AI, AI-103, Microsoft Certification

AI-103: Develop AI Apps and Agents on Azure – Practice Exam #1 (30 questions with answers)

30 Practice Questions with Answers and Explanations

Question 1

You are building a Retrieval-Augmented Generation (RAG) solution that must provide semantically relevant answers from enterprise documents.

Which Azure capability should you use to store and search vector embeddings?

A. Azure Monitor
B. Azure Firewall
C. Azure AI Search
D. Azure Policy

Answer

C. Azure AI Search

Explanation

Azure AI Search supports:

  • Vector indexing
  • Semantic search
  • Hybrid retrieval
  • Embedding-based similarity search

These features are core components of modern RAG architectures.

Question 2

You need to ensure that Azure AI services authenticate securely without storing secrets in application code.

Which feature should you implement?

A. Anonymous access
B. Managed identities
C. Shared admin passwords
D. Public API endpoints

Answer

B. Managed identities

Explanation

Managed identities provide secure service-to-service authentication without embedding credentials in code or configuration files.

Question 3

You need an AI system to identify names of companies, people, and locations from contracts.

Which capability should you use?

A. OCR
B. Translation
C. Object detection
D. Named Entity Recognition

Answer

D. Named Entity Recognition

Explanation

Named Entity Recognition (NER) extracts structured entities such as:

  • People
  • Organizations
  • Locations
  • Dates

from textual content.

Question 4

MULTIPLE ANSWER — Which capabilities are commonly included in a RAG ingestion pipeline? (Choose THREE)

A. Chunking
B. Embedding generation
C. Vector indexing
D. DHCP leasing
E. VLAN routing

Answer

A. Chunking
B. Embedding generation
C. Vector indexing

Explanation

Typical RAG ingestion workflows include:

  • Splitting documents into chunks
  • Generating embeddings
  • Storing vectors in a searchable index

Question 5

You need to extract text from scanned paper forms.

Which capability should you implement FIRST?

A. Semantic ranking
B. OCR
C. Sentiment analysis
D. Face detection

Answer

B. OCR

Explanation

OCR (Optical Character Recognition) converts image-based text into machine-readable text.

Question 6

MATCHING — Match the service to its primary purpose.

ServicePurpose
Azure AI Vision?
Azure OpenAI Service?
Azure AI Document Intelligence?

Options:

  • OCR and structured document extraction
  • Image analysis
  • Embedding generation and generative AI

Answer

ServicePurpose
Azure AI VisionImage analysis
Azure OpenAI ServiceEmbedding generation and generative AI
Azure AI Document IntelligenceOCR and structured document extraction

Question 7

You need an AI chatbot to retrieve current company policies at runtime before answering users.

Which architecture should you implement?

A. RAG architecture
B. Static FAQ architecture
C. Traditional ETL pipeline
D. Relational replication architecture

Answer

A. RAG architecture

Explanation

RAG retrieves trusted external content during prompt execution to ground responses and reduce hallucinations.

Question 8

Which parameter MOST directly controls randomness in a large language model response?

A. OCR confidence
B. Embedding dimension
C. Temperature
D. Chunk overlap

Answer

C. Temperature

Explanation

Temperature controls response variability:

  • Lower temperature = deterministic
  • Higher temperature = creative/random

Question 9

You are building an AI system that must process:

  • Text
  • Images
  • Audio

What type of AI pipeline is this?

A. Relational pipeline
B. Lexical pipeline
C. Structured query pipeline
D. Multimodal pipeline

Answer

D. Multimodal pipeline

Question 10

FILL IN THE BLANK

The numeric vector representation of semantic meaning is called an __________.

Answer

embedding

Question 11

You need to preserve document structure, headings, and tables for downstream LLM reasoning.

Which format is BEST suited?

A. Binary serialization
B. JPEG
C. Markdown
D. CSV only

Answer

C. Markdown

Explanation

Markdown preserves:

  • Hierarchy
  • Lists
  • Tables
  • Readability

which improves semantic chunking and retrieval quality.

Question 12

You need to identify emotional tone within customer reviews.

Which capability should you use?

A. Sentiment analysis
B. OCR
C. Object tracking
D. Pose estimation

Answer

A. Sentiment analysis

Question 13

HOTSPOT — Select the BEST capability for each requirement.

RequirementCapability
Detect objects within images?
Extract invoice totals?
Generate semantic vectors?

