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About Data Science With SAS Certification & Training In this SAS Certification Training, you’ll become an expert in analytics techniques using the SAS data science tool. You’ll learn how to apply data manipulation and optimization techniques; advanced statistical concepts like clustering, linear regression, and decision trees; data analysis methods to solve real-world business problems and predictive modelling techniques. This SAS Certification course will give you practical knowledge you can apply on your next data analysis job. Prerequisites For Data Science With SAS Certification Course? Applicant enrol for this course have a Bachelor’s degree or its global equivalent (4-year degree, or 3-year degree). The students have basic knowledge of Computer. Let’s Know The Data Science With SAS Certification Course Objectives/ Goals? Increase your competence levels as an information security professional. Understand penetration testing and network security through the eyes of a hacker.

Course Curriculum

Course Description

  • Introduction

Analytics Overview

  • Introduction to Business Analytic
  • Types of Analyticsy
  • Areas of Analytics
  • Analytical Techniques

Introduction to SAS

  • What is SAS
  • Navigating in the SAS Console
  • SAS Language Input Files
  • Data Step
  • PROC Step and DATA Step – Example
  • DATA Step Processing
  • SAS Libraries
  • Importing & Exporting Data
  • Knowledge Pack

Combining and Modifying Datasets

  • Why Combine or Modify Data
  • Concatenating Datasets
  • Interleaving Method
  • Reading & Merging
  • Data Manipulation
  • Modifying Variable Attributes


  • What is PROC SQL
  • Retrieve Data from a Table
  • Selecting Columns in a Table
  • Retrieving Data from Multiple Tables
  • Selecting Data from Multiple Tables
  • Concatenating Query Results

SAS Macros

  • Need for SAS Macros
  • Macro Functions
  • SQL Clauses for Macross
  • The Macro Statements
  • The Conditional Statement

Basics of Statistics

  • Introduction to Statistics
  • Procedures in SAS for Descriptive Statistics
  • Hypothesis Testinge
  • Hypothesis Testing – Process
  • Parametric and Non – parametric Tests

Statistical Procedures

  • Statistical Procedures
  • PROC Means
  • Deleting Of Elements

Data Exploration

  • Data Preparation
  • Data Type Conversion
  • Character Functions
  • SCAN Function

Advanced Statistics

  • Introduction to Cluster
  • Clustering Methodologies
  • K Means Clustering
  • Decision Trees & Regression
  • Assignments