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Oracle 1z0-1122-26 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Intro to OCI AI Services	20%	- OCI Speech - OCI Language - OCI Vision - OCI Document Understanding
Topic 2: Intro to ML Foundations	15%	- Discuss Supervised Learning Fundamentals 1. Regression 2. Classification - Explain Machine Learning Basics - Discuss Unsupervised Learning Fundamentals - Discuss Reinforcement Learning Fundamentals
Topic 3: Get started with OCI AI Portfolio	15%	- Discuss OCI AI Infrastructure Overview - Discuss OCI ML Services Overview - Explain Responsible AI - Discuss OCI AI Services Overview
Topic 4: OCI Generative AI and Oracle 23ai	10%	- Discuss Autonomous Database Select AI - Describe OCI Generative AI Services - Discuss Oracle Vector Search
Topic 5: Intro to Generative AI and LLMs	15%	- Discuss Generative AI Overview - Explain Prompt Engineering and Instruction Tuning - Explain LLM Fine Tuning - Explain Transformers Fundamentals - Discuss Large Language Models Fundamentals
Topic 6: Intro to DL Foundations	15%	- Discuss Deep Learning Fundamentals - Explain Convolutional Models (CNN) - Explain Sequence Models (RNN and LSTM)
Topic 7: Intro to AI Foundations	10%	- Discuss AI Basics - Explain AI vs ML vs DL - Discuss AI Applications and Types of Data

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Oracle Cloud Infrastructure 2026 AI Foundations Associate 1z0-1122-26 Prüfungsfragen mit Lösungen (Q44-Q49):

44. Frage
What is the primary benefit of using Oracle Cloud Infrastructure Supercluster for AI workloads?

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

Antwort: B

Begründung:
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.

45. Frage
Which is NOT a category of pretrained foundational models available in the OCI Generative AI service?

A. Translation models
B. Chat models
C. Embedding models
D. Generation models

Antwort: A

Begründung:
The OCI Generative AI service offers various categories of pretrained foundational models, including Embedding models, Chat models, and Generation models. These models are designed to perform a wide range of tasks, such as generating text, answering questions, and providing contextual embeddings. However, Translation models, which are typically used for converting text from one language to another, are not a category available in the OCI Generative AI service ' s current offerings. The focus of the OCI Generative AI service is more aligned with tasks related to text generation, chat interactions, and embedding generation rather than direct language translation.

46. Frage
How do Large Language Models (LLMs) handle the trade-off between model size, data quality, data size and performance?

A. They ensure that the model size, training time, and data size are balanced for optimal results.
B. They focus on increasing the number of tokens while keeping the model size constant.
C. They disregard model size and prioritize high-quality data only.
D. They prioritize larger model sizes to achieve better performance.

Antwort: A

47. Frage
Which AI domain can be employed for identifying patterns in images and extract relevant features?

A. Anomaly Detection
B. Speech Processing
C. Natural Language Processing
D. Computer Vision

Antwort: D

Begründung:
Computer Vision is the AI domain specifically employed for identifying patterns in images and extracting relevant features. This field focuses on enabling machines to interpret and understand visual information from the world, automating tasks that the human visual system can perform, such as recognizing objects, analyzing scenes, and detecting anomalies. Techniques in Computer Vision are widely used in applications ranging from facial recognition and image classification to medical image analysis and autonomous vehicles.

48. Frage
What is the benefit of using embedding models in OCI Generative AI service?

A. They enable creating detailed graphics.
B. They facilitate semantic searches.
C. They simplify managing databases.
D. They optimize the use of computational resources.

Antwort: B

Begründung:
Embedding models in the OCI Generative AI service are designed to represent text, phrases, or other data types in a dense vector space, where semantically similar items are located closer to each other. This representation enables more effective semantic searches, where the goal is to retrieve information based on the meaning and context of the query, rather than just exact keyword matches.
The benefit of using embedding models is that they allow for more nuanced and contextually relevant searches. For example, if a user searches for " financial reports, " an embedding model can understand that " quarterly earnings " is semantically related, even if the exact phrase does not appear in the document. This capability greatly enhances the accuracy and relevance of search results, making it a powerful tool for handling large and diverse datasets .

49. Frage
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