SlideShare a Scribd company logo
Analytics Training Institute
                                         Course Details

Statistical Analysis Software (SAS+):

Duration: 32 Hours + Practice session
Fee Structure: Rs. 10000/Ͳ (inc. of service tax of 10.3%)

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




                                  Analytics Training Institute
                                New Delhi | Hyderabad | Bengaluru
                                 Email- info@analyticstraining.in
                                     www.analyticstraining.in
Analytics Training Institute
Excel Basics:

Duration: 16 Hours + Practice session
Fee Structure: Rs. 3,500/Ͳ (inc. of service tax of 10.3%)

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


Excel Dash boarding:

Duration: 24 Hours + Practice session
Fee Structure: Rs. 8,500/Ͳ (inc. of service tax of 10.3%)
   x Working with Controls
   x Command Button, Text Box and Label, Combo Box, User Forms, Scroll Bar and Check Box
   x Create a simple calculator dashboard.
   x Functions like VLOOKUP,HLOOKUP,INDEX,MATCH,OFFSET,SUBTOTAL
   x Using the above functions to make simple parts of a dashboard.
   x Using Pivot Table to make simple dashboard.
   x Dynamic Charts, Rolling Charts, Formatting Charts, Format as Table, Naming a Range
   x Introduction to VBA
              o Programming Language, VBA, OOP, Objects,
              o Data Types, Variables, Procedures & Operators
   x Recording a Macro and Editing the Macro
   x UserͲDefined Functions
   x Control Statements
           o If… Then
           o For… Next
           o Do Loops
   x Error Handling and Debugging
   x Worksheet and Workbook Events
   x ActiveX Controls
       x User form – Data Entry Form
       x Data entry with simple dashboard
   x Connecting Excel to Outlook & PowerPoint(Requires strong VBA skills)




                                   Analytics Training Institute
                                 New Delhi | Hyderabad | Bengaluru
                                  Email- info@analyticstraining.in
                                      www.analyticstraining.in
Analytics Training Institute
Advanced Analytics (Analytics+):

Duration: 40Hours + Practice session
Fee Structure:
Tool Used SAS - Rs. 15, 000/Ͳ (inc. of service tax of 10.3%)
Other tools- Rs 12,000/ - (inc. of service tax of 10.3 %)

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




                                  Analytics Training Institute
                                New Delhi | Hyderabad | Bengaluru
                                 Email- info@analyticstraining.in
                                     www.analyticstraining.in

More Related Content

Viewers also liked

one penny doubled daily, multiplication lesson plan
one penny doubled daily, multiplication lesson planone penny doubled daily, multiplication lesson plan
one penny doubled daily, multiplication lesson plan
Houdini Howard
 
interactive education website review
interactive education website reviewinteractive education website review
interactive education website reviewHoudini Howard
 
European Recruitment
European RecruitmentEuropean Recruitment
European Recruitment
gturok
 
How to Start Up in 1 Hour
How to Start Up in 1 HourHow to Start Up in 1 Hour
How to Start Up in 1 Hour
Susie Pan
 
C aptitude 1st jan 2012
C aptitude 1st jan 2012C aptitude 1st jan 2012
C aptitude 1st jan 2012
Kishor Parkhe
 
Life Goes on After Shad
Life Goes on After ShadLife Goes on After Shad
Life Goes on After Shad
Susie Pan
 
How to make a Glog with Glogster, tutorial
How to make a Glog with Glogster, tutorialHow to make a Glog with Glogster, tutorial
How to make a Glog with Glogster, tutorial
Houdini Howard
 
How To Surround Yourself with the Right People
How To Surround Yourself with the Right PeopleHow To Surround Yourself with the Right People
How To Surround Yourself with the Right People
Susie Pan
 
Big data and hadoop
Big data and hadoopBig data and hadoop
Big data and hadoop
Kishor Parkhe
 
การป้องกันและระบบความปลอดภัย
การป้องกันและระบบความปลอดภัยการป้องกันและระบบความปลอดภัย
การป้องกันและระบบความปลอดภัย
Kinko Rhino
 
