SAS Training for Data Analytics and Statistical Modeling

SAS Training introduces the SAS environment for turning raw data into structured analysis, reports, and predictive models. Learn to manage datasets, apply statistical modeling techniques, create data visualizations, and interpret analytical results for business and research use cases. The curriculum focuses on the practical workflow behind data analytics, from data preparation and querying to model development and communicating findings clearly.
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SAS Training at ZeblearnIndia is supported by leading analytics firms that co‑create the learning environment. Students access licensed SAS Enterprise Guide licenses and receive quarterly webinars from partner data scientists.

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manideepak
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Hari Shankar Jha
Senior System Admin
alok kumar singh Upskilled
alok kumar singh
sap hcm
Jeevak Placed
Jeevak
Consultant
Abhijit S. Getme Upskilled
Abhijit S. Getme
Consultant Engineer
Kartik Singh Placed
Kartik Singh
SAP SD
Hemant Khainar Upskilled
Hemant Khainar
SAP MM Consultant
Neeraj Khanna Placed
Neeraj Khanna
SAP MM
Burna Vinay Kumar Placed
Burna Vinay Kumar
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Shubham Placed
Shubham
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Shashikant Career switch
Shashikant
Structure Engineer
Khushbu Career switch
Khushbu
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Curriculum

SAS Training, Data Analytics, Predictive Modeling, Statistical Modeling, Data Visualization Course Syllabus Structure

The SAS Training curriculum covers data manipulation, statistical inference, and machine learning using SAS tools. Modules include 40 hours of lab work, 12 case studies, and a final exam scored on a 100‑point scale.

Overview of SAS
  • Introduction to SAS Software
  • History and Evolution of SAS
  • Applications of SAS

  • SAS Environment
  • SAS Interface: Windows, Menus, and Commands
  • Navigating SAS Windows (Editor, Log, Output)
  • Creating and Managing SAS Programs
  • SAS Data Sets
  • Creating and Managing SAS Data Sets
  • Importing and Exporting Data
  • Using LIBNAME and DATA Statements

  • Data Manipulation
  • Data Step Processing
  • Reading and Writing Data from Various Formats
  • Conditional Processing with IF-THEN Statements

  • Data Cleaning
  • Identifying and Handling Missing Data
  • Data Transformation and Recoding
  • Using Functions for Data Manipulation
  • Descriptive Statistics
  • Summarizing Data
  • Frequency and Crosstabulation Tables
  • Descriptive Statistics Procedures (PROC MEANS, PROC FREQ)

  • Inferential Statistics
  • Hypothesis Testing
  • T-Tests, ANOVA, and Chi-Square Tests
  • Correlation and Regression Analysis
  • Advanced Statistical Procedures
  • Multivariate Analysis (Factor Analysis, Cluster Analysis)
  • Time Series Analysis
  • Survival Analysis

  • SAS Macros
  • Introduction to Macros
  • Macro Variables and Macro Programs
  • Automating Tasks with Macros

  • SAS SQL
  • Introduction to PROC SQL
  • Querying Data with SQL
  • Joining and Merging Data Sets
  • Creating Reports
  • PROC REPORT and PROC TABULATE
  • Customizing Reports with ODS (Output Delivery System)
  • Generating HTML, PDF, and RTF Reports

  • Data Visualization
  • Using PROC SGPLOT and PROC SGPANEL
  • Creating Bar Charts, Pie Charts, and Histograms
  • Advanced Graphing Techniques
  • Efficient SAS Programming
  • Best Practices for SAS Programming
  • Debugging and Error Handling
  • Optimizing SAS Code

  • SAS Functions
  • Character Functions
  • Numeric Functions
  • Date and Time Functions
  • Beyond Learning

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    SOLD OUT 30 Aug 2026 Weekend SAT - SUN (08 Weeks) 18:00 - 20:00
    FILLING FAST 4 Sep 2026 Weekday MON - FRI (08 Weeks) 08:00 - 10:00
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