Quick Stats

Organizations rank analytics as the #1 contributing factor for a competition driven growth and survival. SAS is currently the most demnading and the widely used tool across data industry and we cater the Global SAS certification training program.

The Analytics industry is observing a steep growth while others are finding hard to survive.This is the new revolution in data science as a whole

Professionals with SAS Analytics certification make an easy platform for landing up in good role jobs. Freshers with certification are also given preference over others. Early entry in this field could take you far.

Benefits

SAS Analytics Certification

Knowledge of Data Science, Predictive Modeling, Machine Learning and Statistical Techniques algorithms with data driven approach

Real time data driven projects

Development of analytical and decision-making abilities by examining real-life case studies and coming up with strategies and decisions

Certification

Certification on SAS Analytics-Regression and Modeling is a great value-add for the student’s resume, which can help an individual pursue a promising career or a career growth

hands on model development

Industry recognized SAS Analytics-Regression and modeling certification from SAS after completion of the program.

Career Rise

Looking for switch, career growth, enhancement, upskill. This is the perfect module designed for the same. Take a step forward and be a part of the future drive

Who Should Attend

Engineering and IT Students – BTech / BE, BCA, MCA, BSc-IT, MSc-IT

Commerce & Finance Students - BCom / MCom, Economics Graduates, MBA or BBA

Highly recommended for people aspiring for jobs that required data handling – Research, Marketing, IT Services, Big Data & more

People who are already employed, but want to upskill themselves in the domain of Analytics

As a prerequisite, its just your passion towards data and hard work that is the only requirement, rest is just a cake-walk.

Course Outcome

Understanding of basic concepts and types of data
Understanding of sampling techniques
Data Science and Machine Learnig concepts with application
Understanding of frequency distributions and measures of central tendency, dispersion and shape
In Depth Knowledge of the Hypothests testing T-Test ANOVA
In depth knowledge on Correlation and Regression
In depth Knowledge of Predictive modeling using Logistic Regression
Four live projects which is full hands on real time industrial data

Curriculum

Basic Concepts

Enroll Now

Introduction to SAS tool

SAS Libraries /Temporary Library/ Permanent Library

Creating Libraries

Start with a Basic SAS programs

Data Step / Proc Step / Statements/ Global statements

Variables / Datatypes / properties of Variables
Access Data

Enroll Now

INFILE statement options to read raw data files

Creating a file refrence with filename statement

DATALINES statement with an INPUT statement
Starting With Raw Data(Basics)

Enroll Now

Styles of Input

Reading Unaligned Data / Understanding List Input

Understanding Column Input / Reading Data Aligned in Columns
Formats and Informats

Enroll Now

Standard Data/ Non Standard Data

How Informats and Format works

Working with Date/Time/Datetime informat

How and when to use Yearcutoff
Starting With Raw Data( Beyond Basics)

Enroll Now

Formatted Input style

Using Modifiers
Mixing Styles of Input

Enroll Now

Testing a Condition before Creating an Observation

Creating Multiple Observations from a Single Record

Reading Multiple Records to Create a Single Observation
PDV: How the DATA Step Works

Enroll Now

Writing Basic Data Step

How SAS Processes Programs

Compilation phase

Execution Phase

Debugging a Data Step

Testing SAS Programs
Manipulating SAS Datasets

Enroll Now

Creating & Modifying Variables

Assigning Values Conditionally

Specifying Lengths for Variables

Subsetting Data

Assigning Permanent Labels and Formats
Grouping Statements Using DO Groups

Enroll Now

Assigning Values Conditionally Using SELECT Groups

Reading a Single Data Set

Manipulating Data

Using BY-Group Processing

Reading Observations Using Direct Access (Point= option)

Detecting the End of a Data Set(end= option)

