Who should attend?

• Aspirants who want to become Business Data Visualization analysts /experts and build a strong SAS programming foundation to manipulate data, perform queries and analyses, and generate reports.
• Additionally, wants to access the power of SAS for analysis and report generation on data using the point-and-click interface.

Course Outline:

SAS Programming 1: Essentials

• Navigate the SAS windowing environment.
• Navigate the SAS Enterprise Guide programming environment.
• Read various types of data into SAS data sets.
• Create SAS variables and subset data.
• Combine SAS data sets.
• Create and enhance listing and summary reports.
• Validate SAS data sets.

SAS Programming 2: Data Manipulation Techniques

• Control SAS data set input and output.
• Combine SAS data sets.
• Summarize, read, and write different types of data.
• Perform DO loop and SAS array processing.
• Transform character, numeric, and date variables.

SAS Macro Language 1: Essentials

• Perform text substitution in SAS code
• Automate and customize the production of SAS code
• Conditionally or iteratively construct SAS code
• Use macro variables and macro functions.

SAS SQL 1: Essentials

• Query and subset data
• Summarize and present data
• Combine tables, including complex joins and merges
• Create and modify table views and indexes
• Replace multiple data and proc steps with one sql query.

SAS Programming 3: Advanced Techniques and Efficiencies

• Benchmark computer resource usage
• Control memory, i/o, and cpu resources
• Create and use indexes
• Combine data horizontally
• Use hash and hiter data step component objects and arrays as lookup tables
• Compress sas data sets
• Sample your sas data sets
• Create and use sas data views
• Safely reduce the length of numeric variables
• Create user-defined functions and informats.

Statistics 1: Introduction to ANOVA, Regression, and Logistic Regression

• Prerequisite Basic Concepts
• Introduction to Statistics
• t Tests and Analysis of Variance
• Linear Regression
• Linear Regression Diagnostics
• Categorical Data Analysis

Predictive Modeling Using Logistic Regression

• Predictive Modeling
• Fitting the Model
• Preparing the Input Variables
• Classifier Performance

The fees is inclusive of:

• Fee: ₹2,26,000/-   ₹1,30,000+GST| Duration: 136 Hours.
• Training & Digital Badge.
• Course material.
• 2 attempts of Global certification.

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