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There are 4 modules in this course
This applied, hands-on course teaches you how to manage models through their useful life cycle. After creating a modeling project, you add and compare models to it so that you can identify a champion model. The course uses models that are created using SAS Advanced Analytics capabilities, Python, and R. The course also shows how to implement workflow to ensure that model governance and oversight approval is being followed.
You learn how to test a model in the production environment in which it will be deployed. After the model test completes successfully, you learn how to schedule a model scoring job so it can run automatically. Further, the course shows how to measure and monitor the ongoing model performance over time. The performance monitoring process will also be scheduled to run automatically in class. An optional lesson shows how to register and score Text Analytics models.
This course is appropriate for anyone involved in data preparation and production model scoring; modelers who create and test models; business analysts who are consumers of the model; and business analysts or consultants who are responsible for integrating models, business rules, and rule flows into operational processes
In this module, you meet the instructor and learn about course logistics, such as how to access the software for this course.
What's included
8 videos1 app item
Show info about module content
8 videos•Total 15 minutes
Course Overview•2 minutes
Overview•0 minutes
The Analytical Life Cycle•3 minutes
Key User Roles•3 minutes
Managed Model Life Cycle•1 minute
Development Operations Pipeline•1 minute
Model Operations•1 minute
Model Operations Environments•3 minutes
1 app item•Total 60 minutes
Access SAS Viya for Learners•60 minutes
Working with Projects and Models
Module 2•4 hours to complete
Module details
In this module, you learn about working with projects and models.
What's included
22 videos14 readings1 assignment
Show info about module content
22 videos•Total 68 minutes
Overview•0 minutes
Analytics Life Cycle•1 minute
Model Manager Services•1 minute
A Modeling Process•1 minute
Demo: Modeling Life Cycle•3 minutes
Demo: Accessing the Data Files•4 minutes
Demo: Creating a New Project•7 minutes
Demo: Quickstart Wiz•1 minute
Demo: Importing Models into a Project•4 minutes
Demo: Setting Model Properties•8 minutes
Python Model Coding Considerations•1 minute
Deploy a Model•2 minutes
Help with Python Models•0 minutes
Demo: Importing a Python Model•6 minutes
Working with R Models•1 minute
Demo: Importing an Open Source R Model into Model Manager•4 minutes
Demo: Comparing Models•5 minutes
Demo: Testing a Model•5 minutes
Demo: Setting a Champion Model•3 minutes
Demo: Adding a Workflow Definition•5 minutes
Demo: Starting a Workflow•1 minute
Demo: Completing Workflow Tasks•4 minutes
14 readings•Total 140 minutes
Resource•10 minutes
General Project Properties•10 minutes
Types of Model Functions•10 minutes
Practice: Creating a New Project•10 minutes
Practice: Importing a Data Source and Profiling the Data•10 minutes
Resource•10 minutes
General Model Properties•10 minutes
Demo Steps: Using a notebook to build Python models, add and test score code in a new Model Manager project•10 minutes
Resource•10 minutes
Working with R Models•10 minutes
The R SASCTL Package•10 minutes
Practice: Importing Models from SAS Package File, PMML, and ZIP Formats•10 minutes
Self-Study Demo: Enabling a Workflow•10 minutes
Resource•10 minutes
1 assignment•Total 30 minutes
Question: Model Manager•30 minutes
Model Deployment
Module 3•2 hours to complete
Module details
In this module, you learn about model deployment.
What's included
17 videos3 readings1 assignment
Show info about module content
17 videos•Total 61 minutes
Overview•1 minute
Operationalizing Analytics•2 minutes
Publishing Models•3 minutes
Demo: Publishing a Champion Model•4 minutes
Demo: Adding and Testing a CAS Publishing Destination (Part 1)•4 minutes
Demo: Adding and Testing a CAS Publishing Destination (Part 2)•3 minutes
Deployment Considerations•1 minute
Practical Deployment Considerations•1 minute
Scoring Output Table Considerations•1 minute
Demo: Model Deployment in CAS•8 minutes
Monitoring Model Performance•1 minute
Performance Data Source Choices•1 minute
Available Performance Metrics•4 minutes
Demo: Running Performance Jobs•12 minutes
Demo: Model Cards•4 minutes
Automating Model Performance Reporting•2 minutes
Demo: Scheduling a Performance Job•10 minutes
3 readings•Total 30 minutes
Additional Ways to Create a CASLIB for a Publishing Destination•10 minutes
Resource•10 minutes
Model Retraining•10 minutes
1 assignment•Total 30 minutes
Question: Score Code•30 minutes
Additional Topics (self-study)
Module 4•1 hour to complete
Module details
In this self-study module, you learn about scoring visual text analytics models.
What's included
1 video8 readings
Show info about module content
1 video
Overview•0 minutes
8 readings•Total 80 minutes
Scoring Visual Text Analytics Models•10 minutes
Model Repositories•10 minutes
How to Fit a Scoring Script for Model Containerization•10 minutes
Feature Contribution Index•10 minutes
Model Usage Summary•10 minutes
Communities Articles•10 minutes
Python Requirements File•10 minutes
Python Score Code Generation with pzmm•10 minutes
Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.
Through innovative software and services, SAS empowers and inspires customers around the world to transform data into intelligence. SAS is a trusted analytics powerhouse for organizations seeking immediate value from their data. A deep bench of analytics solutions and broad industry knowledge keep our customers coming back and feeling confident. With SAS®, you can discover insights from your data and make sense of it all. Identify what’s working and fix what isn’t. Make more intelligent decisions. And drive relevant change.
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To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Certificate?
When you enroll in the course, you get access to all of the courses in the Certificate, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.