試験の準備方法-検証する1z0-1122-26専門知識試験-素晴らしい1z0-1122-26学習教材

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Oracle 1z0-1122-26 Exam Syllabus Topics:

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

                                                  >> 1z0-1122-26専門知識 <<

                                                  1z0-1122-26学習教材、1z0-1122-26試験

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                                                  Oracle Cloud Infrastructure 2026 AI Foundations Associate 認定 1z0-1122-26 試験問題 (Q22-Q27):

                                                  質問 # 22
                                                  What is the purpose of the model catalog in OCI Data Science?

                                                  正解：C

                                                  解説：
                                                  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.


                                                  質問 # 23
                                                  Which feature is NOT available as part of OCI Speech capabilities?

                                                  正解：A

                                                  解説：
                                                  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.


                                                  質問 # 24
                                                  What is a key advantage of using dedicated AI clusters in the OCI Generative AI service?

                                                  正解：D

                                                  解説：
                                                  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.


                                                  質問 # 25
                                                  How does Oracle Cloud Infrastructure Document Understanding service facilitate business processes?

                                                  正解：A

                                                  解説：
                                                  Oracle Cloud Infrastructure (OCI) Document Understanding service facilitates business processes by automating data extraction from documents. This service leverages machine learning to identify, classify, and extract relevant information from various document types, reducing the need for manual data entry and improving efficiency in document processing workflows. Automation of these tasks enables organizations to streamline operations and reduce errors associated with manual data handling.


                                                  質問 # 26
                                                  What key objective does machine learning strive to achieve?

                                                  正解：C

                                                  解説：
                                                  The key objective of machine learning is to enable computers to learn from experience and improve their performance on specific tasks over time. This is achieved through the development of algorithms that can learn patterns from data and make decisions or predictions without being explicitly programmed for each task.
                                                  As the model processes more data, it becomes better at understanding the underlying patterns and relationships, leading to more accurate and efficient outcomes.


                                                  質問 # 27
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