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Updated: Sep 09, 2026
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| Certification Vendor: | Oracle |
|---|---|
| Exam Name: | Oracle AI Database Foundations Associate |
| Exam Number: | 1Z0-1195-26 |
| Real Exam Qty: | 40 |
| Exam Duration: | 60 minutes |
| Passing Score: | 65% |
| Certificate Validity Period: | 10 years |
| Related Certifications: | Oracle AI Database Certified Foundations Associate Oracle Data Platform 2025 Certified Foundations Associate |
| Exam Price: | Free |
| Available Languages: | Japanese, English |
| Exam Format: | Multiple Choice, Online Proctored |
| Sample Questions: | Oracle 1z0-1195-26 Sample Questions |
| Exam Way: | Online proctored exam; Japanese delivery is also available. |
| Pre Condition: | No prerequisite exam or prior certification is required. |
| Official Syllabus URL: | https://www.oracle.com/education/certification/ |
| Section | Objectives |
|---|---|
| Topic 1: Identifying Oracle AI Database 26ai Strategy and Autonomous AI Database Basics | - Describe Autonomous AI Database characteristics, offerings, and deployment choices - Explain modern data characteristics and the Oracle AI Database 26ai converged strategy - Create an Autonomous AI Database Serverless instance for a basic workload |
| Topic 2: Implementing Select AI and AI Vector Search in Autonomous AI Database | - Apply AI Vector Search to combined semantic and business-data search scenarios - Describe Select AI in Autonomous AI Database - Determine how AI Vector Search supports GenAI pipelines and RAG |
| Topic 3: Building Low-Code Applications and Agentic AI | - Choose the appropriate Agent Factory capability for a no-code AI agent use case - Describe Oracle APEX as Oracle's low-code platform |
| Topic 4: Working with AI and Vector Foundations | - Explain vectors, embeddings, and the Oracle VECTOR data type - Apply vector distance and indexing concepts to similarity search needs - Describe AI, AGI, and machine learning foundations |
| Topic 5: Using Oracle Database Actions and Data Studio Tools | - Apply Data Studio capabilities to data discovery, integration, analysis, and sharing tasks - Describe Database Actions and core development tools |
| Topic 6: Working with JSON and Graph in Oracle AI Database | - Describe core graph concepts and graph analytic capabilities - Explain JSON and Oracle AI Database JSON capabilities - Distinguish when graph capabilities and Property Graph Views fit a business use case |
Question 1
Which graph analytics capability is commonly used to rank important vertices based on their relationships?
A. Vector distance metric
B. Private endpoint access
C. JSON Duality View
D. PageRank
Question 2
What is an embedding in the context of AI Vector Search?
A. A graph edge label stored in a property graph
B. A maintenance schedule attached to a database instance
C. A sequence of numbers that represents semantic content
D. A text-only backup of a JSON collection
Question 3
What does Oracle mean by a converged database strategy?
A. One reporting tool replaces SQL, JSON APIs, and graph queries.
B. One storage tier is reserved only for AI workloads and vector indexes.
C. One application server manages all databases without schema changes.
D. One database architecture supports multiple data types and workloads together.
Question 4
A team already uses Database Actions and now needs the part of the environment focused on discovery, load, integration, and cataloging. Which workspace should they open?
A. Graph Studio
B. SQL Worksheet
C. Data Studio
D. Database Users
Question 5
Which set is included in the Oracle AI Database 26ai converged approach?
A. Relational, XML, spatial, external-only graph stores, and separate vector databases
B. JSON, document APIs, storage buckets, monitoring, and billing
C. Relational, JSON, vector, object-only files, and separate document stores
D. Relational, JSON, vector, graph, and spatial
Solutions:
| Question 1 Answer: D | Question 2 Answer: C | Question 3 Answer: D | Question 4 Answer: C | Question 5 Answer: D |
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