[100% Off] Ai-300: Machine Learning And Generative Ai Solutions

6 mock exams × 100 questions • MLOps and GenAIOps judgement • Multiple-choice, multi-select, sequencing and case studies

Added on October 26, 2026 IT & Software 2 min read

What you’ll learn

Design workspaces
compute
and datastores so that environments
credentials
and assets cannot leak into each other,Define infrastructure as code with Bicep and parameter files
and keep it drift-free with deployment stacks,Replace stored secrets with workload identity federation
managed identity
and per-environment service principals,Automate training and deployment with `az ml` declarative jobs
pipelines
components
and GitHub Actions environments,Track experiments properly with MLflow
then register
version
tag
and promote models with provenance,Deploy and operate online and batch endpoints: traffic splits
readiness probes
autoscaling
rollback
and drift alerts,Stand up GenAIOps foundations: hubs and projects
model catalog and capacity choices
prompt flows
connections
and runtime identity,Ground generative systems with Azure AI Search: chunking
embeddings
hybrid retrieval
entitlement-aware indexes
and refresh,Gate prompt and flow changes with offline evaluation
then describe them with versioned prompt files,Measure quality honestly: dataset design
sample size
LLM judges
groundedness
relevance
coherence
safety
and injection testing,Observe and diagnose: span-level tracing
prompt logging
feedback loops
and continuous evaluation on sampled traffic,Control cost and latency without losing quality: token budgets
caching with TTL
routing
right-sizing
quantization
streaming
compression
and provisioned c,Practise 600 original questions
including 24 case studies
with an explanation for every option

Requirements

No prior certification is required. The exam is written for engineers who build and operate machine learning and generative AI workloads on Azure
so the material assumes some exposure to that work.,Helpful but not required: • Having trained or deployed at least one model on any platform • Having read a pipeline or CI/CD workflow definition • Basic familiarity with Azure resource groups and the Azure CLI • Comfort reading configuration files such as Bicep
YAML
or JSON

Description

You can train a model. Can you ship it, gate it, watch it, and keep it affordable after the demo ends?

Prepare for Microsoft AI-300 (Microsoft Certified: Machine Learning Operations Engineer Associate) with 600 original questions across six full-length mock exams of 100 items each. Every exam is blueprint-weighted, so each one is a coherent rehearsal of the whole blueprint rather than a random topic dump.

AI-300 tests configuration, and this package honours that. You will read Bicep, `az ml` and job YAML, GitHub Actions workflows, MLflow and prompt-flow structure, endpoint traffic splits, and evaluation configuration — and decide what to change. That is deliberate: it is the one place this course departs from a purely conceptual style, because an operations engineer is judged on configuration.

WHAT YOU GET

• Six original 100-question mock exams

• Blueprint weighting on every exam: 18 / 29 / 23 / 15 / 15 across the five published domains

• Mixed item types: 76 multiple-choice, 16 multi-select, with 8 of the multiple-choice items asking you to pick the correct candidate sequence

• Four three-question case studies inside every exam

• An explanation for every option plus a case-specific overall rationale

• Local study-map skill anchors and the official study-guide reference on every item

• Offline Markdown review copies alongside instructor CSV files

• A reproducible ZIP, a validation report, and automated structural tests

EACH EXAM CONTAINS

• 18 questions on Design and implement an MLOps infrastructure

• 29 questions on Implement machine learning model lifecycle and operations