Training Structure
E-Learning
Features:
- Train when and where you want.
- Learn at your own pace.
- Satisfaction guaranteed.
- Content equivalent to instructor-based courses, optimized for self-study.
- Certificate of completion.
- Created by SAS experts.
E-Learning
The fees is inclusive of:
AS Predictive Modeling with SAS Enterprise Guide |
|
| E-Learning | ✓ |
| Extended Learning | ✓ |
| Quiz | ✓ |
| Certification Reference | ✓ |
| Software Access | ✓ |
| Learn Badge | ✓ |
| Full Retail Price | ₹ 1,99,000/- |
| Save 87% | ₹ 26,500/- |
| Global Certification | ₹ 17,500/- |
| Full Retail Price | ₹ 2,16,500/- |
| Save 80% | ₹ 42,500/- |
SAS In & Out
Watch Video:
SAS Predictive Modeling with SAS Enterprise Guide
This self-paced learning is designed for individuals who need a solid foundation in using SAS Enterprise Miner and who can learn autonomously. The included content helps you prepare for the SAS Certified Predictive Modeler Using SAS Enterprise Miner 14 credential.
Why should you learn SAS ?
Included courses:
- SAS Enterprise Guide: ANOVA, Regression, and Logistic Regression: This course is designed for SAS Enterprise Guide users who want to perform statistical analyses.
- Applied Analytics Using SAS Enterprise Miner: This course is appropriate for SAS Enterprise Miner 5.3 up to 14.2. The course covers the skills that are required to assemble analysis flow diagrams using the rich tool set of SAS Enterprise Miner for both pattern discovery (segmentation, association, and sequence analyses) and predictive modeling (decision tree, regression, and neural network models).
The learning environment includes the following content:
- e-Learning (online, hands-on tutorials)
- Course materials (course notes and data)
- Quiz to test your knowledge
Learn How To:
- generate descriptive statistics and explore data with graphs
- perform analysis of variance
- perform linear regression and assess the assumptions
- use diagnostic statistics to identify potential outliers in multiple regression
- use chi-square statistics to detect associations among categorical variables
- fit a multiple logistic regression model
- define a SAS Enterprise Miner project and explore data graphically
- modify data for better analysis results
- build and understand predictive models such as decision trees and regression models
- compare and explain complex models
- generate and use score code
- apply association and sequence discovery to transaction data.
Prerequisites:
Before attending this course, you should be acquainted with Microsoft Windows and Windows software. In addition, you should have at least an introductory-level familiarity with basic statistics and regression modeling. Previous SAS software experience is helpful but not required.
This content addresses Base SAS software and is appropriate for those using SAS(R)9 software. Access to Enterprise Miner software (30 hours) is included.