Understanding How Data Sets Are Read through PDV

Renaming Variables

Selecting Variables
Combining SAS Data Sets

Enroll Now

One-to-One Reading

Concatenating

Interleaving

Match-Merging

Match-Merge Processing

Excluding Unmatched Observations
Transforming Data with SAS Functions

Enroll Now

General Form of SAS Functions

Converting Data with Functions

Restriction for WHERE Expressions

Manipulating SAS Date Values with Functions

SAS Date and Time Values

SAS Date Functions

Modifying Character Values with Functions

Modifying Numeric Values with Functions

Nesting SAS Functions
Relevant base SAS procedures

Enroll Now

Append procedure

Sort procedure

Datasets procedure

Printto procedure

Format procedure

Transpose procedure

Import procedure

Export procedure

Print procedure

Tabulate procedure

Report procedure

Means procedure

Summary procedure

Freq procedure
Generating Data with DO Loops

Enroll Now

Constructing DO Loops

Introduction to Constructing DO Loops

DO Loop Execution

Counting Iterations of DO Loops

Decrementing DO Loops

Nesting DO Loops

Iteratively Processing Data That Is Read from a Data Set

Conditionally Executing DO Loops

Using Conditional Clauses with the Iterative DO Statement

Creating Samples
Processing Variables with Arrays

Enroll Now

Creating One-Dimensional Arrays

Understanding SAS Arrays

Defining an Array

Variable Lists as Array Elements

Referencing Elements of an Array

Compilation and Execution

Using the DIM Function in an Iterative DO Statement

Creating Variables in an ARRAY Statement

Creating Temporary Array Elements
Analytics-An Introduction

Enroll Now

What is Business Analytics

Difference between Analytics and Analysis

Importance of Analytics in Industry

Application of Analytics in Industry

Learning and the growth curve of Analytics

Puzzle

Interview Preparation
Data and Variables-An introduction

Enroll Now

What is Statististics

What is an Average- Mean Median Mode

Different types of Data and variables

Basic Statistical Measures

Puzzle

Quiz

Coding-An Introduction

Dependent and Independent Variable
Population and Sample-Sampling techniques

Enroll Now

Why do we need sample over a population

Difference between population and sample

Sampling Techniques

Simple Random Sampling

Stratified Random Sampling

Sampling with and without replacement

Puzzle

Assignment
Normal Distribution & Central Limit Theorem

Enroll Now

Introduction to Bell Curve

Deviation Vs Standard Deviation

Variance and Standard deviation

Outliers and their effects on basic statistical measures

Symmetric and Asymmetric curve

Bell Curve-Emperical Rule--Grading process

Quiz
Exploratory data Analysis

Enroll Now

Univariate anlysis vs Bivariate analysis Vs Multivariate analysis

Decile, Percentile,Vintile,Quartile,Quantile

Proc Univarite- Detailed

Moments , Basis Statistical Measures, Test for Location, Quantiles , Extreme Observation

