This outline is provisional and subject to change.
Companies need to continually adapt to changing business conditions. They can make informed decisions with the help of predictive models, but many businesses still struggle with getting models into production in a reasonable timeframe. This course describes how awareness of ModelOps (model operations) can streamline the journey from preparing data, building models, and deploying them in production environments to managing their performance. Proven DevOps (development operations) disciplines are evolving into the unique practice of deploying models in today’s environment.
Use of SAS Container Runtime and SAS Model Risk Management are also addressed, as are pointers about administrating a production environment.
This course helps candidates prepare for the SAS Certified ModelOps Specialist exam along with the topics covered in the Managing Models in SAS® Viya® course.
Learn how to
- Distinguish ModelOps from DevOps.
- Use corporate culture as a positive influence on modeling outcomes.
- Control the process of deploying models with the ModelOps approach.
- Recognize the hidden impact of model risk.
- Deploy models in the cloud using SAS Container Runtime.
- Set up administration of the SAS modeling environment.
Who should attend
Anyone who needs to know what ModelOps is; anyone responsible for managing the deployment of models in a production environment; operations team members that support model deployment and administration; modeling team leaders wanting to get hands-on experience with ModelOps management software; and those preparing for the SAS Certified ModelOps Specialist exam.
This outline is provisional and subject to change.
Although not required, it is highly recommended that students complete the Managing Models in SAS® Viya® course.
This course addresses SAS Model Manager software.
This outline is provisional and subject to change.
Introduction to ModelOps- Introduction to ModelOps.
- Current state of models.
- Objectives of ModelOps.
- DevOps principles and values background.
The Analytics Life Cycle- A blueprint for ModelOps.
- ModelOps initiation phase.
- DataOps and model building.
- The Register, Document, Validate, and Test phases.
- Deploying models.
- Monitoring performance.
Model Risk and Governance- SAS Model Risk Management.
SAS Container Runtime and Administration Concepts- SAS Container Runtime.
- SAS Model Manager administration concepts.
