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Oracle 1z0-1122-23 Exam Overview:
| Certification Vendor: | Oracle |
|---|---|
| Exam Name: | Oracle Cloud Infrastructure AI Foundations Associate (1Z0-1122-23) |
| Exam Number: | 1Z0-1122-23 |
| Exam Format: | Multiple choice, Multiple response |
| Available Languages: | English |
| Exam Duration: | 90 minutes |
| Sample Questions: |  |
| Exam Way: | Online proctored exam |
| Pre Condition: | None |
Oracle 1z0-1122-23 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| OCI AI Services | - OCI Vision service capabilities - OCI Speech service capabilities - OCI Language service capabilities |
| AI Infrastructure and Security on OCI | - Security, governance, and responsible AI principles - Compute and GPU resources for AI workloads |
| Data and Machine Learning on OCI | - OCI Data Science service overview - ML workflow and lifecycle concepts |
| Generative AI on Oracle Cloud Infrastructure | - Foundation models and use cases - Prompt engineering concepts |
| Artificial Intelligence Fundamentals | - Machine learning and deep learning basics - Core AI concepts and terminology |
Common Questions About the Oracle 1z0-1122-23 Exam
The 1z0-1122-23 exam, officially known as Oracle Cloud Infrastructure 2023 AI Foundations Associate, is the Oracle test that leads to the Oracle Cloud Infrastructure AI Foundations Associate certification at the Associate level. Passing it validates the skills employers expect from a certified professional.
Oracle recommends the following training options for Oracle Cloud Infrastructure 2023 AI Foundations Associate candidates:
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The official Oracle Cloud Infrastructure 2023 AI Foundations Associate outline is organized into 5 domains. The first three are:
- Data and Machine Learning on OCI
- OCI AI Services
- Generative AI on Oracle Cloud Infrastructure
See the complete exam topics section above for the full outline and the weighting of every domain.
Oracle Cloud Infrastructure 2023 AI Foundations Associate Sample Questions:
Question 1
Which capability is supported by Oracle Cloud Infrastructure Language service?
A. Converting text into images
B. Detecting objects and scenes in Images
C. Analyzing text to extract structured information like sentiment or entities
D. Translating speech into text
Question 2
What is the purpose of fine-tuning Large Language Models?
A. To Increase the complexity of the model architecture
B. To reduce the number of parameters in the model
C. To specialize the model's capabilities for specific tasks
D. To prevent the model from overfitting
Question 3
Which type of machine learning is used to understand relationships within data and is not focused on making predictions or classifications?
A. Supervised learning
B. Reinforcement learning
C. Active learning
D. Unsupervised learning
Solutions:
| Question 1 Answer: C | Question 2 Answer: C | Question 3 Answer: D |
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