SAS Training and Certification

SAS Training and Certification

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.

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

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

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Course Curriculum

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SAS Training and Certification

SELF PACED

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.

  • WEEK 5-6
  • 10 Modules
  • 6 Hours
SAS Programming And Analytics

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 Rormat.
  • 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, 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.

Program Syllabus

Curriculum

You can also view the program syllabus by downloading this program Curriculum.

Curriculum

Projects

What are the system requirements for this course?

Software requirements:- SAS University Edition can be installed on Microsoft Windows 7 or later version, Mac OS X 10.8 or later, Linux operating environment. Hardware requirements:- 64-bit hardware with a minimum of 1 GB RAM.

How will I execute the Practicals?

For executing the practicals a detailed installation guide is provided in the LMS for setting up the SAS University Edition software environment which has a lifetime validity. In case you come across any doubt, the 24*7 support team will promptly assist you.

Which Case-Studies will be part of the course?

Problem Statement:- You as ML expert have to do analysis and modeling to predict the number of shares of an article given the input parameters.

Course Description

About The Course
About the Course.
  • 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.
Objectives Of Our Online PySpark Training Course
Course Objectives. 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.
Go For Online Spark Training
Why Learn SAS?
  • The OL Tech Edu 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.
Learning With Our PySpark Certification Training
Who should go for this training?
  • 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.
Who Should Go For Our PySpark Training Course
What are the pre-requisites 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.

Course Certification

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Features

Explore step by step paths to get started on your journey to Jobs of Today and Tomorrow.

Instructor-led Sessions

30 Hours of Online Live Instructor-Led Classes.
Weekend Class : 10 sessions of 3 hours each.

Real Life Case Studies

Real-life Case Studies

Live project based on any of the selected use cases, involving implementation of the various real life solutions / services.

Assignments

Assignments

Each class will be followed by practical assignments.

24 x 7 Expert Support

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.

Certification

Certification

Towards the end of the course, OL Tech Edu certifies you for the course you had enrolled for based on the project you submit.

Course FAQ's

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