Redis
RedisRedis
Mongo db basic installation
Mongo db basic installationMongo db basic installation
Mongo db basic installation
Kishor Parkhe
 
Getting started with replica set in MongoDB
Getting started with replica set in MongoDBGetting started with replica set in MongoDB
Getting started with replica set in MongoDBKishor Parkhe
 
Aggregation in MongoDB
Aggregation in MongoDBAggregation in MongoDB
Aggregation in MongoDBKishor Parkhe
 
Adolescent decision making
Adolescent decision makingAdolescent decision making
Adolescent decision makingHoudini Howard
 
Alloy in fix prosthodontics
Alloy in fix prosthodonticsAlloy in fix prosthodontics
Alloy in fix prosthodontics
piroozgiv
 

Viewers also liked (18)

one penny doubled daily, multiplication lesson plan
one penny doubled daily, multiplication lesson planone penny doubled daily, multiplication lesson plan
one penny doubled daily, multiplication lesson plan
 
interactive education website review
interactive education website reviewinteractive education website review
interactive education website review
 
European Recruitment
European RecruitmentEuropean Recruitment
European Recruitment
 
How to Start Up in 1 Hour
How to Start Up in 1 HourHow to Start Up in 1 Hour
How to Start Up in 1 Hour
 
C aptitude 1st jan 2012
C aptitude 1st jan 2012C aptitude 1st jan 2012
C aptitude 1st jan 2012
 
Life Goes on After Shad
Life Goes on After ShadLife Goes on After Shad
Life Goes on After Shad
 
How to make a Glog with Glogster, tutorial
How to make a Glog with Glogster, tutorialHow to make a Glog with Glogster, tutorial
How to make a Glog with Glogster, tutorial
 
How To Surround Yourself with the Right People
How To Surround Yourself with the Right PeopleHow To Surround Yourself with the Right People
How To Surround Yourself with the Right People
 
Big data and hadoop
Big data and hadoopBig data and hadoop
Big data and hadoop
 
การป้องกันและระบบความปลอดภัย
การป้องกันและระบบความปลอดภัยการป้องกันและระบบความปลอดภัย
การป้องกันและระบบความปลอดภัย
 
Redis
RedisRedis
Redis
 
Mongo db basic installation
Mongo db basic installationMongo db basic installation
Mongo db basic installation
 
Getting started with replica set in MongoDB
Getting started with replica set in MongoDBGetting started with replica set in MongoDB
Getting started with replica set in MongoDB
 
Aggregation in MongoDB
Aggregation in MongoDBAggregation in MongoDB
Aggregation in MongoDB
 
Indexing In MongoDB
Indexing In MongoDBIndexing In MongoDB
Indexing In MongoDB
 
Adolescent decision making
Adolescent decision makingAdolescent decision making
Adolescent decision making
 
G tube training
G tube trainingG tube training
G tube training
 
Alloy in fix prosthodontics
Alloy in fix prosthodonticsAlloy in fix prosthodontics
Alloy in fix prosthodontics
 

Similar to Ati course contents

Introduction to Machine Learning with SciKit-Learn
Introduction to Machine Learning with SciKit-LearnIntroduction to Machine Learning with SciKit-Learn
Introduction to Machine Learning with SciKit-Learn
Benjamin Bengfort
 
The Machine Learning Workflow with Azure
The Machine Learning Workflow with AzureThe Machine Learning Workflow with Azure
The Machine Learning Workflow with Azure
Ivo Andreev
 
Predicting Employee Attrition
Predicting Employee AttritionPredicting Employee Attrition
Predicting Employee Attrition
Shruti Mohan
 
Predictive modeling
Predictive modelingPredictive modeling
Predictive modeling
Prashant Mudgal
 
EE-232-LEC-01 Data_structures.pptx
EE-232-LEC-01 Data_structures.pptxEE-232-LEC-01 Data_structures.pptx
EE-232-LEC-01 Data_structures.pptx
iamultapromax
 
