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SAS Training and Certification

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SAS Certification Training is intended to make you an expert in SAS programming and Analytics. You will be able to analyse and write SAS code for real problems, learn to use SAS to work with datasets, perform advanced statistical techniques to obtain optimized results with Advanced SAS programming.  

Why this course ?

1  SAS is a Leader in 2017 Gartner Magic Quadrant for Data Science Platform

2 Since 1976, SAS has helped customers at more than 83,000 sites make better decisions faster.

3 The average salary for a Business Intelligence Developer skilled in SAS is $100k (Payscale salary data)


  • 128K + satisfied learners. Reviews

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Course Duration

You will undergo self-paced learning where you will get an in-depth knowledge of various concepts that will be covered in the course.

Real-life Case Studies

Towards the end of the training, you will be working on a project where you will implement the techniques learnt to visualize.

Assignments

Each class has practical assignments which shall be finished before the next class and helps you to apply the concepts taught during

24 x 7 Expert Support

We have 24x7 online support team to resolve all your technical queries, through ticket based tracking system, for the lifetime.

Forum

We have a community forum for all our customers that further facilitates learning through peer interaction and knowledge

The SAS Training and Certification Course is designed to provide concept and skills of SAS Programming language, tools and several leading statistical techniques to become a successful Analytics professional. These techniques can be enforced to carry out advanced SAS programming. The course is fed with series of interactive exercises, which makes the learning more effective. This Course allows you to prepare for the below SAS certifications:

SAS Certified Base Programmer for SAS 9

SAS Certified Advanced Programmer for SAS 9

At the end of this course, you should be able to:
Perceive Analytics with SAS
Explain SAS GUI, datasets, import/export of manipulated data
Gain in-depth knowledge of integrating and refining datasets
Perform conditional and iterative looping into your SAS program
Simplify a SAS program with SAS arrays
Analyse statistics and perform advanced statistical techniques with SAS
Perform automation on complex repeated tasks using MACROS
Implement and invoke SQL queries in SAS program
Execute ODS statement with SAS 
Build and solve models using PROC OPTMODEL

  • The Avvacado Tech Info SAS training certifies you as an ‘in demand’ SAS professional, to help you grab top paying analytics job titles with hands-on skills and expertise around data mining and management concepts.
  • SAS is the primary analytics tool  used by some of the largest KPOs, Banks like American Express, Barclays etc., financial services irms like GE Money, KPOs like Genpact, TCS etc., telecom companies like Verizon (USA), consulting companies like Accenture, KPMG etc use the tool effectively.

Anyone who wants to learn programming with SAS can start right away! The course is exclusively designed for students and professionals aspiring to make a career in Data Analytics with SAS. 

SAS Developers

Analytics Professionals

Other professionals, from technology field, willing to acquire a solid foundation of this widely-used Analytical language, can also opt for this course

It would be advantageous for you to have prior programming experience and familiarity with basic concepts such as variables, flow-control, and functions along with basic knowledge of Stats. But if you have none and are motivated you will do fine.

Goal: In this module, you will learn to use the SAS Environment and program flow in SAS with specifications of Data and Proc steps. Also, you will learn to install SAS University Edition on your system.

Objective:

At the end of this module, you should be able to:

Install SAS University Edition 

Express SAS as a language

Describe the rules for the definition of SAS names

Define the different datatypes, datasets in SAS

Explain the significance of Data/Procedural step

Run a simple SAS program

Exercise better control over Data Step Programming using PDV.

Topics:

Use Cases of SAS implementation

Installing SAS University Edition

Explore SAS GUI, SAS window and its contents

Rules for definition of a SAS name

Different Datatypes in SAS

Use of Formats and Informats in SAS

Illustration of SAS Datasets

The Data step and procedural step

Creating an Instream SAS Dataset

Basic Procedural statements

Assessing Input Buffer and Program Data Vector (PDV)


Hands On:

Navigating the SAS windows environment

Nuts and bolts of SAS programming steps

Converting data as per required format

Creating a dataset using CARDS

Generating the output using PROC PRINT

Goal: This module introduces you to import datasets and control the import of datasets into SAS and ultimately concatenating them.

Objective: At the end of this module, you should be able to:

Bring in your external data into SAS and modifying it.

Describe and subset permanent datasets.

