SAS Certified Specialist: Machine Learning Using SAS Viya 3.4

To prepare for the SAS exam, you can create a map that contains all the resources and details. Then, work your way through the steps. Similar to this, the SAS Certified Specialist: Machine learning Using SAS Viya 3.0 Cheat Sheet will provide you with a sequential approach to strong revision. This certification exam is the best for core knowledge and experience in AI. SAS Machine Learning Using SAS Viya3.4 exam requires skills and knowledge in AI and Analytics Talent using Open Source SAS tools. This cheat sheet will help you organize all of these items and guide you through your preparation.
Let’s begin with the basics and then move on to the overview.
Machine Learning Using SAS Viya 3.4: Exam Overview
SAS Machine Learning Using SAS Viya3.4 exam requires you to demonstrate your AI and Analytics Talent using Open Source SAS tools to gain insight from data. This exam tests your knowledge and skills in Visual Data Mining and Machine Learning software.
First, prepare data and feature engineering
Second, creating supervised machine-learning models
Third, we evaluate the model’s performance
Finally, models can be put into production
This exam is required if you wish to become data scientists in order to create supervised machine learning models using SAS Viya pipelines.
Quick Cheat Sheet for SAS Certified Specialist: Machine Learning with SAS Viya 3.4
The SAS Certified Specialist: Machine learning Using SAS Viya3.4 exam is widely accepted around the world and will add great value for your resume by validating skills and knowledge. It is important to put in a lot of effort, passion, effort, and time to pass this exam. You can prepare well for the SAS exam by using the right training and resources. Let’s not waste time, and let’s go over all the necessary resources to help you revise quickly.
Understanding Exam Topics
You will find detailed information about the components, resources, and exam objectives for SAS Certified Specialist Machine Learning Using SAS Viya3.4. A thorough analysis of exam concepts will help you align yourself with the main objectives of the exam. You will be able to mark and review the topics and sections you find difficult later. The topics included in this exam are listed below.
Data Sources (30%)
Model Studio allows you to create a project (Reference:Creating New Projects)
Explore the data (Refer:Easing into data exploration, reporting and analytics Using SAS Enterprise Guide).
Modify data (Refer:MODIFY Statement).
Reduce the dimensionality of the data (Reference:Multivariate Analysis: Principal Component Analysis)
To identify important variables, use the VARIABLE SELECTION node (Reference:Variable Select Node).
Building Models (50%)
Describe key terms and concepts in supervised machine learning (Refer:Machine Learning).
Build models with decision trees and ensemble of trees (Reference:Tree-Based Machine Learning Methods in SAS Viya)
Building models with neural networks (Refer: How to build deep learning models using SAS)
Build models with support vector machines (Reference:Application of Support Vector Machine Modeling and Graph Theory Metrics for Disease Classification)
Use Model Interpretability tools to explain black box models (Reference:Explaining complex models in SAS Viya with programmatic interpretability)
Incorporate externally written code (Reference:Registering an External File with User-Written Code)
Model Assessment and Deployment (20%)
Describe the principles of Model Assessment (Refer:Model assessment and selection for machine learning).
Model Studio allows you to compare and assess models (Reference:Compare Models).
How to deploy a model

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