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Oracle 1z0-1122-26 Exam Syllabus Topics:

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

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                                                  Oracle Cloud Infrastructure 2026 AI Foundations Associate Sample Questions (Q23-Q28):

                                                  NEW QUESTION # 23
                                                  What is a key advantage of using dedicated AI clusters in the OCI Generative AI service?

                                                  Answer: B

                                                  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 # 24
                                                  Which type of machine learning is used to understand relationships within data and is not focused on making predictions or classifications?

                                                  Answer: C

                                                  Explanation:
                                                  Unsupervised learning is a type of machine learning that focuses on understanding relationships within data without the need for labeled outcomes. Unlike supervised learning, which requires labeled data to train models to make predictions or classifications, unsupervised learning works with unlabeled data and aims to discover hidden patterns, groupings, or structures within the data.
                                                  Common applications of unsupervised learning include clustering, where the algorithm groups data points into clusters based on similarities, and association, where it identifies relationships between variables in the dataset. Since unsupervised learning does not predict outcomes but rather uncovers inherent structures, it is ideal for exploratory data analysis and discovering previously unknown patterns in data .


                                                  NEW QUESTION # 25
                                                  Which AI domain is associated with tasks such as identifying the sentiment of text and translating text between languages?

                                                  Answer: C

                                                  Explanation:
                                                  Natural Language Processing (NLP) is the AI domain associated with tasks such as identifying the sentiment of text and translating text between languages. NLP focuses on enabling machines to understand, interpret, and generate human language in a way that is both meaningful and useful. This domain covers a wide range of applications, including text classification, language translation, sentiment analysis, and more, all of which involve processing and analyzing natural language data.


                                                  NEW QUESTION # 26
                                                  A customer feedback analysis team needs to extract insights from thousands of online product reviews. They want to determine whether customers express positive or negative opinions about different aspects of a product or service. Which feature of OCI Language is helpful?

                                                  Answer: B

                                                  Explanation:
                                                  OCI Language provides pretrained natural language processing capabilities for analyzing unstructured text, including sentiment analysis. In this scenario, the requirement is specifically to determine whether customers express positive or negative opinions concerning individual aspects of a product or service. Oracle ' s OCI Language customer-feedback architecture describes extracting aspects from reviews and associating sentiments such as positive, negative, or neutral with those aspects. Oracle Docs Key phrase extraction identifies important topics or phrases, named entity recognition identifies entities such as organizations, people, or locations, and language detection determines the language in which content is written. None directly evaluates customer opinion. Sentiment analysis therefore precisely matches the business requirement because it transforms subjective review content into structured sentiment information that can be analyzed at scale.


                                                  NEW QUESTION # 27
                                                  Which statement describes the Optical Character Recognition (OCR) feature of Oracle Cloud Infrastructure Document Understanding?

                                                  Answer: A

                                                  Explanation:
                                                  The Optical Character Recognition (OCR) feature of Oracle Cloud Infrastructure (OCI) Document Understanding recognizes and extracts text from documents. This capability is fundamental for converting printed or handwritten text into a machine-readable format, allowing for further processing, such as text analysis, search, and archiving. OCI ' s OCR is an essential tool in automating document processing workflows, enabling businesses to digitize and manage their documents efficiently.


                                                  NEW QUESTION # 28
                                                  ......

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