Week_1 Machine Learning introduction.pptx
Week_1 Machine Learning introduction.pptxWeek_1 Machine Learning introduction.pptx
Week_1 Machine Learning introduction.pptx
muhammadsamroz
 
Data analysis
Data analysisData analysis
Data analysis
AnandDesshpande
 
Data analytcis-first-steps
Data analytcis-first-stepsData analytcis-first-steps
Data analytcis-first-steps
Shesha R
 
Challenges in business analytics
Challenges in business analyticsChallenges in business analytics
Challenges in business analytics
Miklos Koren
 
Workshop nwav 47 - LVS - Tool for Quantitative Data Analysis
Workshop nwav 47 - LVS - Tool for Quantitative Data AnalysisWorkshop nwav 47 - LVS - Tool for Quantitative Data Analysis
Workshop nwav 47 - LVS - Tool for Quantitative Data Analysis
Olga Scrivner
 
Azure Databricks for Data Scientists
Azure Databricks for Data ScientistsAzure Databricks for Data Scientists
Azure Databricks for Data Scientists
Richard Garris
 
Machine Learning - Simple Linear Regression
Machine Learning - Simple Linear RegressionMachine Learning - Simple Linear Regression
Machine Learning - Simple Linear Regression
Siddharth Shrivastava
 
Barga Data Science lecture 8
Barga Data Science lecture 8Barga Data Science lecture 8
Barga Data Science lecture 8
Roger Barga
 
Data Analytics with R and SQL Server
Data Analytics with R and SQL ServerData Analytics with R and SQL Server
Data Analytics with R and SQL Server
Stéphane Fréchette
 
Machine Learning Notes for beginners ,Step by step
Machine Learning Notes for beginners ,Step by stepMachine Learning Notes for beginners ,Step by step
Machine Learning Notes for beginners ,Step by step
SanjanaSaxena17
 
1440 track 2 boire_using our laptop
1440 track 2 boire_using our laptop1440 track 2 boire_using our laptop
1440 track 2 boire_using our laptop
Rising Media, Inc.
 
Data Science for Dummies - Data Engineering with Titanic dataset + Databricks...
Data Science for Dummies - Data Engineering with Titanic dataset + Databricks...Data Science for Dummies - Data Engineering with Titanic dataset + Databricks...
Data Science for Dummies - Data Engineering with Titanic dataset + Databricks...
Rodney Joyce
 
Feature Engineering - Getting most out of data for predictive models - TDC 2017
Feature Engineering - Getting most out of data for predictive models - TDC 2017Feature Engineering - Getting most out of data for predictive models - TDC 2017
Feature Engineering - Getting most out of data for predictive models - TDC 2017
Gabriel Moreira
 
Keynote at IWLS 2017
Keynote at IWLS 2017Keynote at IWLS 2017
Keynote at IWLS 2017
Manish Pandey
 

Similar to Ati course contents (20)

Introduction to Machine Learning with SciKit-Learn
Introduction to Machine Learning with SciKit-LearnIntroduction to Machine Learning with SciKit-Learn
Introduction to Machine Learning with SciKit-Learn
 
The Machine Learning Workflow with Azure
The Machine Learning Workflow with AzureThe Machine Learning Workflow with Azure
The Machine Learning Workflow with Azure
 
Predicting Employee Attrition
Predicting Employee AttritionPredicting Employee Attrition
Predicting Employee Attrition
 
Predictive modeling
Predictive modelingPredictive modeling
Predictive modeling
 
EE-232-LEC-01 Data_structures.pptx
EE-232-LEC-01 Data_structures.pptxEE-232-LEC-01 Data_structures.pptx
EE-232-LEC-01 Data_structures.pptx
 
Week_1 Machine Learning introduction.pptx
Week_1 Machine Learning introduction.pptxWeek_1 Machine Learning introduction.pptx
Week_1 Machine Learning introduction.pptx
 
Data analysis
Data analysisData analysis
Data analysis
 
Data analytcis-first-steps
Data analytcis-first-stepsData analytcis-first-steps
Data analytcis-first-steps
 
