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Oracle 1z0-1122-26 Exam Syllabus Topics:

Section	Weight	Objectives
Deep Learning Foundations	15%	- Deep Learning and neural networks 1. Convolutional Neural Networks (CNN) architectures 2. Recurrent Neural Networks, LSTMs, and sequence models
OCI Generative AI and Oracle 23ai	10%	- OCI Generative AI Service features 1. Generative AI capabilities on OCI 2. Oracle 23ai Vector Database integration
Machine Learning Foundations	15%	- Machine Learning fundamentals 1. Reinforcement learning basics and model evaluation concepts 2. Unsupervised learning: clustering and dimensionality reduction 3. Supervised learning: regression and classification
Generative AI and Large Language Models	15%	- Generative AI concepts 1. Transformers, prompt engineering, and fine-tuning 2. Embeddings, Retrieval-Augmented Generation (RAG), and LLMs
AI Foundations	10%	- Artificial Intelligence basics and terminology 1. AI applications, use cases, and responsible AI principles 2. AI, Machine Learning, and Deep Learning relationship
OCI AI Portfolio	15%	- Overview of OCI AI offerings 1. AI Services, ML Services, and AI Infrastructure overview 2. OCI Data Science and GPU-based compute infrastructure
Introduction to OCI AI Services	20%	- OCI AI Service APIs 1. OCI Language, Vision, Speech, and Document Understanding services 2. OCI Select AI and AI service use cases

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Oracle Cloud Infrastructure 2026 AI Foundations Associate Sample Questions (Q45-Q50):

NEW QUESTION # 45
Lisa is working on a project that involves transcribing thousands of audio files stored in Oracle Cloud. She wants to process multiple files efficiently instead of transcribing them one by one. Which OCI Speech feature should Lisa use?

A. Confidence scoring
B. Batch support
C. Timestamping
D. Profanity filtering

Answer: B

Explanation:
OCI Speech supports batch transcription for efficiently processing prerecorded media. Lisa ' s key requirement is to process thousands of audio files without manually handling them individually. Oracle documentation explicitly identifies OCI Speech as supporting both real-time and batch transcription, while the OCI Speech documentation includes transcription jobs and large batch jobs among its supported workflows.
Oracle Docs Batch support therefore directly addresses high-volume processing of stored audio. Confidence scoring measures the service ' s certainty about recognized speech, timestamping associates transcript content with positions in the source recording, and profanity filtering controls how offensive language is represented.
Those capabilities enhance transcription output but do not provide the required multi-file processing mechanism. Consequently, Batch support is the appropriate OCI Speech capability for scalable transcription of Lisa ' s collection of audio files.

NEW QUESTION # 46
Which feature is NOT available as part of OCI Speech capabilities?

A. Transcribes audio and video files into text
B. Supports multiple languages including English, Spanish, and Portuguese
C. Uses extensive data science experience to operate
D. Provides timestamped, grammatically accurate transcriptions

Answer: C

Explanation:
OCI Speech capabilities are designed to be user-friendly and do not require extensive data science experience to operate. The service provides features such as transcribing audio and video files into text, offering grammatically accurate transcriptions, supporting multiple languages, and providing timestamped outputs.
These capabilities are built to be accessible to a broad range of users, making speech-to-text conversion seamless and straightforward without the need for deep technical expertise.

NEW QUESTION # 47
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 is ideal for tasks such as text-to-speech conversion.
D. It provides a cost-effective solution for simple AI tasks.

Answer: B

NEW QUESTION # 48
What is the purpose of the model catalog in OCI Data Science?

A. To deploy models as HTTP endpoints
B. To create and switch between different environments
C. To provide a preinstalled open source library
D. To store, track, share, and manage models

Answer: D

Explanation:
The primary purpose of the model catalog in OCI Data Science is to store, track, share, and manage machine learning models. This functionality is essential for maintaining an organized repository where data scientists and developers can collaborate on models, monitor their performance, and manage their lifecycle. The model catalog also facilitates model versioning, ensuring that the most recent and effective models are available for deployment. This capability is crucial in a collaborative environment where multiple stakeholders need access to the latest model versions for testing, evaluation, and deployment.

NEW QUESTION # 49
What is a key advantage of using dedicated AI clusters in the OCI Generative AI service?

A. They are free of charge for all users.
B. They provide faster internet connection speeds.
C. They allow access to unlimited database resources.
D. They provide high performance compute resources for fine-tuning tasks.

Answer: D

Explanation:
The primary advantage of using dedicated AI clusters in the Oracle Cloud Infrastructure (OCI) Generative AI service is the provision of high-performance compute resources that are specifically optimized for fine-tuning tasks. Fine-tuning is a critical step in the process of adapting pre-trained models to specific tasks, and it requires significant computational power. Dedicated AI clusters in OCI are designed to deliver the necessary performance and scalability to handle the intense workloads associated with fine-tuning large language models (LLMs) and other AI models, ensuring faster processing and more efficient training.

NEW QUESTION # 50
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