Exam Name: Oracle AI Vector Search Professional
Certification Provider: Oracle
Corresponding Certification: Oracle Database 23ai
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Oracle 1Z0-184-25 Exam Overview:
| Certification Vendor: | Oracle |
|---|---|
| Exam Name: | Oracle AI Vector Search Professional |
| Exam Number: | 1Z0-184-25 |
| Available Languages: | English |
| Exam Format: | Multiple Choice |
| Related Certifications: | Oracle Database 23ai Certified Professional |
| Real Exam Qty: | 50 |
| Exam Price: | $245 USD |
| Certificate Validity Period: | 2 years |
| Exam Duration: | 90 minutes |
| Passing Score: | 68% |
| Sample Questions: | DOWNLOAD DEMO |
| Exam Way: | Online Proctored |
| Pre Condition: | Candidates should have basic familiarity with Python and AI/ML concepts. |
| Official Syllabus URL: | https://education.oracle.com/oracle-ai-vector-search-professional/pexam_1Z0-184-25 |
Oracle 1Z0-184-25 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Leveraging Related AI Capabilities | 20% | - Load and manage vector data using SQL Loader and Oracle Data Pump - Use Oracle GoldenGate for AI data replication - Understand Exadata AI Storage and Distributed AI Processing - Query data using natural language prompts with Select AI |
| Understand Vector Fundamentals | 20% | - Use Vector Data type for storing embeddings and enabling semantic queries - Use Vector Distance Functions and Metrics for AI vector search - Perform DML Operations on Vectors - Perform DDL Operations on Vectors |
| Performing Similarity Search | 15% | - Perform Multi-Vector similarity search for multi-document search - Perform Exact Similarity Search - Perform approximate similarity search using Vector Indexes |
| Using Vector Embeddings | 15% | - Generate Vector Embeddings using ONNX models in the database - Store and Manage Vector Embeddings - Generate Vector Embeddings using External APIs |
| Using Vector Indexes | 15% | - Use IVF Vector Index for search queries - Use HNSW Vector Index for search queries - Create Vector Indexes to speed up AI vector search |
| Building a RAG Application | 15% | - Implement RAG using PL/SQL - Understand RAG Architecture and Concepts - Implement RAG using Python |
1Z0-184-25 Exam FAQ — Read Before You Buy
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The official Oracle AI Vector Search Professional outline defines 6 domains. The leading three are Using Vector Indexes (15%), Understand Vector Fundamentals (20%), and Leveraging Related AI Capabilities (20%). The full list is in the topics section above, and iPassleader's 62 practice questions cover each one.
Three versions of the same study materials, offering three learning modes: a printable, expert-prepared PDF with free demo download and instant access; a Desktop Test Engine for Windows with customizable simulation and timed modes that works offline; and an Online Test Engine for any browser on Windows, Mac, Android, and iOS with test history and performance review. All 62 practice questions are identical across versions. Every purchase includes 365 days of free updates, a 50% renewal discount afterward, and unlimited computer installations.
Candidates should have basic familiarity with Python and AI/ML concepts. Since requirements change over time, confirm the latest on the official Oracle exam page before scheduling.
The 1Z0-184-25 exam is a Oracle certification exam validating the Oracle AI Vector Search Professional syllabus shown above. It belongs to these credential paths: Oracle Database 23ai Certified Professional. Candidates in 2026 prepare for it with iPassleader's 62 practice questions, available as a printable PDF, a Windows Desktop Test Engine, and an Online Test Engine — three versions of the same materials.
Online Proctored Register for the Oracle AI Vector Search Professional exam through these official channels:
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Oracle recommends these training resources for the Oracle AI Vector Search Professional exam:
Follow the training with steady self-testing — the 62 practice questions from iPassleader help you apply theory and fill any gaps the training leaves.
The Oracle AI Vector Search Professional exam contains 50 to complete within 90 minutes. Timed simulation in the iPassleader Desktop Test Engine teaches that rhythm before exam day does.
The Oracle AI Vector Search Professional exam requires 68% to pass, and registration costs $245 USD. A failed attempt means paying the same fee again — a readiness check with the iPassleader engines before booking is the cheaper option.
Oracle AI Vector Search Professional Sample Questions:
Which statement best describes the capability of Oracle Data Pump for handling vector data in thecontext of vector search applications?
- A. Because of the complexity of vector data, Data Pump requires a specialized plug-in to handle the export and import operations involving vector data types
- B. Data Pump provides native support for exporting and importing tables containing vector data types, facilitating the transfer of vector data for vector search applications
- C. Data Pump only exports and imports vector data if the vector embeddings are stored as BLOB (Binary Large Object) data types in the database
- D. Data Pump treats vector embeddings as regular text strings, which can lead to data corruption or loss of precision when transferring vector data for vector search
Correct Answer: B 🗳️
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A database administrator wants to change the VECTOR_MEMORY_SIZE parameter for a pluggable database (PDB) in Oracle Database 23ai. Which SQL command is correct?
- A. ALTER SYSTEM SET VECTOR_MEMORY_SIZE=1G SCOPE=SGA
- B. ALTER SYSTEM SET VECTOR_MEMORY_SIZE=1G SCOPE=BOTH
- C. ALTER SYSTEM RESET VECTOR_MEMORY_SIZE
- D. ALTER DATABASE SET VECTOR_MEMORY_SIZE=1G SCOPE=VECTOR
Correct Answer: B 🗳️
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An application needs to fetch the top-3 matching sentences from a dataset of books while ensuring a balance between speed and accuracy. Which query structure should you use?
- A. Approximate similarity search with the VECTOR_DISTANCE function
- B. Multivector similarity search with approximate fetching and target accuracy
- C. A combination of relational filters and similarity search
- D. Exact similarity search with Euclidean distance
Correct Answer: A 🗳️
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Which function should you use to determine the storage format of a vector?
- A. VECTOR_DIMENSION_FORMAT
- B. VECTOR_NORM
- C. VECTOR_EMBEDDING
- D. VECTOR_CHUNKS
Correct Answer: A 🗳️
A machine learning team is using IVF indexes in Oracle Database 23ai to find similar images in a large dataset. During testing, they observe that the search results are often incomplete, missing relevant images. They suspect the issue lies in the number of partitions probed. How should they improve the search accuracy?
- A. Re-create the index with a higher EFCONSTRUCTION value
- B. Change the index type to HNSW for better accuracy
- C. Add the TARGET_ACCURACY clause to the query with a higher value for the accuracy
- D. Increase the VECTOR_MEMORY_SIZE initialization parameter
Correct Answer: C 🗳️
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