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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 |
| Exam Price: | USD $245 |
| Passing Score: | 68% |
| Related Certifications: | Oracle Database Certification |
| Exam Format: | Multiple Choice |
| Real Exam Qty: | 50 |
| Certificate Validity Period: | Cloud Recertification Policy (Retires May 29, 2026) |
| Available Languages: | English |
| Exam Duration: | 90 minutes |
| Recommended Training: | Become an Oracle AI Vector Search Professional |
| Exam Registration: | Oracle University Exam Registration |
| Sample Questions: |  |
| Exam Way: | Online proctored or onsite testing center |
| Pre Condition: | Basic familiarity with Python, AI/ML concepts, and Oracle database knowledge |
| Official Syllabus URL: | https://education.oracle.com/products/pexam_1Z0-184-25 |
Oracle 1Z0-184-25 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Using Vector Indexes | 15% | - Performance vs accuracy trade-offs - Index types: HNSW, IVF - Create, manage and optimize vector indexes |
| Topic 2: Leveraging Related AI Capabilities | 10% | - Load and manage vector data - Exadata AI Storage and GoldenGate integration - Select AI for natural language queries |
| Topic 3: Performing Similarity Search | 15% | - Exact and approximate similarity search - Combine vector search with SQL queries - Multi-vector and multi-document search |
| Topic 4: Understand Vector Fundamentals | 20% | - VECTOR data type usage and storage - Vector distance functions and metrics - Vector concepts and differences from traditional search |
| Topic 5: Using Vector Embeddings | 15% | - Store and manage embeddings - Embedding generation workflows - Generate embeddings inside/outside database |
| Topic 6: Building a RAG Application | 25% | - RAG architecture and components - Integrate with AI services - Implement with PL/SQL and Python |
1Z0-184-25 FAQ — Efficient Preparation Starts Here
Basic familiarity with Python, AI/ML concepts, and Oracle database knowledge Eligibility rules do change, so confirm the current requirements on the official page (official 1Z0-184-25 exam page) before booking.
90 minutes for 50 questions. Efficiency beats exhaustion: the ExamTorrent software version simulates the real test scene and scores your performance, so every practice hour moves you forward.
Yes:
Training gives knowledge direction; practice gives it proof. Follow courses with the 62 practice questions for the Oracle AI Vector Search Professional to measure real progress.
Delivery and payment are both safe: we support credit card payment, your information is protected by a strict system, and the product emails automatically within a minute of purchase — unlimited devices, 7*24 support if nothing arrives within 2 hours. If you fail the corresponding 1Z0-184-25 exam within 60 days of purchase, we refund in full: provide a scanned enrollment slip plus the official Score Report PDF within 2 days of the exam, processed within 7 days. Excluded: exams within 3 days of purchase, candidate names that don't match the payer, and free or expired products. Or exchange for two equal-value products free.
USD $245 per attempt, 68% to pass. Since a retake costs the full fee, prepare with direction: the 62 practice questions from ExamTorrent focus your effort where the exam points are.
The Oracle AI Vector Search Professional is Oracle's certification exam for Oracle AI Vector Search Certified Professional, at the Professional level. It validates applied skills employers hire for — a credential worth the effort. Related credentials include Oracle Database Certification.
The Oracle AI Vector Search Professional blueprint covers 6 domains — including Leveraging Related AI Capabilities (10%), Using Vector Indexes (15%), Performing Similarity Search (15%). The weightings are your efficiency map: heavy domains first. Every subtopic appears in the outline above.
Through the vendor's official registration channels:
The Oracle AI Vector Search Professional is delivered Online proctored or onsite testing center, so pick the arrangement that suits you when booking.
Yes — download the free Oracle AI Vector Search Professional demo and judge the question quality before paying. Every purchase stays valid for 365 days with free updates throughout, renewable afterward at 50% off.
Oracle AI Vector Search Professional Sample Questions:
How is the security interaction between Autonomous Database and OCI Generative AI managed in the context of Select AI?
- A. By establishing a secure VPN tunnel between the Autonomous Database and OCI Generative AI service
- B. By utilizing Resource Principals, which grant the Autonomous Database instance access to OCI Generative AI without exposing sensitive credentials
- C. By requiring users to manually enter their OCI API keys each time they execute a natural language query
- D. By encrypting all communication between the Autonomous Database and OCI Generative AI using TLS/SSL protocols
Correct Answer: B 🗳️
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You are tasked with finding the closest matching sentences across books, where each book has multiple paragraphs and sentences. Which SQL structure should you use?
- A. FETCH PARTITIONS BY clause
- B. A nested query with ORDER BY
- C. GROUP BY with vector operations
- D. Exact similarity search with a single query vector
Correct Answer: B 🗳️
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What is the purpose of the VECTOR_DISTANCE function in Oracle Database 23ai similarity search?
- A. To fetch rows that match exact vector embeddings
- B. To create vector indexes for efficient searches
- C. To calculate the distance between vectors using a specified metric
- D. To group vectors by their exact scores
Correct Answer: C 🗳️
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Which is NOT a feature or capability related to AI and Vector Search in Exadata?
- A. AI Smart Scan
- B. Loading Vector Data using SQL*Loader
- C. Vector Replication with GoldenGate
- D. Native Support for Vector Search Only within the Database Server
Correct Answer: D 🗳️
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Which SQL statement correctly adds a VECTOR column named "v" with 4 dimensions and FLOAT32 format to an existing table named "my_table"?
- A. ALTER TABLE my_table ADD (v VECTOR(4, FLOAT32))
- B. ALTER TABLE my_table MODIFY (v VECTOR(4, FLOAT32))
- C. UPDATE my_table SET v = VECTOR(4, FLOAT32)
- D. ALTER TABLE my_table ADD v VECTOR(4, FLOAT32)
Correct Answer: A 🗳️
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