AI-102 Easy to Grasp
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| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Designing and Implementing a Microsoft Azure AI Solution |
| Exam Number: | AI-102 |
| Exam Duration: | 100-120 |
| Exam Format: | Case studies, Drag and drop, Multiple choice, Multiple response, Build/review solution scenarios |
| Passing Score: | 700 (out of 1000) |
| Available Languages: | Spanish (Latin America), Portuguese (Brazil), Japanese, English, French, Simplified Chinese, Korean, German |
| Real Exam Qty: | 40-60 (approximate range) |
| Related Certifications: | Microsoft Certified: Azure AI Fundamentals (AI-900) |
| Certificate Validity Period: | 1 year (renewable annually via Microsoft certification renewal assessment) |
| Exam Price: | USD 165 (varies by country/region) |
| Recommended Training: | Microsoft Learn AI-102 Learning Path Azure AI Engineer Associate Study Resources |
| Exam Registration: | Microsoft Certification Exam Registration (Pearson VUE) Microsoft Learn AI-102 Certification Page |
| Sample Questions: | ![]() |
| Exam Way: | Online proctored or onsite test center (Pearson VUE) |
| Pre Condition: | No formal prerequisites required, but familiarity with Azure fundamentals and AI/ML concepts is recommended |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/azure-ai-engineer/ |
| Section | Objectives |
|---|---|
| Plan and Manage an Azure AI Solution | - Manage security, compliance, and responsible AI - Plan solution requirements and architecture - Select appropriate Azure AI services |
| Implement Knowledge Mining and Document Intelligence | - Implement document intelligence solutions - Enrich and index data for search scenarios - Build Azure AI Search solutions |
| Implement Natural Language Processing Solutions | - Implement question answering and conversational AI - Translate and interpret language using Azure AI services - Analyze text using Azure AI Language |
| Implement Generative AI Solutions | - Integrate prompt engineering techniques - Build retrieval-augmented generation (RAG) solutions - Implement Azure OpenAI Service solutions |
| Implement Computer Vision Solutions | - Implement custom vision models - Extract information using OCR and form recognition - Analyze images and videos using Azure AI Vision |
You need to upload speech samples to a Speech Studio project. How should you upload the samples?
Correct Answer: A 🗳️
Explanation: Only visible for DumpsActual members. You can sign-up / login (it's free).
Select the answer that correctly completes the sentence.
Correct Answer:

Explanation:
In SQL, DML (Data Manipulation Language) statements include SELECT , INSERT , UPDATE , and DELETE . Often, you need to filter which rows are affected or returned. That filtering is done with the WHERE clause.
Let's review the options:
ALTER
Used in Data Definition Language (DDL), not DML.
Alters the structure of a database object (e.g., add/remove columns, modify constraints).
Not used to filter rows.
ON
Used in JOIN operations to specify the relationship between tables.
Does not specify row-level filtering criteria in general DML.
SET
Used in the UPDATE statement to assign new values to columns.
Does not specify which rows to update.
WHERE
Used in DML statements to specify criteria for rows that must match.
Examples:
SELECT * FROM Customers WHERE Country = ' USA ' ;
DELETE FROM Orders WHERE OrderDate < ' 2020-01-01 ' ;
UPDATE Products SET Price = Price * 1.1 WHERE CategoryID = 5;
Thus, the correct clause is WHERE.
The answer: WHERE
Microsoft References
SQL WHERE clause
SQL UPDATE with WHERE
SQL DELETE with WHERE
You successfully run the following HTTP request.
POST https://management.azure.com/subscriptions/18c51a87-3a69-47a8-aedc-a54745f708a1/resourceGroups
/RG1/providers/Microsoft.CognitiveServices/accounts/contosol/regenerateKey?api-version=2017-04-18 Body{ " keyName " : " Key2 " } What is the result of the request?
Correct Answer: A 🗳️
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You have data saved in the following format.
Which format was used?
Correct Answer: A 🗳️
Explanation: Only visible for DumpsActual members. You can sign-up / login (it's free).
You are building an Azure Cognitive Search custom skill.
You have the following custom skill schema definition.
For each of the following statements, select Yes if the statement. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Correct Answer:

Explanation:
Code Recap (Custom Skill JSON Schema)
{
" @odata.type " : " #Microsoft.Skills.Custom.WebApiSkill " ,
" description " : " My custom skill description " ,
" uri " : " https://contoso-webskill.azurewebsites.net/api/process " ,
" context " : " /document/organizations/* " ,
" inputs " : [
{
" name " : " companyName " ,
" source " : " /document/organizations/* "
}
],
" outputs " : [
{
" name " : " companyDescription "
}
]
}
Statement Analysis
CompanyDescription is available for indexing.
Yes.
The skill produces an output field called companyDescription . Outputs of a custom skill become part of the enrichment tree, which can then be projected into the search index or knowledge store.
The definition calls a web API as part of the enrichment process.
Yes.
This is a Web API skill ( @odata.type: #Microsoft.Skills.Custom.WebApiSkill ) with a uri pointing to
https://contoso-webskill.azurewebsites.net/api/process . This means an external web API is called to enrich data.
The enrichment step is called only for the first organization under /document/organizations .
No.
The context is set to " /document/organizations/* " , where the * means the skill runs for each element in the collection. It is not limited to the first element.
Final Answer
CompanyDescription is available for indexing # Yes
The definition calls a web API as part of the enrichment process # Yes
The enrichment step is called only for the first organization under /document/organizations # No Microsoft References Custom skills in Azure Cognitive Search Enrichment tree and skill context Reference:
https://docs.microsoft.com/en-us/azure/search/cognitive-search-output-field-mapping
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