Challenges in business analytics
Challenges in business analyticsChallenges in business analytics
Challenges in business analytics
 
Workshop nwav 47 - LVS - Tool for Quantitative Data Analysis
Workshop nwav 47 - LVS - Tool for Quantitative Data AnalysisWorkshop nwav 47 - LVS - Tool for Quantitative Data Analysis
Workshop nwav 47 - LVS - Tool for Quantitative Data Analysis
 
Azure Databricks for Data Scientists
Azure Databricks for Data ScientistsAzure Databricks for Data Scientists
Azure Databricks for Data Scientists
 
Machine Learning - Simple Linear Regression
Machine Learning - Simple Linear RegressionMachine Learning - Simple Linear Regression
Machine Learning - Simple Linear Regression
 
Barga Data Science lecture 8
Barga Data Science lecture 8Barga Data Science lecture 8
Barga Data Science lecture 8
 
Data Analytics with R and SQL Server
Data Analytics with R and SQL ServerData Analytics with R and SQL Server
Data Analytics with R and SQL Server
 
Machine Learning Notes for beginners ,Step by step
Machine Learning Notes for beginners ,Step by stepMachine Learning Notes for beginners ,Step by step
Machine Learning Notes for beginners ,Step by step
 
1440 track 2 boire_using our laptop
1440 track 2 boire_using our laptop1440 track 2 boire_using our laptop
1440 track 2 boire_using our laptop
 
Data Science for Dummies - Data Engineering with Titanic dataset + Databricks...
Data Science for Dummies - Data Engineering with Titanic dataset + Databricks...Data Science for Dummies - Data Engineering with Titanic dataset + Databricks...
Data Science for Dummies - Data Engineering with Titanic dataset + Databricks...
 
Feature Engineering - Getting most out of data for predictive models - TDC 2017
Feature Engineering - Getting most out of data for predictive models - TDC 2017Feature Engineering - Getting most out of data for predictive models - TDC 2017
Feature Engineering - Getting most out of data for predictive models - TDC 2017
 
An introduction to R
An introduction to RAn introduction to R
An introduction to R
 
Keynote at IWLS 2017
Keynote at IWLS 2017Keynote at IWLS 2017
Keynote at IWLS 2017
 

Recently uploaded

How world-class product teams are winning in the AI era by CEO and Founder, P...
How world-class product teams are winning in the AI era by CEO and Founder, P...How world-class product teams are winning in the AI era by CEO and Founder, P...
How world-class product teams are winning in the AI era by CEO and Founder, P...
Product School
 
Introduction to CHERI technology - Cybersecurity
Introduction to CHERI technology - CybersecurityIntroduction to CHERI technology - Cybersecurity
Introduction to CHERI technology - Cybersecurity
mikeeftimakis1
 
PHP Frameworks: I want to break free (IPC Berlin 2024)
PHP Frameworks: I want to break free (IPC Berlin 2024)PHP Frameworks: I want to break free (IPC Berlin 2024)
PHP Frameworks: I want to break free (IPC Berlin 2024)
Ralf Eggert
 
Welocme to ViralQR, your best QR code generator.
Welocme to ViralQR, your best QR code generator.Welocme to ViralQR, your best QR code generator.
Welocme to ViralQR, your best QR code generator.
ViralQR
 
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdfSmart TV Buyer Insights Survey 2024 by 91mobiles.pdf
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf
91mobiles
 
GenAISummit 2024 May 28 Sri Ambati Keynote: AGI Belongs to The Community in O...
GenAISummit 2024 May 28 Sri Ambati Keynote: AGI Belongs to The Community in O...GenAISummit 2024 May 28 Sri Ambati Keynote: AGI Belongs to The Community in O...
GenAISummit 2024 May 28 Sri Ambati Keynote: AGI Belongs to The Community in O...
Sri Ambati
 
The Future of Platform Engineering
The Future of Platform EngineeringThe Future of Platform Engineering
The Future of Platform Engineering
Jemma Hussein Allen
 
