Welcome to your one-stop solution for all the information you need to excel in the SAS Managing the Model Life Cycle using ModelOps (A00-440) Certification exam. This page provides an in-depth overview of the SAS A00-440 Exam Summary, Syllabus Topics, and Sample Questions, designed to lay the foundation for your exam preparation. We aim to help you achieve your SAS Certified ModelOps Specialist certification goals seamlessly. Our detailed syllabus outlines each topic covered in the exam, ensuring you focus on the areas that matter most. With our sample questions and practice exams, you can gauge your readiness and boost your confidence to take on the SAS ModelOps exam.
Why SAS ModelOps Certification Matters
The SAS A00-440 exam is globally recognized for validating your knowledge and skills. With the SAS Certified ModelOps Specialist credential, you stand out in a competitive job market and demonstrate your expertise to make significant contributions within your organization. The SAS Managing the Model Life Cycle using ModelOps Certification exam will test your proficiency in the various syllabus topics.
SAS A00-440 Exam Summary:
| Exam Name | SAS Managing the Model Life Cycle using ModelOps |
| Exam Code | A00-440 |
| Exam Duration | 110 minutes |
| Exam Questions | 65 |
| Passing Score | 65% |
| Exam Price | $180 (USD) |
| Books / Training |
ModelOps: Governing AI and Machine Learning Models That Drive Your Business with SAS®. Managing Models in SAS Viya |
| Exam Registration | Pearson VUE |
| Sample Questions | SAS ModelOps Certification Sample Question |
| Practice Exam | SAS ModelOps Certification Practice Exam |
SAS A00-440 Exam Syllabus Topics:
| Objective | Details |
|---|---|
Define the ModelOps Framework (18 - 22%) |
|
| Emphasis on governance and stakeholders |
- Determine relevant stakeholders based on desired business outcome - How will collaboration be achieved - What are standard channels of communication |
| Determine the business process workflow |
- Outline feedback loops and decision validation - Articulate handoffs and individual roles/responsibilities
- Define audit and tracking needs
|
| Develop workflow template(s) to execute the process |
- Model Type
- Scoring Environments
|
Develop Model Proposal (23 - 28%) |
|
| Define the business objective |
- Define the business objective
|
| Associated assets to include |
- Cost/benefit analysis - Optimal business value - Time to return on investment - Level of risk - Caveats/Assumptions - Finalize consumption method |
| Evaluation against alternative resource allocation | |
| Establish preferred deployment method | |
| Establish monitoring assessment metrics |
- Business outcome metrics - Optimal model accuracy fit statistics - Model monitoring frequency and evaluation criteria - Operational performance metrics |
Model Development and Management (23 - 28%) |
|
| New or Re-build Model Development |
- Pre-processing - data extracts and data preparation - Model training - Post-processing - Integration with third party software |
| Model tournament |
- Evaluate and compare multiple candidate models
- Select a champion model |
| Execute peer review | |
| Execute business review |
- Exporting score code - Registering a model - Publish a model |
| Model registration |
- Metadata
- Artifacts
|
| Establish the monitoring process |
- Build data extracts for input data - Create metrics to monitor
- Setup thresholds and alerts |
| Prepare a model for use in production | |
Model Deployment (18 - 22%) |
|
| Develop the data ingestion pipeline |
- Confirm naming conventions/standards used - Review adherence to architecture standards - Process request for additional data source (if needed) - Build data extract for monitoring |
| Define production jobs |
- Create consumption application(s) (on-demand/streaming) - Integrate with decisioning process - Setup scoring, includes pre-/post-processing - Setup performance data creation - Setup performance monitoring reports
- Develop follow-up actions
|
| IT compliance check |
- Validate regulatory compliance - Cross-check against standards/policy |
| Pre-production Testing |
- Unit testing - Regression testing - Performance testing |
Production (9 - 12%) |
|
| Execute preprocessing | |
| Execute scoring/decision | |
| Execute post-processing | |
| Execute business actions associated with score/decision | |
| Execute performance monitoring |
- Evaluation
- Alerts based on thresholds |
The SAS has created this credential to assess your knowledge and understanding in the specified areas through the A00-440 certification exam. The SAS Certified ModelOps Specialist exam holds significant value in the market due to the brand reputation of SAS. We highly recommend thorough study and extensive practice to ensure you pass the SAS Managing the Model Life Cycle using ModelOps exam with confidence.