Microsoft AI-300 exam voucher gives you official exam credit to schedule the Operationalizing Machine Learning and Generative AI Solutions (MLOps Engineer) exam. ITExamDeals supplies genuine voucher codes for redemption in the vendor or Pearson VUE scheduling portal after payment is confirmed.
What this exam voucher includes
- A Microsoft AI-300 exam voucher code (official exam credit) for redemption in the scheduling portal.
- Voucher instructions for booking your exam date (portal redemption guidance in chat).
- Country/region-specific voucher handling for Hungary eligibility.
- Delivery confirmation message after payment is received.
- Support in chat on successful code redemption and next booking steps.
Exam voucher price and what affects it
This voucher is offered at a discounted price of $39 USD versus a regular price of $165 USD.
Voucher pricing can vary based on:
- Country/region eligibility rules set by the vendor.
- Current supply and promotional discounting by resellers.
- Voucher issuance timing and any vendor-specific availability constraints.
- Scheduling and accounting policies used by the vendor’s exam delivery partners (Microsoft/Pearson VUE).
| Item | Value |
|---|---|
| Vendor | Microsoft |
| Exam code | AI-300 |
| Regular price (context) | $165 USD |
| Selling price (context) | $39 USD |
| Currency | USD |
Validity, expiry and rescheduling
Your voucher validity and expiry are controlled by the vendor. The exact expiry date and any rescheduling constraints are shown/confirmed during voucher redemption and/or in vendor account details.
In practice:
- You should redeem the voucher code and schedule your preferred time window as soon as you receive it.
- Rescheduling windows, allowable changes, and cutoff times are set by the vendor/partner exam policy.
- If you miss the permitted window, the voucher may not be transferable to a new slot.
How delivery and redemption work
Delivery happens over WhatsApp or Telegram after payment is confirmed.
After you receive the voucher code:
- Redeem the code in the vendor or Pearson VUE scheduling portal.
- Select the exam date and time that fits your schedule (availability varies by location and demand).
- Complete any final booking steps required by the portal to confirm your appointment.
If you run into redemption issues:
- Send the order reference and the message you see in the portal.
- We’ll help you verify that you’re redeeming against the correct exam code (AI-300) and the correct country eligibility (Hungary).
Exam format at a glance
Microsoft AI-300 is designed for candidates who build and operationalize machine learning systems, including MLOps and generative AI workflows.
Key points to plan around:
- Question types typically include scenario-based questions and knowledge checks.
- Duration and scoring thresholds are defined by the vendor exam policy.
- The passing score and exact distribution by domain are listed by Microsoft/Pearson VUE at the time of booking and/or in the official exam guide.
| 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 | check the vendor page |
Exam domains (weighted):
- Model development and evaluation: check the vendor page (weight %)
- MLOps pipelines and deployment: check the vendor page (weight %)
- Generative AI operationalization and monitoring: check the vendor page (weight %)
- Governance, security, and reliability for ML/GenAI: check the vendor page (weight %)
Prerequisites:
- Practical experience with MLOps concepts (CI/CD for ML, deployment, monitoring).
- Familiarity with ML workflows and at least one cloud AI platform used for production-grade ML/GenAI.
- Understanding of APIs, data pipelines, and operational monitoring patterns.
Recertification cycle:
- Vendor policies determine whether/when an exam role certification requires renewal. Check Microsoft’s certification lifecycle guidance for the latest schedule.
Realistic study time:
- Typical preparation is often 6–10 weeks depending on prior hands-on MLOps experience and time spent weekly.
Career value and job roles
This exam is directly aligned with MLOps Engineer responsibilities, especially for teams moving from experiments to production.
Roles commonly targeted:
- MLOps Engineer (mid-level) building CI/CD, deployment, and monitoring pipelines for ML and GenAI.
- AI Engineer / Applied AI Engineer (mid-to-senior) operationalizing model services and ensuring reliability.
- ML Platform Engineer / ML Infrastructure Engineer (senior) driving governance, safety, and scalable production operations.
You’ll also benefit if you work on:
- Model evaluation, online/offline inference patterns, and performance troubleshooting.
- Generative AI solution reliability, observability, and lifecycle management.
- Cross-team work between data scientists and platform engineers to standardize production workflows.
Prepare before you book
Before you schedule, confirm your planned topics match the current AI-300 exam guide and practice with realistic tasks.
Use our prep hub to reduce surprises:
- Start with free mock exams.
- Passing a mock exam unlocks extra voucher discounts.
This approach helps you:
- Identify weak areas in MLOps and GenAI operationalization early.
- Build exam-day confidence with timed, exam-style practice.
- Adjust your study plan before you commit to a booking window.
Common mistakes to avoid
- Buying a voucher without checking that you’re eligible to book from Hungary and that the redemption portal recognizes your country selection.
- Waiting too long to redeem and schedule, then running into limited availability or rescheduling cutoffs.
- Studying only model training concepts while under-preparing for operations: monitoring, deployment strategies, and reliability.
- Ignoring governance and security-related aspects (permissions, operational controls, and safe production patterns).
- Skipping hands-on practice: for AI-300, scenario-based questions reward experience with pipelines, deployment, and operational troubleshooting.
- Not using practice exams before booking—reducing your ability to focus on the highest-impact exam topics.