SAS Certificate Training - Weekendr Bootcamps

Basic Details

When: 21st May 2017 to 24th June 2017 (10 Sessions, 4 hours each inclusive of Hands-on Project Session)

Support & Assessments: 2 Internal Assessments, 2 Doubt Sessions

Where: Weekendr Training Centre, 2230, 1st Floor, Outram Lines, Delhi (5 mins walk from Exit 2 of GTB Metro Station, Yellow Line)

Fee: Rs 14,000, 10% Group discount for a group of 3 or more

Who should attend: Anyone looking to learn SAS from scratch in a hands-on manner. We have had Bachelors, Masters students, research scholars and Working Professionals as our participants in past who have found the course quite beneficial and useful.

Course Material: Ebooks, PPT's, Handouts and Practice datasets included for a sound practical learning experience.

Why should you attend: In over 50+ Analytics (SAS, SPSS, Excel, SQL & R) engagements conducted so far in last 12 months, we have had over 950+ participants from some of the most prominent colleges and courses from Delhi University (DSE,SRCC, Stephen's, DRC, SSCBS, Miranda, Dept. of OR, Stats and many more), JNU, Jamia, Amity, Ambedkar University, IIT Delhi, Wipro etc. and working professionals from companies like American Express, RMS, Mercer Consulting, WNS, Koncept Analytics, KBR and many more with an average rating of 9/10 across all our engagements.

Prerequisites: Basic Knowledge of Statistics will be helpful

Faculty profile: Sarvesh Kumar - Certified Base Programmer for SAS 9 & SAS Faculty at Weekendr

Professional Skills:

  • Experience in Business Analysis, Creating Excel Dashboard, Business & Financial Modeling, and Data Modeling
  • Quantitative Analysis of Companies – Relative valuation, Profitability analysis, Cash flow analysis and price analysis
  • Experience in VBA Macro & Capital IQ, SAS, Business Objects XI

Field of Expertise:

  • Finance Services: - Credit Default Analysis
  • Retail Services:- Data segmentation, Sales Analysis, Customer Profile analysis, Competitors Analysis

Analytical Skills:

  • Analytical Tool: - SAS, Microsoft Excel
  • SAS Knowledge: - Base SAS, SAS Graph, SAS SQL, SAS Macro, SAS Access, SAS ODS, SAS STAT. As a SAS certified programmer, he has sound knowledge of SAS data set Creation, Manipulation, Merging, Report generation applying Statistical procedure. Good with the SAS Procedure like Proc Freq, Proc Means, Proc Reg, Proc Logistics, Proc fastclus. etc
  • Data Analysis: - Data Mining, Sampling, Segmentation, Factor Analysis, Cluster Analysis
  • Modeling Techniques: - Linear Regression Data Modeling Techniques. Logistics Data Modeling Techniques. Trend analysis

Training Experience:

  • Part of Analytics Faculty Panel at Weekendr
  • Have conducted training on Base SAS & SAS CLINICAL in GENPACT and Bank of America
  • Have conducted training on SAS Mainframe in IBM Bangalore
  • Have taken lectures In Delhi university on Base SAS as guest lecturer at Masters of Business Economics for 2009 and 2010 batches
  • Have conducted training in Apollo hospital on clinical trials of prospective studies on diabetes mellitus
  • Have trained over 500 students

Course details :

Introduction to SAS

  • Introduction
  • What is SAS ? Need for SAS ? Who uses SAS ?
  • Overview of Base SAS Software
  • Data Management Facility, Structure of SAS Dataset
  • SAS Program, Programming Language, Elements of the SAS Language
  • Rules for SAS Staements, SAS Names, Variable names, Types of SAS Variables
  • Data Analysis and reporting utilities, Traditional Output
  • Ways to run SAS Programs, SAS Windowing Environment
  • Non Interactive Mpde, Batch Mode, Interactive Line Mode
  • Running programs in SAS Windowing Environment