The Art of the Pitch: WordPress Relationships and Sales
The Art of the Pitch: WordPress Relationships and SalesThe Art of the Pitch: WordPress Relationships and Sales
The Art of the Pitch: WordPress Relationships and Sales
Laura Byrne
 
Free Complete Python - A step towards Data Science
Free Complete Python - A step towards Data ScienceFree Complete Python - A step towards Data Science
Free Complete Python - A step towards Data Science
RinaMondal9
 
UiPath Test Automation using UiPath Test Suite series, part 4
UiPath Test Automation using UiPath Test Suite series, part 4UiPath Test Automation using UiPath Test Suite series, part 4
UiPath Test Automation using UiPath Test Suite series, part 4
DianaGray10
 
Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...
Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...
Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...
Thierry Lestable
 
Secstrike : Reverse Engineering & Pwnable tools for CTF.pptx
Secstrike : Reverse Engineering & Pwnable tools for CTF.pptxSecstrike : Reverse Engineering & Pwnable tools for CTF.pptx
Secstrike : Reverse Engineering & Pwnable tools for CTF.pptx
nkrafacyberclub
 
FIDO Alliance Osaka Seminar: Overview.pdf
FIDO Alliance Osaka Seminar: Overview.pdfFIDO Alliance Osaka Seminar: Overview.pdf
FIDO Alliance Osaka Seminar: Overview.pdf
FIDO Alliance
 
State of ICS and IoT Cyber Threat Landscape Report 2024 preview
State of ICS and IoT Cyber Threat Landscape Report 2024 previewState of ICS and IoT Cyber Threat Landscape Report 2024 preview
State of ICS and IoT Cyber Threat Landscape Report 2024 preview
Prayukth K V
 
GraphRAG is All You need? LLM & Knowledge Graph
GraphRAG is All You need? LLM & Knowledge GraphGraphRAG is All You need? LLM & Knowledge Graph
GraphRAG is All You need? LLM & Knowledge Graph
Guy Korland
 
Essentials of Automations: Optimizing FME Workflows with Parameters
Essentials of Automations: Optimizing FME Workflows with ParametersEssentials of Automations: Optimizing FME Workflows with Parameters
Essentials of Automations: Optimizing FME Workflows with Parameters
Safe Software
 
Assuring Contact Center Experiences for Your Customers With ThousandEyes
Assuring Contact Center Experiences for Your Customers With ThousandEyesAssuring Contact Center Experiences for Your Customers With ThousandEyes
Assuring Contact Center Experiences for Your Customers With ThousandEyes
ThousandEyes
 
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...
DanBrown980551
 
When stars align: studies in data quality, knowledge graphs, and machine lear...
When stars align: studies in data quality, knowledge graphs, and machine lear...When stars align: studies in data quality, knowledge graphs, and machine lear...
When stars align: studies in data quality, knowledge graphs, and machine lear...
Elena Simperl
 
Accelerate your Kubernetes clusters with Varnish Caching
Accelerate your Kubernetes clusters with Varnish CachingAccelerate your Kubernetes clusters with Varnish Caching
Accelerate your Kubernetes clusters with Varnish Caching
Thijs Feryn
 

Recently uploaded (20)

How world-class product teams are winning in the AI era by CEO and Founder, P...
How world-class product teams are winning in the AI era by CEO and Founder, P...How world-class product teams are winning in the AI era by CEO and Founder, P...
How world-class product teams are winning in the AI era by CEO and Founder, P...
 
Introduction to CHERI technology - Cybersecurity
Introduction to CHERI technology - CybersecurityIntroduction to CHERI technology - Cybersecurity
Introduction to CHERI technology - Cybersecurity
 
PHP Frameworks: I want to break free (IPC Berlin 2024)
PHP Frameworks: I want to break free (IPC Berlin 2024)PHP Frameworks: I want to break free (IPC Berlin 2024)
PHP Frameworks: I want to break free (IPC Berlin 2024)
 
Welocme to ViralQR, your best QR code generator.
Welocme to ViralQR, your best QR code generator.Welocme to ViralQR, your best QR code generator.
Welocme to ViralQR, your best QR code generator.
 
