ADVANCE ANALYTICS WITH SAS SCRIPT.

  • SAS Introduction
  • Fundaments of creating Datasets
  • Create Temporary Datasets
  • Handling Missing Values
  • Define Variables Length
  • Understanding of library
  • Create Permanent Datasets
  • Creating a SAS Programs
  • Submitting SAS Program
  • Reading SAS Log
  • Browsing the Data Portion
  • Components of SAS Programs
  • List input
  • Column input
  • Formatted input
  • Column Input
  • Format Input
  • Date and Time Input
  • System Defined Formats
  • User Defined Formats
  • Numeric Formats
  • Character Formats
  • Date Formats
  • Temporary Formats
  • Permanents Formats
  • Labeling of Variable Names
  • Arithmetic Functions
  • Character Functions
  • Date Functions
  • Subsetting a SAS Data Set
  • Creating More Than One Subset Data Set in One DATA Step
  • Adding Observations to a SAS Data Set
  • Using IF-Then-Else Statement
  • Nested If Statements
  • Select and Case Statement
  • Creating Multiple Datasets
  • Proc Append
  • Proc Print
  • Proc Contents
  • Proc Means
  • Proc Sort
  • Proc Datasets
  • Proc plot
  • Proc Gplot
  • Proc Chart
  • Proc Gchart
  • Proc Summary
  • Proc Freq
  • Proc Tabulate
  • Proc Report
  • Proc Univariate
  • Numeric Functions
  • Character Functions
  • Date Functions
  • User Defined Functions
  • Computing New Variables
  • Duplicate Values
  • Sorting
  • Labelling
  • Numeric Formatting
  • Character Formatting
  • Date Formatting
  • Merge
  • Append
  • If-else statements
  • For loops
  • While loops
  • Repeat, Next, Break
  • Scatterplots, Histograms, Barcharts, Dotplots
  • Labels, Legends, Titles, Axes
  • Simple Array
  • Array with Dim Statement
  • Lower and upper bound Arrary
  • One Dimensional Array
  • Two Dimensional Array
  • Table Append using Data Steps
  • Interleave
  • Concatenation of Tables
  • Inner Join using Data Steps
  • Outer Join using Data Steps
  • Full Join using Data Steps
  • Basic SQL Commands
  • Case Statement
  • Full Joins using SQL
  • Inner Join using SQL
  • Outer Join using SQL
  • Anti Join using SQL
  • SQL to create Macro Variable
  • Rules to create Macro
  • Compilation of program
  • Creating Macro Variables
  • Call Symput and call Symget Method
  • Macro Functions
  • Debugging Options
  • Saving Macro Permanently
  • Introduction
  • Treatment of Missing Values
  • Treatment of outliers
  • Data Distribution
  • Basic Statistical Formula
  • Introduction
  • Creating Hypothesis for Test
  • Result Interpretation
  • Introduction to T-Test
  • Statistical Calculation
  • Univariate Analysis
  • One Sample T-Test
  • Two Sample T-Test
  • Paired T-TEST
  • Introduction
  • ANOVA Table & Calculations
  • One Way ANOVA
  • Two Way ANOVA
  • Multivariate ANOVA
  • Introduction
  • Calculation
  • Area of Application and Technique
  • Interpretation
  • Introduction
  • Calculations, Equation and Assumptions
  • Area of Application and Technique
  • Interpretation
  • Introduction
  • Assumptions
  • Area of Application and Methods
  • Diagnostics
  • Interpretation
  • Introduction
  • Area of Application and Methods
  • Hierarchal Clustering
  • K-Means Clustering
  • Introduction
  • Area of Applications
  • Moving Average Methods
  • ARIMA
Course Detail
Fees:
22,000

 

Class Mode:
Classroom/Online

 

Duration:
2.5 Months

 

Course Contents:
S-A-S Script, Predictive Analytics

 

Course Benefits:
STUDENT WILL ABLE TO LEARN SAS Script and apply Data Science Tecniques and methods.

 

RS 15,000

2 Months

Base S-A-S and Advance

S-A-S Script

RS 18,000

2 Months

Advance Analytics with SPSS

IBM SPSS, Predictive Analytics

KEY FEATURES

2.5 Months of Classroom Training.

 

Session have assignments and daily task.

 

Recorded Videos and presentation for reference.

Books and related data sets in form of excel and csv.

 

Interview Questions for related topic.

 

Used Case Study and Projects to understand real scenarios.

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