Data science using SAS

Data Science with SAS Certification Training Course Agenda

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

Lesson 10: Working with Time series Data

• Reading Simple Time Series
• Dating time series and working with SAS date and date time values
• Sub setting data and selecting observations
• Storing time series data in SAS data sets
• Plotting, transforming, transposing, interpolating

Lesson 11: Data Optimization using SAS

• Data Optimization
• Creating optimization models commonly used in industry
• Formulating and solving a data envelopment analysis
• Solving optimization problems using the OPTMODEL procedure in SAS