AI-102 [AI Engineer] Practice Test: 1500 Certified Questions
4 days ago
IT & Software
[100% OFF] AI-102 [AI Engineer] Practice Test: 1500 Certified Questions

Covers vision solutions, language understanding, bots, search, integration, security and lifecycle governance

0
2,551 students
Certificate
English
$0$44.99
100% OFF

Course Description

Artificial intelligence systems are no longer theoretical — they are visual, conversational, searchable, secured, and continuously governed. The AI-102 Azure AI Engineer exam tests whether you truly understand how to build production-ready AI solutions instead of merely experimenting with models. That is why this practice test delivers 1,500 professionally structured questions across six applied domains, teaching real AI engineering inside Azure’s ecosystem.

We begin with Cognitive Vision Services & Intelligent Image Processing, exploring how image data becomes structured insight through object detection, OCR, spatial analysis, custom models, and visual telemetry. You will understand how cameras, forms, and inspections can fuel intelligent automation.

The second section, Language Understanding, NLP Models & Conversational AI Logic, focuses on how Azure processes human language. You will study sentiment analysis, translation workflows, intent prediction, entity extraction, and large language model integration — including how LLMs adapt to user context.

In Bot Framework, Conversational Flows & User Interaction Design, you will examine how enterprise-grade bots are built using dialogs, adaptive logic, APIs, authentication flows, and backend integration. Real-world design patterns reveal how bots automate operations and customer interaction.

Next, Azure Cognitive Search, Indexing Logic & Retrieval Intelligence explains how unstructured data is transformed into enterprise knowledge through skillsets, vector search, semantic ranking, embeddings, enrichment layers, metadata extraction and search-driven intelligence.

Security becomes essential in Security Enforcement, Identity Integration & AI Risk Control, where you analyze encryption methods, access scopes, Zero Trust boundaries, identity-based restrictions, responsible data handling, and model protection across services.

Finally, AI Solution Lifecycle, Deployment Patterns & Governance Models explores CI/CD deployment strategies, telemetry dashboards, rollback logic, model registry, cost control, and governance rules that turn AI into reliable, trustworthy systems.

Each domain contains 250 unique questions — and every test can be retaken multiple times to reinforce learning and support deep understanding. Whether your goal is certification, cloud engineering skills, AI development, or professional confidence, this course helps you think like an AI engineer, not just prepare for the exam.

Your next step into applied artificial intelligence begins here.

Similar Courses