DATA SCIENCE COURSE OFFERED IN BASAVESHWAR AT BANGALORE

Data Science- SAS

Lesson 1: Analytics Overview
Definition of Analytics
Types of Analytics
Analytics Problem Types
Widely used tools and analytical techniques

Lesson 2: SAS Introduction
Introduction of GUI
Library statement, understanding of PDV
Import / Export of Data
Variable Attributes
Basic Procedures

Lesson 3: Combining/Modifying Datasets
Combining Data Sets Methods
Concatenation
Interleaving
One to One Reading
One to One Merging
Data Manipulation steps and tools

SAS Functions and Procedures for Data Manipulations

Lesson 4: PROC SQL
Introduction and Advantages
Options and Syntax - Understanding of Select Statement
Joins in SQL
Merge v/s Join

Lesson 5: SAS Macros
Need for SAS Macros
Macro Variables
Automatic Macro Variables
User-defined Macro Variables
Macro Functions
SYMBOLGEN System Option
SQL Clauses for Macros
The %Macro Statement

Lesson 6: Basic Statistics
Descriptive Statistics
Inferential Statistics
Hypothesis testing
Non parametric tests

Lesson 7: Basic Statistical Procedures
PROC UNIVARIATE
PROC MEANS
PROC FREQ
PROC CORR
PROC REG
PROC ANOVA

Lesson 8: Data Exploration
Data Preparation
Data Type Conversion
Missing Value Treatment
Summarizing Data

Lesson 9: Advanced Statistical Techniques

Clustering
Introduction
Clustering Methodology
Data Preparation
K Means Clustering
Cluster Profiling

Decision Trees
Introduction
Creating Decision Trees

Linear Regression
Introduction
Linear Regression in SAS
Diagnostics

Logistic Regression
Introduction
Logistic Regression in SAS
Diagnostics