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdfSmart TV Buyer Insights Survey 2024 by 91mobiles.pdf
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf
 
GenAISummit 2024 May 28 Sri Ambati Keynote: AGI Belongs to The Community in O...
GenAISummit 2024 May 28 Sri Ambati Keynote: AGI Belongs to The Community in O...GenAISummit 2024 May 28 Sri Ambati Keynote: AGI Belongs to The Community in O...
GenAISummit 2024 May 28 Sri Ambati Keynote: AGI Belongs to The Community in O...
 
The Future of Platform Engineering
The Future of Platform EngineeringThe Future of Platform Engineering
The Future of Platform Engineering
 
The Art of the Pitch: WordPress Relationships and Sales
The Art of the Pitch: WordPress Relationships and SalesThe Art of the Pitch: WordPress Relationships and Sales
The Art of the Pitch: WordPress Relationships and Sales
 
Free Complete Python - A step towards Data Science
Free Complete Python - A step towards Data ScienceFree Complete Python - A step towards Data Science
Free Complete Python - A step towards Data Science
 
UiPath Test Automation using UiPath Test Suite series, part 4
UiPath Test Automation using UiPath Test Suite series, part 4UiPath Test Automation using UiPath Test Suite series, part 4
UiPath Test Automation using UiPath Test Suite series, part 4
 
Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...
Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...
Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...
 
Secstrike : Reverse Engineering & Pwnable tools for CTF.pptx
Secstrike : Reverse Engineering & Pwnable tools for CTF.pptxSecstrike : Reverse Engineering & Pwnable tools for CTF.pptx
Secstrike : Reverse Engineering & Pwnable tools for CTF.pptx
 
FIDO Alliance Osaka Seminar: Overview.pdf
FIDO Alliance Osaka Seminar: Overview.pdfFIDO Alliance Osaka Seminar: Overview.pdf
FIDO Alliance Osaka Seminar: Overview.pdf
 
State of ICS and IoT Cyber Threat Landscape Report 2024 preview
State of ICS and IoT Cyber Threat Landscape Report 2024 previewState of ICS and IoT Cyber Threat Landscape Report 2024 preview
State of ICS and IoT Cyber Threat Landscape Report 2024 preview
 
GraphRAG is All You need? LLM & Knowledge Graph
GraphRAG is All You need? LLM & Knowledge GraphGraphRAG is All You need? LLM & Knowledge Graph
GraphRAG is All You need? LLM & Knowledge Graph
 
Essentials of Automations: Optimizing FME Workflows with Parameters
Essentials of Automations: Optimizing FME Workflows with ParametersEssentials of Automations: Optimizing FME Workflows with Parameters
Essentials of Automations: Optimizing FME Workflows with Parameters
 
Assuring Contact Center Experiences for Your Customers With ThousandEyes
Assuring Contact Center Experiences for Your Customers With ThousandEyesAssuring Contact Center Experiences for Your Customers With ThousandEyes
Assuring Contact Center Experiences for Your Customers With ThousandEyes
 
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...
 
When stars align: studies in data quality, knowledge graphs, and machine lear...
When stars align: studies in data quality, knowledge graphs, and machine lear...When stars align: studies in data quality, knowledge graphs, and machine lear...
When stars align: studies in data quality, knowledge graphs, and machine lear...
 
Accelerate your Kubernetes clusters with Varnish Caching
Accelerate your Kubernetes clusters with Varnish CachingAccelerate your Kubernetes clusters with Varnish Caching
Accelerate your Kubernetes clusters with Varnish Caching
 

