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Oracle 1z0-1122-26 Exam Syllabus Topics:

Section	Objectives
OCI Generative AI and Oracle Database AI Capabilities	- Oracle AI Database 1. Vector database concepts 2. AI capabilities in Oracle Database - AI Application Frameworks 1. Language frameworks 2. Retrieval and AI application concepts - OCI Generative AI 1. Generative AI models and applications 2. OCI Generative AI services
Generative AI and Large Language Models	- Generative AI Fundamentals 1. Generative AI use cases 2. Generative AI concepts and capabilities - Large Language Models 1. LLM fundamentals 2. Language models and generative AI applications
Oracle AI and Machine Learning Services	- OCI Machine Learning Services 1. OCI Data Science and machine learning workflows 2. Machine learning capabilities in OCI - Oracle AI Stack 1. AI infrastructure 2. AI data and machine learning services - OCI AI Services 1. Document Understanding 2. Language 3. Vision 4. Speech
Artificial Intelligence and Machine Learning Fundamentals	- Artificial Intelligence Concepts 1. AI fundamentals and terminology 2. AI use cases and applications - Machine Learning Fundamentals 1. Machine learning models and architectures 2. Supervised and unsupervised learning - Deep Learning Fundamentals 1. Convolutional and sequence models 2. Neural networks

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Oracle Cloud Infrastructure 2026 AI Foundations Associate Sample Questions (Q19-Q24):

NEW QUESTION # 19
What is the primary benefit of using Oracle Cloud Infrastructure Supercluster for AI workloads?

A. It offers seamless integration with social media platforms.
B. It delivers exceptional performance and scalability for complex AI tasks.
C. It provides a cost-effective solution for simple AI tasks.
D. It is ideal for tasks such as text-to-speech conversion.

Answer: B

Explanation:
Oracle Cloud Infrastructure Supercluster is designed to deliver exceptional performance and scalability for complex AI tasks. The primary benefit of this infrastructure is its ability to handle demanding AI workloads, offering high-performance computing (HPC) capabilities that are crucial for training large-scale AI models and processing massive datasets. The architecture of the Supercluster ensures low-latency networking, efficient resource allocation, and high-throughput processing, making it ideal for AI tasks that require significant computational power, such as deep learning, data analytics, and large-scale simulations.

NEW QUESTION # 20
Which is NOT a capability of OCI Vision ' s image analysis?

A. Assigning classification labels to images
B. Translating text in images to another language
C. Locating and extracting text in images
D. Object detection with bounding boxes

Answer: B

Explanation:
OCI Vision ' s image analysis capabilities include locating and extracting text from images, assigning classification labels to images, and detecting objects with bounding boxes. However, translating text in images to another language is not a capability of OCI Vision ' s image analysis. This functionality typically requires an additional layer of processing, such as integration with a language translation service, which is beyond the scope of OCI Vision ' s core image analysis features.
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NEW QUESTION # 21
You are training a logistic regression model to classify emails as spam or not spam. The model is currently classifying too many emails as spam. What would you do to adjust the model?

A. Increase the threshold value for classification.
B. Increase the regularization parameter.
C. Decrease the number of iterations.
D. Decrease the weight of the feature representing the presence of certain keywords.

Answer: A

Explanation:
In binary classification, the decision threshold determines how much predicted probability is required before an observation is assigned to the positive class. Here, spam represents the positive class, and the model is producing too many spam classifications, indicating excessive positive predictions or false positives.
Increasing the classification threshold requires a higher predicted probability before an email is labeled as spam, reducing the number of positive classifications. Oracle Machine Learning documentation defines the probability threshold as the decision point used for binary classification and explains that changing this threshold changes true-positive and false-positive behavior. Oracle Docs Altering individual feature weights, iteration counts, or regularization affects model training rather than directly controlling the classification decision boundary. Therefore, increasing the classification threshold is the most appropriate adjustment.

NEW QUESTION # 22
What can Oracle Cloud Infrastructure Document Understanding NOT do?

A. Generate transcript from documents
B. Extract text from documents
C. Classify documents into different types
D. Extract tables from documents

Answer: A

Explanation:
Oracle Cloud Infrastructure (OCI) Document Understanding service offers several capabilities, including extracting tables, classifying documents, and extracting text. However, it does not generate transcripts from documents. Transcription typically refers to converting spoken language into written text, which is a function associated with speech-to-text services, not document understanding services. Therefore, generating a transcript is outside the scope of what OCI Document Understanding is designed to do .

NEW QUESTION # 23
What is the primary benefit of using Oracle Cloud Infrastructure Supercluster for AI workloads?

A. It offers seamless integration with social media platforms.
B. It delivers exceptional performance and scalability for complex AI tasks.
C. It provides a cost-effective solution for simple AI tasks.
D. It is ideal for tasks such as text-to-speech conversion.

Answer: B

NEW QUESTION # 24
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