How SAS Works

  • Writing your first SAS Program
  • A Simple Program To Read Raw Data And Produce A Report
  • Enhancing The Program
  • More On Comment Statements, Internal Processing In SAS
  • How SAS Works - The Compilation Phase, The Execution Phase
  • Processing A Data Step: A Walkthrough
  • Creating The Input Buffer And The Program Data Vector
  • SAS Libraries, Work Library

Reading Raw Data Into SAS

  • What Is Raw Data, Definitions, Data Values, Numeric Value, Character Value
  • Standard Data, Nonstandard Data, Numeric Data, Character Data
  • Choosing An Input Style, List Input, Modified List Input, Column Input, Formatted Input, Named Input, Instream Data
  • Creating Multiple Records From Single Input Row
  • Reading Data From External Files
  • Reading Blank Separated Values (list Or Free Form Data):
  • Reading Raw Data Separated By Commas (.csv Files):, Reading In Raw Data Separated By Tabs (.txt Files):
  • Using Informats With List Input, Supplying An Informat Statement With List Input
  • Using List Input With Embedded Delimiters
  • Reading Raw Data That Are Aligned In Columns: Method 1: Column Input, Method 2: Formatted Input
  • Using More Than One Input Statement: The Single Trailing @
  • Reading Column Data That Is On More Than One Line
  • Mixed-style Input: Infile Options For Special Situations, Missover, Truncover, Pad
  • Using Lrecl To Read Very Long Lines Of Raw Data
  • Checking Your Data After It Has Been Read Into SAS

Reading Data From A Dataset

  • Introduction, Set Statement Overview
  • Automatic Variables In SAS, Interleave Multiple SAS Data Sets, Combine Multiple SAS Data Sets
  • Creating & Modifying Variable, Creating Multiple Datasets In A Single Data-step
  • Subsetting Observations, Conditional SAS Statements
  • Logical And Special Operators, The SAS Supervisor And The Set Statement
  • Efficiency And The Set Statement, Know Your Data
  • Set Statement Data Set Options, Drop And Keep Options, Rename Option
  • Firstobs And Obs Options, Where Option -, Other Set Statement Options, Nobs Option, Point Option
  • Do Loops And The Set Statement
  • Introduction To Retain Statement, Carry Over Values From One Observation To Another, Compare Values Across Observations
  • Assign Initial Values, Determining Column Order In Output Dataset, SAS System Options

Reading Data From A Dataset

  • Introduction, Set Statement Overview
  • Automatic Variables In SAS, Interleave Multiple SAS Data Sets, Combine Multiple SAS Data Sets
  • Creating & Modifying Variable, Creating Multiple Datasets In A Single Data-step
  • Subsetting Observations, Conditional SAS Statements
  • Logical And Special Operators, The SAS Supervisor And The Set Statement
  • Efficiency And The Set Statement, Know Your Data
  • Set Statement Data Set Options, Drop And Keep Options, Rename Option
  • Firstobs And Obs Options, Where Option -, Other Set Statement Options, Nobs Option, Point Option
  • Do Loops And The Set Statement
  • Introduction To Retain Statement, Carry Over Values From One Observation To Another, Compare Values Across Observations
  • Assign Initial Values, Determining Column Order In Output Dataset, SAS System Options
  • Input SAS Data Set For Example
  • Selecting Observations For A New SAS Data Set
  • Deleting Observations Based On A Condition, Accepting Observations Based On A Condition
  • Comparing The Delete And Subsetting If Statements, Methods Of Creating New Data Sets With A Subset
  • Subsetting Records From An External File With A Subsetting If Statement
  • Subsetting Observations In A Data Step With A Where Statement, Subsetting Observations In A Proc Step With A Where Statement
  • Subsetting Observations In Proc Sql, Difference Between If And Where

SAS Informats And Formats

  • Overview, Using SAS Informats
  • Input Statement, Input Function, Inputn And Inputc Functions
  • Attrib And Informat Statements
  • Using SAS Formats, Format Statement In Procedures, Put Statement, Put Function, Additional Comments

SAS Functions

  • Categories Of Functions
  • SAS Character Functions -Functions That Change The Case Of Characters - Upcase, Lowcase, Propcase
  • Functions - Miscellaneous String Functions, SAS Date And Time Functions
  • Introduction - What Is A SAS Date And Time Literal?, Date And Time Functions, Functions To Get Quarter ,year Or Day Of The Date, Functions That Work With Intervals
  • Using Formats For Date And Time, System Options Fordate And Time