Assignment

Puzzle
Data Visualization

Enroll Now

Box and whiskers plot

Ranking Algorithm-Proc Rank in detail

Outlier- Detection Removal Treatment

Missing values- How critical are they to a data

Missing value Removal and imputation

Proc for missing value Treatment
Hypothesis Testing

Enroll Now

Hypothests testing - What does that mean

What is Hypothesis and what we do we test

Null Hypothesis and Alternate Hypothesis

Significanace level and Confidence level- P value and α value

Decision making- Reject/Fail to Reject Null Hypothesis

Confidence Interval

Accuracy and Error

Type I Error and Type II Error
Campaign Management

Enroll Now

Test and Control group

Solicit and Non Solicit

Responder and Non Responder

Targets and Non Targets

Measuring Cost/Revenue/Profit of a campaign

2*2 profit/revenue contingency matrix

Actual Vs predicted conflicts

Accuracy Error Sensitivity Specificity

Puzzle

Interview preparation
One Sample T-Test

Enroll Now

One Sample T-test- What is the hypothsis for this test

One Sample T Test using proc ttest

One Sample T Test using proc univariate

Sides of a test- One sample- two sided, Upper tail, lower tail

How to apply T-test to the data

How will this help in making a decision

Graphical interpretation of T test

Puzzle

Assignment

Assumptions to a 1 sample T Test
Two sample T-test & Sides of a test

Enroll Now

Difference between a one sample and a two sample T-Test

Hypothesis for a T Test

Proc T Test for 2 sample T Test

Understanding the results from the statistical point of view

Plotting the graph for visulizing T-Test

Sides of 2 sample T Test-2 sided, Lower tail and upper tail

Application of 2 Sample T Test

Puzzle

Quiz

Assumptions to 2 sample T-TEst
Anova-Analysis of Variance

Enroll Now

Why do we need Anova

Why cant we use a 3 Sample T TEst

Hypothesis Testing for Anova

Assumptions to Anova

1 way Anova vs N Way Anova

Performing 2 sample T test using Anova

Coefficient of determination

Degree of Freedom

Levenes Test and F test

Interaction - Type 1 and Type III SS

Balanced Vs Unbalanced design

Proc Anova

Proc GLM

Puzzle

Interview Preparation
Anova-hPost Hoc Analysis Test

Enroll Now

Why apply Post-hoc Test when applying Anova

Controlled Design experimen

Experimental Error Rate

Multiple Comparison Test

Referential comparison

Tukey and Dunnett Test- Sides of a test

Diffogram and Control Plot

Means Vs LS Means

Puzzle

Mock Test
Correlation-Different types

Enroll Now

What is Correlation

Why do need correlation analysis in any other analysis

How to measure correlation

Pearson and Spearman Correlation

Correlation-Hypothesis Test

Proc Corr

Correlation Matrix

Correlation-graphical representation and Interpretation

Puzzle

Case Study
Regression -Exploring the algorithm

Enroll Now

Simple Linear Regression and Multiple Linear Regression

Regression-Hypothesis Testing

Degree of Freedom

Anova table for Regression

What is Ordinary least square

Parameter Estimate and Intercept

Significant and Non Significant Variables

Removing Redundancy

Collinearity- VIF

Puzzle

Assignment-Discussion
Regression - Model Building

Enroll Now

Regression- Model Building

R square and adjusted R square

2 way honest assessment

3 way honest assessment

How to split Training validation Test

Oversampling Undersampling Overfitting Underfitting

Model Selection techniques

variable selection techniques

Model building Vs Model Fitting

Model fit statistics

Puzzle

Mock Test
Logistic Regression-Introduction

Enroll Now

Logistic Regression-An Introduction

Logistic Regression-Need and the necessity

Why cant we apply regression everywhere

Algorithm to Logistic Regression

Asssumption to Logistic Regression

Checking the linearity amongst variables

Checking for collinearity

Removing Non Linearity

Logistic Regression- Hypothesis testing
Predictive modeling using Logistic Regression

Enroll Now

What are odds ratio

Odds ratio vs probability

Log odds

log Vs natural Log

Complete seperation Vs Quasi Complete Seperation

Data Convergence

Fischers Technique

Creating and identifying the dependent variable

Data preparation for model building process
Logistic Regression-Model Building

Enroll Now

Sampling data for Training Validation Test

Fine tuning Assessment and final assessment

Out of sample validation

Out of time validation

Variable transformation

Variable reduction techniques

Variable clusting techniques

Identifying Collinearity amongst variables

Interpretation of Results
Logistic Regression-Measure model performance

Enroll Now

Cumulative Lift Chart

Cumulative Gain Chart

Relative operating characteristics

Area under the curve

Model fit statistics

validation statistics

Variable selection techniques

Significant and non significant variables

Identifying the best variables for a model
Logistic Regression-Industry view and applications

