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Duration: 32 Hours

SAS is one of the world’s most widely used statistical software. With our SAS training learn how to read databases, conduct variable transformations and simple statistical analyses, and how to integrate SAS with other databases. One of our most popular courses, ATI has trained in excess of 4000 students in SAS over the last 5 years

Course Modules

  • Introduction to Analytics
  • Introduction to SAS, GUI
  • Types of Libraries, Creating
  • Variable Attributes
    • Name, Type, Format, Informat, Label
  • Introduction to Data steps and Proc steps
  • DATA Understanding
    • Reading, Importing, Exporting and Copying Data
  • Conditional Statements (Where, If, If then Else)
  • Appending, Merging and Sorting Datasets
  • Proc steps like " Proc Means, Proc Freq, Proc Sort
  • Output Delivery System (ODS)
  • SAS Functions and Options
  • List Input, Delimiters, Reading missing Values, and non standard values
  • Do loops
  • Generating Data
    • Execution
    • Output Statements
    • Nesting Do loops
    • Do While and Do Until Statement
  • Arrays
    • Dimensions
    • Array elements and Range
    • Proc report
  • Introduction to Data base, Relational Data base concepts
  • Proc SQL, Data integrity Constraints, Creating table and Inserting Values
  • Proc SQL codes to
    • Retrieve & Summarize data
    • Group, Sort & Filter
    • Using Joins
    • Indexes
  • Macros
    • Defining and calling a macro
    • Macro Parameters and Variables
    • Global and Local Variables

 

Duration: 16 Hours

Excel is by far the world’s most popular spreadsheet, useful for everything from maintaining simple household budgets to building sophisticates financial, models or designing complex dashboards. Excel in its universality is now a must have skill in every business environment. According to Microsoft Office Live Director of Marketing Michael Schultz, "roughly half a billion people use MS Office", making Excel the world’s most popular spreadsheet application by a mile.

Course Modules

  • Navigating Through Excel
    • Formatting, sorting, filter, subtotals, grouping and data validation.
  • Basic Functions
    • Text, Stat & Math Formulae and Logical
  • Advanced Functions
    • Reference " Lookups, Match and Index
    • Using Reference, Logical and Formulae functions in combination
  • Pivot Tables and Charts
    • Case Studies using Pivot Tables

Duration: 24 Hours

Dashboard reports provide Managers with information regarding the key performance indicators of the business at a glance. Excel along with VBA is a powerful tool to create these dashboards that provide analysis and insights in a timely manner.

Course Modules

  • Working with Controls
  • Command Button, Text Box and Label, Combo Box, User Forms, Scroll Bar and Check Box
  • Create a simple calculator dashboard.
  • Functions like VLOOKUP,HLOOKUP,INDEX,MATCH,OFFSET,SUBTOTAL
  • Using the above functions to make simple parts of a dashboard.
  • Using Pivot Table to make simple dashboard.
  • Dynamic Charts, Rolling Charts, Formatting Charts, Format as Table, Naming a Range
  • Introduction to VBA
    • Programming Language, VBA, OOP, Objects,
    • Data Types, Variables, Procedures & Operators
  • Recording a Macro and Editing the Macro
  • User-Defined Functions
  • Control Statements
    • If… Then
    • For… Next
    • Do Loops
  • Error Handling and Debugging
  • Worksheet and Workbook Events
  • ActiveX Controls
    • User form – Data Entry Form
    • Data entry with simple dashboard
  • Connecting Excel to Outlook & PowerPoint(Requires strong VBA skills)

Duration: 40 Hours

The Advanced Analytics course introduces participants to fundamental concepts of statistics, and guides them all the way to building predictive models using multiple linear and logistic regressions. All the topics are explained with the help of hands-on practice with live case studies and data, enabling a deeper understanding of the underlying concepts of analytics.


Course Modules

  • Introduction to analytics
    • Need for analytics
    • Analytics use in different industries
    • Challenges in adoption of analytics
    • Overview of Course Contents
  • Data understanding
    • Data types (Nominal, Ordinal, Interval and Ratio)
  • Descriptive statistics
    • Tabular & Graphical Method
    • Summary statistics
  • Introduction to some statistical terminologies and inferences
    • Population, Sample and Random variables
    • Point and Interval Estimations
    • Probability
    • Discrete/Continuous Probability Distributions
  • Hypothesis Testing
    • Importance of formulating and validating the hypothesis
    • Formulation of hypothesis (Null and alternate)
    • Testing association and differences
    • Statistical significance and test statistic
    • Level of significance
  • Z-Test, T-Test, Chi-Square test, ANOVA
  • Parametric & Non-Parametric test
  • Correlation & Regression
  • Linear Regression
    • Case Study on Multiple Regression
  • Logistic Regression
    • Case Study on Logistic Regression
  • Cluster Analysis
    • Case Study on Cluster Analysis
  • Factor Analysis
    • Case Study on Factor Analysis

Duration: 16 Hours

Fees: INR 6,000

Topics covered

Learning outcomes

   

Introduction to R

 
  • What is R?
  • Installation and using R console
  • R vs SAS
  • Data types in R
  • Data structures in R
  • Packages in R
  • Working with files

Importing and exporting csv, excel and sas files

  • Understand how R works
  • Learn most often used R syntax
  • Handling of large datasets
   

Text analytics

 
  • Tokenizing
  • Parts of speech tagging
  • Transforming text
  • Stemming
  • Building a Document-Term Matrix
  • Word Cloud
  • Project
  • What is text analytics
  • Industry applications
  • Techniques employed in text analysis
  • Hands on project to conduct sentiment analysis
   

Machine learning

 
  • Introduction to machine learning
  • Types of learning models - Decision tree learning
  • Project
  • Overview of an ML framework
  • How to build an automated system
  • Hands on project to build an automatic classifier
   

Visualization

 
  • Types of data visualization
  • Graphics capability of R
  • Generate graphics using ggplot2 package
  • Advanced charting using the googleVis package
  • Choosing the right visualization
  • Understand how R creates graphics
  • Hands on project to build an advanced dashboard.