An Introduction To Arrays And Array Processing

  • Why Do We Need Arrays?, Basic Array Concepts
  • Array Statement, Array References, Variable Name Array Reference
  • One Dimension Arrays, By - Group Processing, Definitions For By-group Processing, By-group Processing, By Value, By Group
  • First.variable And Last.variable - Modifying SAS Data Sets: Examples., Invoking By-group Processing
  • Preprocessing Input Data For By-group Processing, Sorting Observations For By-group Processing, Indexing For By-group Processing
  • How The Data Step Identifies By Groups, Processing Observations In A By Group, How SAS Determines First.variable And Last.variable
  • Processing By-groups In The Data Step, Overview, Processing By-groups Conditionally, Data Not In Alphabetic Or Numeric Order, Data Grouped By Formatted Values

Overview Of Methods For Combining SAS Data Sets

  • Definitions, Concatenating, Interleaving, One-to- One Reading Or One-to-one Merging, Match-merging
  • Updating, Modifying, Definitions For Reading, Combining, And Modifying SAS Data Sets
  • Reading A SAS Data Set, Combining SAS Data Sets, Modifying SAS Data Sets
  • Overview Of Tools, Reading SAS Data Sets, Reading A Single SAS Data Set, Reading From Multiple SAS Data Sets
  • Combining SAS Data Sets: Basic Concepts, One-to-one, One-to-many And Many-to-one, Many-to-many
  • Access Methods: Sequential Versus Direct, Sequential Access, Direct Access, One-to-one Reading, Data Step Processing During A One-to-one Reading
  • One-to-one Merging, Match-merging
  • Updating With The Update And The Modify Statements : Definitions, Syntax Of The Update Statement, Syntax Of The Modify Statement -
  • Updating With Nonmatched Observations, Missing Values, And New Variables - Using An Index With The Modify Statement

SAS Procedures

  • Introduction, The Proc Statement, Title And Footnote Statements, By Statement, Label Statement, Format Statement, Run Or Quit Statement
  • Description Of Data Used In Reports, SAS Reporting Procedures, Using Proc Print, Using Proc Sql, Proc Report, Procs That Summarize
  • Using Proc Chart, Using Proc Freq, Using Proc Means, Using Proc Univariate
  • Introduction To Proc Tabulate, Proc Sort, Proc Format, Proc Contents, Other Important Procs, Proc Transpose, Definitions, Proc Append
  • How To Import An Excel File Into SAS

Enhancing Your Output With Ods

  • Concepts Of The Output Delivery System
  • Tracing And Selecting Procedure Output
  • Creating SAS Data Sets From Procedure Output
  • Using Ods Statements To Create Html Output

Writing Flexible Code With The SAS Macro Facility

  • Macro Concepts, Substituting Text With Macro Variables, Creating Modular Code With Macros
  • Adding Parameters To Macros
  • Writing Macros With Conditional Logic
  • Writing Data-driven Programs With Call Symput, Debugging Macro Errors

Exporting Your Data

  • Methods For Exporting Your Data
  • Writing Raw Data Files With The Data Step

Proc Graph

  • One Dimensional Graphical Presentation Of Data With Proc Gchart
  • Two Dimensional Graphical Presentation Of Data With Proc Gplot

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SAS is back at Weekendr in an all new enhanced format. Register today! In over 50+ Analytics (SAS, SPSS, Excel, SQL & R) engagements conducted so far in last 12 months, we have had over 1000+ participants from some of the most prominent colleges and courses from Delhi University (DSE,SRCC, Stephen's, DRC, SSCBS, Miranda, Dept. of OR, Stats and many more), JNU, Jamia, Amity, Ambedkar University, IIT Delhi etc. and working professionals from companies like American Express, RMS, Mercer Consulting, WNS, Koncept Analytics, KBR, Wipro and many more with an average rating of 9/10 across all our engagements.

Click to register How to pay ?