Enroll Now

Model selection techniques

Parameter estimate and Intercept

% Concordant, %Discordant, %ties pairs

Calculatig C value from the statistics

Puzzle

Interview Preparation

Case study

Comparing training and validation statistics
SAS SQL 1: Essentials

Enroll Now

Introducing the Structured Query Language

Overview of the SQL procedure

Specifying columns

Specifying rows
Displaying Query Results

Enroll Now

Presenting data

Summarizing data
SQL Joins

Enroll Now

Introduction to SQL joins

Inner joins

Outer joins

Complex SQL joins
Subqueries

Enroll Now

Noncorrelated subqueries

In-line views
Set Operators

Enroll Now

Introduction to set operators

Union operator

Outer Union operator

Except operator

Intersect operator
Creating Tables and Views

Enroll Now

Creating tables with the SQL procedure

Creating views with the SQL procedure
Advanced PROC SQL Features

Enroll Now

Dictionary tables and views

Using SQL procedure options

Interfacing PROC SQL with the macro language
SAS Macro Language

Enroll Now

Introduction

Getting Familiar to the macro facility
Macro Variables

Enroll Now

Introduction to macro variables

Automatic macro variables

Macro variable references

User-defined macro variables

Delimiting macro variable references

Macro functions
Macro Definitions

Enroll Now

Defining and calling a macro

Macro parameters
DATA Step and SQL Interfaces

Enroll Now

Creating macro variables in the DATA step

Indirect references to macro variables

Creating macro variables in SQL
Macro Programs

Enroll Now

Conditional processing

Parameter validation

Iterative processing

Global and local symbol tables
Advanced SAS Programming Techniques

Enroll Now

Measuring Efficiencies
Controlling I/O Processing and Memory

Enroll Now

SAS Data step processing

Controlling I/O

Using SAS views

Reducing the length of numeric variables

Compressing SAS data sets
Accessing Observations

Enroll Now

Creating a sample data set

Creating an index

Using an index
Using DATA Step Arrays

Enroll Now

Introduction to lookup techniques

Using one-dimensional arrays

Using multidimensional arrays

Loading a multidimensional array from a SAS data set
Using DATA Step Hash and Hiter Objects

Enroll Now

Introduction

Using hash object methods

Loading a hash object with data from a SAS data set

Using the DATA step hiter object
Combining Data Horizontally

Enroll Now

DATA step merges and SQL procedure joins

Using an index to combine data

Combining summary and detail data

Combining data conditionally
Expert Programmer Techniques

Enroll Now

Creating user-defined functions

The experts’ FORMAT procedure

FAQS

Is this a module or a complete course?

This is a complete SAS certification course. Technically this is a certification course for Analytics on SAS for which we cover three modules- SAS Base Certification, SAS Analytics Certification, SAS Advance Certification

Is this a distance or online program?

This SAS certification course is an online program, available in 2 modes – Instructor-Led and self-paced. The SAS certification course is also available with classroom training in Gurgaon.

What is the difference between instructor led and self paced program?

In the self-paced programme, learners have to learn about the SAS global certification course on their own using the study materials provided to them after registration. There would be recorded videos which will be throughout this programme.

In the Instructor-led version, learners will be provided assistance by faculty who will take them through the complete course as a part of classroom/ live webinar mode.

In case if I missed a class?

Every class is recorded, and in case you miss a class you can go through the recordings and let us know if you have any doubts. You can even sit in other regular SAS certification classes at Delhi Gurgaon or Noida, for the sessions that you missed.

Is there any option of face-to-face classes?

Yes, this is a classroom programme. In case you are not able to make up for the class you can use the webex link to connect online and attend the same LIVE class without even coming to the SAS certification class.

What is the duration of Analytics program?

It is a weekend programme comprising of 130 Hours. It would take 12 weeks or 3 months to cover the SAS training course in full.

Just by spending 30 minutes a day you can become a successful SAS certified Analyst.

What is the speciality of this course?

Our Analytics on SAS certification course is aligned to current industry requirements, uses latest tools and techniques and the curriculum of the course has been developed in consultation with industry practitioners.

Which certification will I be eligible for?

You would be eligible for SAS certification exam conducted by SAS with global recognition.

We will conduct exam preparation classes in Delhi, Noida and Gurgaon for the same, and this is included as a part of this course

Does the fees also includes the SAS certification fees

The SAS certification training and preparation classes are the salient aspects of this course which is not offered anywhere but PST . We make sure that the concepts are well tutored for you to be successful in global exam.

How is this SAS certification different from the certificates provided by other institute

SAS certification is conducted by SAS and recognized globally. Upon successful completion your name appears on the website and anyone can check that. The certificates provided by local institutes ae not recognized by any organization and hence not valid anywhere

Do I have to pay the re-exam fee, if I’m unable to pass in first attempt?

We guarantee this would not be the case. Untill now there has been no case like this. But if that happens we will refund the full fees. You could be a lucky one and stand a chance for the same. You have to be amongst odd to become one of this kind.

What about the projects

The projects which are four in number are industrial projects with real time data and not the mocked one. These are not a capstone project where you actually do not get a pretty idea how things work in industry. It will be hands on and live

Global certified Analytics course