Modify/Delete existing columns

Concatenate Datasets

Topics:

Import of Data in SAS

Manipulating influx of datasets into SAS

Creating a new variable

Working with Temporary and Permanent Datasets

Set and Merge Statements

Hands On:

Demonstrating import of external data within SAS using INFILE

Demonstrating import of external data within SAS using PROC IMPORT

Creating Permanent Datasets

Performing operations with KEEP, DROP and RENAME and LABEL options

Constructing a new variable

Creating integrated datasets using SET/MERGE

Goal: This module introduces the concept of looping and its implementation in the SAS programming language. You will explore arrays and functions to simplify complications in SAS programming.

Objective: At the end of this module, you should be able to:

Demonstrate dependent and independent looping

Master data step programming with SAS functions

Simplify processing with SAS Arrays

Topics:

Conditional& Iterative Processing

SAS Arrays

Useful SAS Functions

PUT/INPUT Functions

Date/Time Functions

Numeric Functions

Character Functions

Hands On:

Use of DO, DO WHILE, DO UNTIL, IF ELSE, ELSE, ELSE IF

Demonstrate the use of arrays in SAS 

Operation with INPUT/PUT functions

Writing a Program with date/time functions

Performing programming with Numeric functions

Executing program with Character Functions

Goal: You will learn the analysis of your statistical data with advanced SAS procedures

Objective: At the end of this module, you should be able to:

Explain Statistical Procedures

Define priorities to your statistical data

Discuss statistics associated with a variable

Express correlation between two or more variables 

Topics:

Proc Dataset

Proc Format

Proc Sort

Proc Means

Proc Freq

Proc Surveyselect

Proc Transpose

Proc Summary

Proc Rank

Proc Corr

Proc Univariate

Hands On:

Obtaining statistical means of variables

Checking the degree of dependence within different variables

Generating ranks for statistical data

Performing re-structuring of data

Conducting sampling: Random and Stratified

Goal: You will learn to model estimate and classify events based on the values of dependent variables. You will be taught to perform different types of clustering methodologies to bunch your observations.

Objective: At the end of this module, you should be able to:

Define clustering and its types

Explain clustering algorithms

Nest data in different clusters 

Analyse the regression between two or multiple variables

Model and estimate an event based on Logits

Topics:

Introduction to Clustering

Hierarchical Clustering

Non-Hierarchical Clustering (K means Clustering)

Simple and Multiple Linear Regression

Logistic Regression

Hands On:

Demonstrate the use of PROC CLUSTER 

Writing a SAS advanced program with PROC FASTCLUS

Performing operations on regression with PROC REG

Demonstrate modelling using PROC LOGISTIC

Goal: You will learn to reduce the degree of complexity of a problem by developing& resolving optimization models and ultimately routing detailed presentation output from SAS in desired formats and destination. 

Objective: At the end of this module, you should be able to:

Discuss data optimization

Acquire optimized models for complex problems

Resolve optimization models

Describe the Output Delivery System in SAS

Explain the use of ODS statement for creation of different file types

Topics:

What is Data Optimization?

Realizing Optimization Models

Using Proc Optmodel

Solving the Rosenbrock Problem

Introduction to ODS

Benefits of using ODS

Generating rtf file

Generating pdf file

Generating html file

Generating doc file

Hands On:

Writing a program with PROC OPTMODEL

Solving the optimization model using SOLVE

Extracting optimized outputs 

Routing quality presentation files

Create html files

Create rtf file

Create pdf and doc files

Goal: You will learn to invoke SQL in SAS.

Objective: At the end of this module, you should be able to:

Write SQL code using various styles of the SELECT statement

Use CASE/WHEN clauses for conditionally processing the data

Systemize appearance of observations

Join data from two or more data sets

Topics:

Creating new tables

The SELECT statement

Sorting Data

The CASE expression

Other SELECT statement clauses

JOINS and UNIONS 

Hands On:

Demonstrating the SQL Procedure

Writing the SELECT clause

Application of WHERE clause

Merging Datasets

Using ORDER BY clause

Goal: You will explore how to automate a complex repeated process in SAS with the use of Macros.

Objective: At the end of this module, you should be able to:

Define Macro Concept

Automate a task that you perform repeatedly

Explain Macro Step

Express Macro step as a combination of different variables

Topics:

Introduction to Macros

Benefits of using SAS Macros

Macro Code Constituents

Macro Variables

Macro Step

Positional Parameters to Macros

Hands On:

Demonstrate the use of Macro variables in SAS

Writing a Macro code to simplify a program

Demonstrate Macro step programming

Performing Macro coding by passing parameters