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Oracle 1z0-1195-26 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Identifying Oracle AI Database 26ai Strategy and Autonomous AI Database Basics | - Explain modern data characteristics and the Oracle AI Database 26ai converged strategy - Create an Autonomous AI Database Serverless instance for a basic workload - Describe Autonomous AI Database characteristics, offerings, and deployment choices |
| 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 |
| Working with JSON and Graph in Oracle AI Database | - Explain JSON and Oracle AI Database JSON capabilities - Describe core graph concepts and graph analytic capabilities - Distinguish when graph capabilities and Property Graph Views fit a business use case |
| Implementing Select AI and AI Vector Search in Autonomous AI Database | - Apply AI Vector Search to combined semantic and business-data search scenarios - Determine how AI Vector Search supports GenAI pipelines and RAG - Describe Select AI in Autonomous AI Database |
| Building Low-Code Applications and Agentic AI | - Describe Oracle APEX as Oracle's low-code platform - Choose the appropriate Agent Factory capability for a no-code AI agent use case |
| Using Oracle Database Actions and Data Studio Tools | - Describe Database Actions and core development tools - Apply Data Studio capabilities to data discovery, integration, analysis, and sharing tasks |
Oracle AI Database Foundations Associate Sample Questions:
Question #1
Which output can Select AI deliver to an application?
A. A result set, a narrative, or the SQL
B. A JSON export file generated from a collection table
C. A maintenance recommendation generated from patch history
D. A graph visualization generated from schema relationships
Question #2
Which statement describes Artificial Intelligence?
A. Systems replace databases by storing all data as graphs
B. Systems use data and algorithms to perform tasks that normally require human intelligence
C. Systems are identical to AGI in all current enterprise products
D. Systems eliminate the need for training data in every use case
Question #3
In a property graph, what are vertices and edges?
A. Vertices are JSON collections, and edges are maintenance policies
B. Vertices are storage partitions, and edges are encryption keys
C. Vertices represent entities, and edges represent relationships between them
D. Vertices are path lengths and edges are SQL functions
Question #4
A recruiting application must find the top job postings that semantically match a candidate's resume, but only in the candidate's city. How should the application meet this requirement?
A. Export all job postings to a separate vector platform and remove city filtering
B. Use Early maintenance so results are ranked sooner
C. Replace job descriptions with graph edge labels only
D. Use one SQL query that combines relational filters with vector distance ordering
Question #5
Which JSON feature helps represent repeating child data inside one document?
A. A flat property list with each child stored as a separate document
B. A scalar property that stores one child value
C. A document identifier that points to an external table only
D. Arrays and nested objects
Solutions:
| Question #1 Correct Answer: A | Question #2 Correct Answer: B | Question #3 Correct Answer: C | Question #4 Correct Answer: D | Question #5 Correct Answer: D |


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