Ati course contents

  • 1. Analytics Training Institute Course Details Statistical Analysis Software (SAS+): Duration: 32 Hours + Practice session Fee Structure: Rs. 10000/Ͳ (inc. of service tax of 10.3%) x Introduction to Analytics x Introduction to SAS, GUI x Types of Libraries, Creating x Variable Attributes o Name, Type, Format, Informat, Label x Introduction to Data steps and Proc steps x DATA Understanding o Reading, Importing, Exporting and Copying Data x Conditional Statements (Where, If, If then Else) x Appending, Merging and Sorting Datasets x Proc steps like Ͳ Proc Means, Proc Freq, Proc Sort x Output Delivery System (ODS) x SAS Functions and Options x List Input, Delimiters, Reading missing Values, and non standard values x Do loops x Generating Data o Execution o Output Statements o Nesting Do loops o Do While and Do Until Statement x Arrays: o Dimensions o Array elements and Range o Proc report x Introduction to Data base, Relational Data base concepts x Proc SQL, Data integrity Constraints, Creating table and Inserting Values x Proc SQL codes to o Retrieve & Summarize data o Group, Sort & Filter o Using Joins o Indexes x Macros: o Defining and calling a macro o Macro Parameters and Variables o Global and Local Variables Analytics Training Institute New Delhi | Hyderabad | Bengaluru Email- info@analyticstraining.in www.analyticstraining.in
  • 2. Analytics Training Institute Excel Basics: Duration: 16 Hours + Practice session Fee Structure: Rs. 3,500/Ͳ (inc. of service tax of 10.3%) x Navigating Through Excel o Formatting, sorting, filter, subtotals, grouping and data validation. x Basic Functions o Text, Stat & Math Formulae and Logical x Advanced Functions o Reference Ͳ Lookups, Match and Index o Using Reference, Logical and Formulae functions in combination x Pivot Tables and Charts o Case Studies using Pivot Tables Excel Dash boarding: Duration: 24 Hours + Practice session Fee Structure: Rs. 8,500/Ͳ (inc. of service tax of 10.3%) x Working with Controls x Command Button, Text Box and Label, Combo Box, User Forms, Scroll Bar and Check Box x Create a simple calculator dashboard. x Functions like VLOOKUP,HLOOKUP,INDEX,MATCH,OFFSET,SUBTOTAL x Using the above functions to make simple parts of a dashboard. x Using Pivot Table to make simple dashboard. x Dynamic Charts, Rolling Charts, Formatting Charts, Format as Table, Naming a Range x Introduction to VBA o Programming Language, VBA, OOP, Objects, o Data Types, Variables, Procedures & Operators x Recording a Macro and Editing the Macro x UserͲDefined Functions x Control Statements o If… Then o For… Next o Do Loops x Error Handling and Debugging x Worksheet and Workbook Events x ActiveX Controls x User form – Data Entry Form x Data entry with simple dashboard x Connecting Excel to Outlook & PowerPoint(Requires strong VBA skills) Analytics Training Institute New Delhi | Hyderabad | Bengaluru Email- info@analyticstraining.in www.analyticstraining.in
  • 3. Analytics Training Institute Advanced Analytics (Analytics+): Duration: 40Hours + Practice session Fee Structure: Tool Used SAS - Rs. 15, 000/Ͳ (inc. of service tax of 10.3%) Other tools- Rs 12,000/ - (inc. of service tax of 10.3 %) x Introduction to statistics/ analytics o Need for analytics o Analytics use in different industries o Challenges in adoption of analytics o Overview of Course Contents x Data understanding o Data types (Nominal, Ordinal, Interval and Ratio) x Descriptive statistics o Tabular & Graphical Method o Summary statistics x Introduction to some statistical terminologies and inferences o Population, Sample and Random variables o Point and Interval Estimations o Probability o Discrete/Continuous Probability Distributions x Hypothesis Testing o Importance of formulating and validating the hypothesis o Formulation of hypothesis (Null and alternate) o Testing association and differences o Statistical significance and test statistic o Level of significance x ZͲTest, TͲTest, ChiͲSquare test, ANOVA x Parametric & NonͲParametric test x Correlation & Regression x Linear Regression o Case Study on Multiple Regression x Logistic Regression o Case Study on Logistic Regression x Cluster Analysis o Case Study on Cluster Analysis x Factor Analysis o Case Study on Factor Analysis Analytics Training Institute New Delhi | Hyderabad | Bengaluru Email- info@analyticstraining.in www.analyticstraining.in