to Data Management Properties & Types of Data,
1.3 Basics of Python Programming
Need for Python, Features of Python, Download, Setup, Installati
1.4 Data Structures in Python
Creating and Understanding Basic Data Structures in Python - Vec
1.5 Data Manipulation & Summarization in Python
Understanding how data can be summarized in different ways to do

2.1 Analytical Modeling
Understand what is Modeling and how it can be used in Various Do
2.2 Statistical Tests
P Value, Z Value, Hypothesis, Null Hypothesis, Alternative Hypot
2.3 Linear Regression Using Python
2.4 Visualization using Graphs
Creating Graph in Python and understanding which graph to be use
2.5 Missing Value and Outlier Analysis
Understanding how missing values & outliers are handled in data
2.6 Logistic Regression
Predicting Binary Outcome (Buy or not, Churn or not, Loan Defaul

3.1 Clustering
Grouping Customers based on characteristics so that they can be
3.2 Decision Trees
When to use CART & CHAID to create a decision tree based on cate
3.3 Ensembles Bagging & Boosting
Random Forest, XGBoost: Problems of Decision Tree covered in Ran

4.1 Association Rule Analysis
Understand how Association Rules can be created using Market Bas
4.2 Twitter Analysis
Configure Twitter Account & Application; Setup for downloading t