Duration: 15 Hours | Mode : Live on-line instructor led classes |  Tools: SAS Project: 3 Hours |  Specialisations : Banking Analytics |   Quiz: Yes |  Certification : Yes

Next Batch

Starts Timings (IST) Price

Basic and Advance SAS

 
9th & 10th July 2016: 11:30 AM – 02:30 PM(IST) or 11:00 PM – 2:00 AM(PDT)

16th July 2016: 1 PM-4 PM(IST) or 12:30 AM-3:30 AM(PDT)

17th July 2016: 11:30 AM – 02:30 PM(IST) or 11:00 PM – 2:00 AM(PDT)

24th July 2016:11:30 AM- 02:30PM(IST) or 11:00 PM – 2:00 AM(PDT)
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  Corporate Instructors  
Ratnakar Pandey Education:University of Arkansas, and MBA (I.S.B.)
Experience: Analytics Head – Credit Exchange , Past : Analytics Leader at Citibank, Target Inc. and Texas Instruments

Program Curriculum

Module: Introduction to SAS
  • What is SAS and importance in Analytics and Data Science Industry
  • Overview of SAS Software and Interface
  • Installation Guide
Module: Basics of SAS Programming
  • SAS Program Structure
  • Syntax Guide
  • Error Detection and Fix
  • SAS Datasets and Libraries
  • Data Import and Export
  • Data Exploration and Creation
Module: Data Manipulation
  • Create and Delete Variables and Observations
  • Subset and Filter Data
  • Sort and Merge Data
  • Format and Label
  • Conditional Selection of Certain Records
Module: Explore and Describe Data
  • Basic Statistics
  • Plots and Charts
  • Trends
  • Printing
  • Reports Generation
Module : Data Cleaning and Data Reduction
  • Outliers and Missing Value Treatment
  • Dimension / Variable Reduction for Statistical Modeling
Module – Predictive Modeling Case Studies
  • Case # 1- Predict Insurance Fraud Amount using Linear Regression
  • Case # 2- Predict Probability of Default and Develop Scorecard on a Credit Card Portfolio using Logistic Regression
  • Case # 3- Identify Customers for Up-sell and Cross-Sell using Logistic Regression
  • Case # 4- Forecast Sales of an Ecommerce Company using ARIMA Time Series
  • Case # 5- Customer Segmentation Based on Clustering (KMeans/Hierarchical)
  • Case # 6- Next Best Product Recommendation Engine for a Retail Portfolio using Market Basket Analysis
Module : Efficiency Improvement in SAS
  • SAS Macros
  • PROC SQL