SAS Financial Data Analyst Certification Training in Pune

Duration: 144 hrs| Live Web Training

In this training you will learn to manipulate, analyze and interpret complex data sets relating to the employer's business. This includes data mining skills, advanced modelling techniques and business visualization which conveys information in a universal manner and make it simple to share ideas with others. Learn to prepare reports for internal and external audiences using business analytics reporting tools. Create data dashboards, graphs and visualizations. Provide sector and competitor benchmarking.
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Course Curriculum

Course 1 - BASE SAS PROGRAMMER

  • the SAS programming process
  • using SAS programming tools
  • understanding SAS syntax
  • understanding SAS data
  • accessing data through libraries
  • importing data into SAS
  • exploring data
  • filtering rows
  • formatting columns
  • sorting data and removing duplicates
  • reading and filtering data
  • computing new columns
  • conditional processing
  • enhancing reports with titles, footnotes, and labels
  • creating frequency reports
  • creating summary statistics reports
  • exporting data
  • exporting reports
  • using Structured Query Language in SAS
  • joining tables using SQL in SAS

Module 2 - SAS Programming 2: Data Manipulation Techniques : Level Intermediate

  • setting up for this course
  • understanding DATA step processing
  • directing DATA step output
  • creating an accumulating column
  • processing data in groups
  • understanding SAS functions and CALL routines
  • using numeric and date functions
  • using character functions
  • using special functions to convert column type
  • creating and using custom formats
  • creating custom formats from tables
  • concatenating tables
  • merging tables
  • identifying matching and nonmatching rows
  • using iterative DO loops
  • using conditional DO loops
  • restructuring data with the DATA step
  • restructuring data with the TRANSPOSE procedure

Module 2- SAS Certified Predictive Modeler Using SAS Enterprise Miner 14

  • Discussing descriptive statistics
  • Discussing inferential statistics
  • Listing steps for conducting a hypothesis test
  • Discussing the basics of using your SAS software
  • Introducing the SAS Enterprise Guide 7.1 environment
  • Discussing fundamental statistical concepts
  • Examining distributions
  • Describing categorical data
  • Constructing confidence intervals
  • Performing simple tests of hypothesis
  • Performing one-way ANOVA
  • Performing multiple comparisons
  • Performing two-way ANOVA with and without interactions
  • Using exploratory data analysis
  • Producing correlations
  • Fitting a simple linear regression mode
  • Understanding the concepts of multiple regression
  • Building and interpreting models
  • Describing all regression techniques
  • Exploring stepwise selection techniques
  • Examining residuals
  • Investigating influential observations and collinearity
  • Describing categorical data
  • Examining tests for general and linear association
  • Understanding the concepts of logistic regression and multiple logistic regression
  • Performing backward elimination with logistic regression

Module 4 - Applied Analytics Using SAS Enterprise Miner : Level Intermediate

  • Introduction to SAS Enterprise Miner
  • Creating a SAS Enterprise Miner project, library, and diagram
  • Defining a data source
  • Exploring a data source
  • Introduction
  • Cultivating decision trees
  • Optimizing the complexity of decision trees
  • Understanding additional diagnostic tools (self-study)
  • Autonomous tree growth options (self-study)
  • Selecting regression inputs
  • Optimizing regression complexity
  • Interpreting regression models
  • Transforming inputs
  • Categorical inputs
  • Polynomial regressions (self-study)
  • Input selection
  • Stopped training
  • Other modeling tools (self-study)
  • Model fit statistics
  • Statistical graphics
  • Adjusting for separate sampling
  • Profit matrices
  • Internally scored data sets
  • Score code modules
  • Cluster analysis
  • Market basket analysis (self-study)
  • Ensemble models
  • Variable selection
  • Categorical input consolidation
  • Surrogate models
  • SAS Rapid Predictive Modeler
  • Banking segmentation case study
  • Website usage associations case study
  • Credit risk case study
  • Enrollment management case study

Course 3- SAS Visual Business Analyst

Module 5 - SAS Visual Analytics 1 for SAS Viya: Basics

  • Introduction to SAS Visual Analytics
  • Exploring the SAS Visual Analytics course environment
  • Viewing SAS Visual Analytics reports
  • Investigating data in SAS Visual Analytics
  • Transforming data using Data Studio
  • Working with data items
  • Exploring data with charts and graphs
  • Creating data items and applying filters
  • Performing data analysis (relationship charts)
  • Creating a simple report
  • Creating interactive reports
  • Working with display rules

Module 6 - SAS Visual Analytics 2 for SAS Viya: Advanced

  • Overview of SAS Visual Analytics
  • Automated explanation
  • Introduction to SAS Data Studio
  • Restructuring data
  • Analyzing geographic information
  • Restructuring data
  • Forecasting
  • Restructuring data for network analysis
  • Creating a network analysis object
  • Creating calculated items
  • Creating aggregated measures
  • Creating advanced filters
  • Creating advanced interactive filters
  • Using numeric parameters
  • Using character parameters
  • Using date parameters

Course 4 - SAS Solutions for RISK and IFRS : An Introduction

  • Risk defined
  • Types of Risk
  • Regulatory Bodies in Risk
  • Basel Accords
  • IFRS9
  • IFRS17
  • SAS for Credit and Market Risk
  • SAS for Operational Risk
  • SAS for IFRS9
  • SAS for IFRS17
  • Solution Components
  • SAS process for IFRS9
  • SAS Outcomes and Disclosure reports
  • Solution Components
  • SAS process for IFRS17
  • SAS Outcomes and Disclosure reports

Course Batch Details

Sample Certificate

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