Options:

  • Embeddings
  • Object detection
  • Invoice extraction model

Answer

RequirementCapability
Detect objects within imagesObject detection
Extract invoice totalsInvoice extraction model
Generate semantic vectorsEmbeddings

Question 14

You need a retrieval system that combines:

  • Keyword matching
  • Semantic similarity

Which search approach should you use?

A. OCR search
B. Hybrid search
C. Sequential search
D. Static indexing

Answer

B. Hybrid search

Question 15

You need an AI agent to execute workflows such as creating support tickets and querying databases.

Which feature enables this behavior?

A. Layout analysis
B. Function calling
C. OCR preprocessing
D. Image segmentation

Answer

B. Function calling

Question 16

MULTIPLE ANSWER — Which factors improve RAG retrieval quality? (Choose THREE)

A. Semantic chunking
B. Metadata enrichment
C. Hybrid retrieval
D. Removing embeddings
E. Disabling ranking

Answer

A. Semantic chunking
B. Metadata enrichment
C. Hybrid retrieval

Question 17

You need to automatically classify support tickets into categories such as:

  • Billing
  • Technical support
  • Sales

Which capability should you use?

A. Text classification
B. OCR
C. Face recognition
D. Image tagging

Answer

A. Text classification

Question 18

You are implementing monitoring and telemetry for AI APIs.

Which Azure service should you use?

A. Azure Bastion
B. Azure DNS
C. Azure Monitor
D. Azure Route Server

Answer

C. Azure Monitor

Question 19

You need to preserve reading order and table structure during document extraction.

Which capability is MOST important?

A. OCR only
B. Layout analysis
C. Translation
D. Key phrase extraction

Answer

B. Layout analysis

Question 20

DRAG AND DROP — Match the concept to the correct description.

ConceptDescription
Grounding?
Chunking?
Semantic search?

Options:

  • Splitting documents into smaller sections
  • Searching by contextual meaning
  • Providing trusted context to an LLM

Answer

ConceptDescription
GroundingProviding trusted context to an LLM
ChunkingSplitting documents into smaller sections
Semantic searchSearching by contextual meaning

Question 21

You need to orchestrate AI workflows using a low-code solution.

Which Azure service should you use?

A. Azure Firewall
B. Azure Backup
C. Azure Logic Apps
D. Azure VPN Gateway

Answer

C. Azure Logic Apps

Question 22

You need an AI application to summarize lengthy legal documents.

Which capability should you implement?

A. Object detection
B. Text summarization
C. OCR masking
D. Image tagging

Answer

B. Text summarization

Question 23

MULTIPLE ANSWER — Which are benefits of grounding AI responses? (Choose THREE)

A. Reduced hallucinations
B. Improved factual accuracy
C. Better enterprise relevance
D. Elimination of embeddings
E. Removal of indexes

Answer

A. Reduced hallucinations
B. Improved factual accuracy
C. Better enterprise relevance

Question 24

You need to build an AI assistant that accepts spoken commands.

Which capability converts speech into text?

A. Speech-to-text
B. OCR
C. Image captioning
D. Object segmentation

Answer

A. Speech-to-text

Question 25

FILL IN THE BLANK

A retrieval system that combines vector similarity with keyword matching is called __________ search.

Answer

hybrid

Question 26

You need to extract structured fields such as:

  • Invoice number
  • Total amount
  • Vendor name

from scanned invoices.

Which service is MOST appropriate?

A. Azure AI Vision
B. Azure AI Document Intelligence
C. Azure Load Balancer
D. Azure Traffic Manager

Answer

B. Azure AI Document Intelligence

Question 27

You need to retrieve semantically similar documents even when queries use different wording.

Which capability enables this?

A. Vector search
B. IP routing
C. DNS resolution
D. Blob replication

Answer

A. Vector search

Question 28

You need to ensure users retrieve only authorized documents from an enterprise AI search solution.

Which approach should you implement?

A. Anonymous indexes
B. Shared admin credentials
C. Public storage access
D. Security trimming with RBAC

Answer

D. Security trimming with RBAC

Question 29

You are building a computer vision solution that identifies vehicles and pedestrians within traffic footage.

Which capability should you use?

A. OCR
B. Sentiment analysis
C. Object detection
D. Translation

Answer

C. Object detection

Question 30

You need to improve retrieval precision by storing additional contextual information such as:

  • Department
  • Document type
  • Security classification

What technique should you implement?

A. Metadata enrichment
B. OCR suppression
C. Token deletion
D. Vector truncation

Answer

A. Metadata enrichment

Explanation

Metadata enrichment improves:

  • Filtering
  • Relevance
  • Security trimming
  • Search precision

within enterprise AI retrieval systems.

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