Microsoft AI-300 is the MLOps Engineer exam for Operationalizing Machine Learning and Generative AI Solutions. This voucher gives you official exam credit that you redeem in the vendor scheduling portal to book your AI-300 exam.
What this exam voucher includes
- One official Microsoft exam voucher code for Microsoft AI-300 (Operationalizing Machine Learning and Generative AI Solutions).
- Voucher redemption instructions for scheduling the exam in the vendor portal.
- El Salvador (SV) eligibility guidance for buyers.
- Support via chat to confirm your order reference and redemption steps.
- Delivery of the voucher code through WhatsApp or Telegram after payment confirmation.
- Confirmation that the voucher is a genuine vendor exam credit (not a third-party “pass guarantee”).
Exam voucher price and what affects it
Your listed pricing for this Microsoft AI-300 voucher from ITExamDeals is:
| Item | Price (USD) |
|---|---|
| Regular price | 165 |
| Selling price | 39 |
The final amount you pay can depend on the country/region availability for the voucher, the current promotional discount applied by ITExamDeals, and Microsoft scheduling/voucher program rules. Microsoft exam pricing and scheduling policies are vendor-controlled; this voucher is sold at the discounted rate shown on this product page.
Validity, expiry and rescheduling
The voucher has a vendor-controlled validity period and may include an expiry date set by Microsoft. You must redeem the code and book your exam within the vendor’s allowed timeframe.
Rescheduling is also controlled by Microsoft’s exam policies once you have booked a specific appointment. If you change plans, reschedule within the vendor’s permitted window for the appointment you booked (typically tied to the appointment date and vendor rules).
If you need to rebook, keep your original booking details, and follow the rescheduling workflow in the scheduling portal.
How delivery and redemption work
- After payment is confirmed, we deliver your AI-300 voucher code via WhatsApp or Telegram.
- You redeem the code in the vendor’s scheduling portal (Microsoft/Pearson VUE booking flow, depending on your region).
- You select your exam center/online option (where available) and choose an exam appointment date.
- You confirm the booking, then follow the pre-exam steps required by the exam provider (ID and testing requirements).
Important: This voucher page provides the exam credit. The actual scheduling appointment (date/time, test delivery format, and rescheduling options) is determined in the vendor portal.
Exam format at a glance
Below is a quick reference for Microsoft AI-300 (Operationalizing Machine Learning and Generative AI Solutions). Where exact figures can vary by delivery/program updates, use the vendor materials for the definitive numbers (marked as check the vendor page).
| Exam code | Questions | Duration | Passing score | Languages | Delivery options |
|---|---|---|---|---|---|
| AI-300 | check the vendor page | check the vendor page | check the vendor page | check the vendor page | English (commonly offered; check the vendor page) |
Question types
Expect a mix of:
- Scenario-based multiple-choice questions.
- Knowledge checks on MLOps workflows, deployment patterns, and operational governance.
- Tasks focused on building, operationalizing, and monitoring ML and generative AI pipelines.
Prerequisites
Microsoft AI-300 is designed for candidates working with MLOps. You should be comfortable with:
- Machine learning fundamentals and model training/packaging concepts.
- Working with cloud services and deployment concepts in an Azure context.
- Basic understanding of containers and CI/CD principles.
- Familiarity with generative AI concepts and responsible deployment practices.
Weighted domains (what to study)
Domain weights can change by exam update. Use the vendor outline as the source of truth; the below reflects the common structure for AI-300-like MLOps exams and should be confirmed on the official page.
- Check the vendor page: MLOps pipelines and operationalization fundamentals — check weight
- Check the vendor page: Model deployment, orchestration, and release workflows — check weight
- Check the vendor page: Monitoring, evaluation, and incident/quality management — check weight
- Check the vendor page: Governance, security, and responsible AI operations — check weight
Realistic study time
Most candidates need 8–12 weeks of preparation when starting with practical experience in MLOps and Azure ML/GenAI operations. Faster learners who already have deployment/monitoring experience may require less time; less experienced candidates often need more.
Recertification cycle
Microsoft certification refresh rules are periodically updated. Confirm your exact recertification expectations on the official Microsoft certification page for AI-300/its credential pathway.
Career value and job roles
This voucher is for candidates targeting roles that operationalize ML and generative AI systems into reliable production services.
Common job titles include:
- MLOps Engineer (mid-level to senior), responsible for end-to-end ML/GenAI lifecycle from training to deployment and monitoring.
- Machine Learning Engineer (MLOps-focused), building repeatable pipelines and automation.
- AI Platform Engineer or Applied AI Engineer, collaborating on governance, CI/CD, observability, and model lifecycle management.
The AI-300 credential helps validate your ability to take ML and GenAI solutions beyond notebooks and into production-grade systems: automated pipelines, deployable artifacts, monitoring, evaluation, and operational governance.
Prepare before you book
Use this voucher only after you’ve done a structured practice plan. Start with our free practice hub here: free mock exams.
Passing a mock exam unlocks extra voucher discounts on eligible products when promotions are running. It’s the fastest way to check readiness, identify weak domains, and avoid booking an exam before you’re prepared.
In addition to mock exams, review the official exam outline, complete hands-on labs (pipelines, deployment, monitoring, governance), and build at least one end-to-end MLOps workflow you can explain clearly.
Common mistakes to avoid
- Booking too early: MLOps includes operations, monitoring, and governance. If you only know training basics, you’ll likely struggle.
- Skipping the “operational” parts: CI/CD, versioning, and release practices are commonly tested in scenario questions.
- Ignoring responsible AI and governance: Even for engineers, exams often include operational governance concepts.
- Not practicing monitoring/evaluation: You should be ready to interpret evaluation signals and think through what to do when metrics drift.
- Relying on memorization: Use scenario-based practice to learn how decisions connect across the MLOps lifecycle.
- Assuming retakes or refunds: Voucher terms are vendor-controlled. Know the expiry and no-refund rules before you buy.
- Forgetting the vendor portal steps: Redeeming the code is the key step; appointment booking is done after redemption.