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The SAS Institute A00-225 exam is an exam that is designed to show that you have the knowledge and skills needed to use SAS software. You will need this certification if you use SAS software at work so that your employer can vouch for your skills and prove how valuable you are to the company.

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Preparation Guide of SAS Institute A00-225 Exam

A00-225 Prep Guide: Prep guide for the SAS Institute A00-225 Exam

An Analysis of the SAS Institute A00-225 Exam: A blog about the SAS Institute A00-225 exam along with preparation tips.

SAS Institute A00-225 exam is an SAS Certified Application Associate Certification exam. It's one of the most famous certifications in IT industry. With the increase in outsourcing and more opportunities for job, SAS certification has gained ground in recent years. SAS jobs have been one of the highest paid jobs for programmers. If you are working as a programmer or a developer, SAS certification can be a stepping stone to your career growth in the future. This guide gives some information about this certification and its benefits. You should read this guide if you frequently deal with programming languages like SAS. SAS Institute A00-225 Dumps is designed to help you pass the SAS Institute A00-225 Exam easily and quickly. Department of Business Administration (BSA) has also come up with the SAS Institute A00-225 test questions and answers for practice. Includes the latest updates on the SAS Institute A00-225 certification. Visual SAS and SAS Visual Studio are two popular development tools for SAS. SAS is a platform that supports the deployment of data security products. Requirements for the SAS Certified Application Associate (SCA) certification are very high.

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SASInstitute A00-225 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Open Source Models in SAS10%- Incorporate Python programs into SAS Enterprise Miner
- Incorporate R programs into SAS Enterprise Miner
Topic 2: Logistic Regression30%- Variable screening and model selection
- Interpret ROC, lift and gains charts
- Prepare input data and handle categorical variables
- Score new data using LOGISTIC and PLM procedures
Topic 3: Predictive Analytics on Big Data40%- Perform cluster analysis and principal component analysis
- Build random forest models
- Analyze categorical and interval targets using SAS Visual Statistics
- Use PROC IMSTAT and high-performance analytics
Topic 4: Neural Networks20%- Apply optimization methods for network training
- Construct custom network architectures
- Use architectures for linear and non-linear modeling
- Describe key concepts underlying neural networks

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