Microsoft AI-300 is a vendor-exam credit you redeem to schedule the official proctored exam: “Operationalizing Machine Learning and Generative AI Solutions (MLOps Engineer)”. This voucher page is for discounted purchase with redemption via the Microsoft/Pearson VUE booking flow, using the voucher code we provide.
What this exam voucher includes
- An official Microsoft AI-300 exam voucher code (exam credit) for scheduling
- Redemption instructions for booking the exam date in the vendor portal
- Country-limited voucher support for Switzerland (as sold)
- Chat-based confirmation of your order reference and voucher issuance
- Guidance on rescheduling expectations before you book
- Proof-of-purchase details tied to your order reference
- Customer support via WhatsApp or Telegram for redemption questions
Exam voucher price and what affects it
Your pricing for this voucher is:
| Item | Amount |
|---|---|
| Regular price | $165 USD |
| ITExamDeals selling price | $39 USD |
The selling price is discounted compared to the regular vendor list price. Actual checkout totals can vary due to currency handling, payment method fees, and vendor-controlled eligibility rules. This page reflects the stated selling price context you provided.
Validity, expiry and rescheduling
Voucher validity and expiry are controlled by the vendor and the time window displayed during redemption in the Microsoft/Pearson VUE scheduling system. You must redeem and schedule within the vendor’s allowed timeframe. If you need to reschedule, Microsoft/Pearson VUE applies their rescheduling policy and any cutoff windows shown in the booking system.
How delivery and redemption work
- Choose Switzerland as your country/region for this voucher purchase.
- After you send your order reference on WhatsApp or Telegram, we confirm the voucher details in chat.
- Pay for the voucher using the payment method shared during order confirmation.
- After payment is confirmed, we deliver the official voucher code over WhatsApp or Telegram.
- Redeem the voucher code in the vendor scheduling portal to book your AI-300 exam date.
Exam format at a glance
Microsoft AI-300 is delivered as a proctored exam through the Microsoft/Pearson VUE ecosystem. Use the exam booking portal to confirm your language options and the exact appointment rules.
| 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 |
Domains (what you are tested on)
Domain weights can change by exam version. Use the current official AI-300 exam page for the latest weighting. Typical AI-300 themes include MLOps operations for production machine learning, generative AI solution operationalization, and lifecycle management.
- Operationalize MLOps pipelines and ML workflows (percentage: check the vendor page)
- Build and manage generative AI solution workflows (percentage: check the vendor page)
- Deployment, monitoring, and lifecycle management in production (percentage: check the vendor page)
- Governance, security, and reliability considerations (percentage: check the vendor page)
Prerequisites and expectations
Microsoft AI-300 expects practical familiarity with building and operating ML/GenAI systems. You should be comfortable with ML pipeline concepts, model lifecycle thinking, and production deployment patterns. Prior experience with cloud-based workloads is strongly recommended.
Recertification / retake timing
This voucher provides access to schedule the specific AI-300 exam. If you do not pass on your first attempt, you may be eligible to retake according to the vendor’s exam retake policy shown in your account.
Realistic study time
For candidates with relevant hands-on experience, plan for roughly 8–12 weeks of focused preparation. If you are building up MLOps/GenAI operational depth from scratch, allow more time.
Career value and job roles
This AI-300 voucher is targeted at professionals responsible for operationalizing machine learning and generative AI solutions—people who take models from experimentation into reliable, monitored, governed production systems.
Common job roles include:
- MLOps Engineer (mid-level to senior)
- ML Engineer focused on productionization
- AI Engineer responsible for GenAI system operations
You should already know how to structure ML workflows and understand production concerns like monitoring, deployments, and lifecycle management.
Prepare before you book
Before you redeem and book, validate your readiness with practice that mirrors the real exam approach. Start with our free practice hub: free mock exams.
Also note: passing a mock exam unlocks extra voucher discounts—so you can reduce risk before you commit to your official booking.
Common mistakes to avoid
- Waiting to study until after booking: aim to finish core learning and practice before you schedule.
- Only knowing model training: AI-300 emphasizes operationalization, not just experimentation.
- Ignoring monitoring and lifecycle: production MLOps topics often carry significant exam weight.
- Skipping governance and reliability fundamentals: be ready for questions on safe, dependable delivery.
- Not checking the current exam version: weights, question styles, and allowed languages can change—confirm inside the official exam listing.