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Oracle 1z0-1122-26 Exam Syllabus Topics:

SectionWeightObjectives
Generative AI and Large Language Models15%- Generative AI concepts
  • 1. Embeddings, Retrieval-Augmented Generation (RAG), and LLMs
    • 2. Transformers, prompt engineering, and fine-tuning
      Deep Learning Foundations15%- Deep Learning and neural networks
      • 1. Convolutional Neural Networks (CNN) architectures
        • 2. Recurrent Neural Networks, LSTMs, and sequence models
          Machine Learning Foundations15%- Machine Learning fundamentals
          • 1. Reinforcement learning basics and model evaluation concepts
            • 2. Unsupervised learning: clustering and dimensionality reduction
              • 3. Supervised learning: regression and classification
                OCI AI Portfolio15%- Overview of OCI AI offerings
                • 1. AI Services, ML Services, and AI Infrastructure overview
                  • 2. OCI Data Science and GPU-based compute infrastructure
                    AI Foundations10%- Artificial Intelligence basics and terminology
                    • 1. AI applications, use cases, and responsible AI principles
                      • 2. AI, Machine Learning, and Deep Learning relationship
                        OCI Generative AI and Oracle 23ai10%- OCI Generative AI Service features
                        • 1. Generative AI capabilities on OCI
                          • 2. Oracle 23ai Vector Database integration
                            Introduction to OCI AI Services20%- OCI AI Service APIs
                            • 1. OCI Select AI and AI service use cases
                              • 2. OCI Language, Vision, Speech, and Document Understanding services

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                                1z0-1122-26 Prüfungsguide: Oracle Cloud Infrastructure 2026 AI Foundations Associate & 1z0-1122-26 echter Test & 1z0-1122-26 sicherlich-zu-bestehen

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                                Oracle Cloud Infrastructure 2026 AI Foundations Associate 1z0-1122-26 Prüfungsfragen mit Lösungen (Q47-Q52):

                                47. Frage
                                What feature of OCI Data Science provides an interactive coding environment for building and training models?

                                Antwort: A

                                Begründung:
                                In OCI Data Science, Notebook sessions provide an interactive coding environment that is essential for building, training, and deploying machine learning models. These sessions allow data scientists to write and execute code in real time, offering a flexible environment for data exploration, model experimentation, and iterative development. The integration with various OCI services and support for popular machine learning frameworks further enhances the utility of Notebook sessions, making them a crucial tool in the data science workflow.


                                48. Frage
                                Which feature is NOT supported as part of the OCI Language service ' s pretrained language processing capabilities?

                                Antwort: C

                                Begründung:
                                The OCI Language service offers several pretrained language processing capabilities, including Text Classification, Sentiment Analysis, and Language Detection. However, it does not natively support Text Generation as a part of its core language processing capabilities. Text Generation typically involves creating new content based on input prompts, which is a feature more commonly associated with models specifically designed for natural language generation.


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

                                Antwort: B

                                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.


                                50. Frage
                                In machine learning, what does the term " model training " mean?

                                Antwort: C

                                Begründung:
                                In machine learning, " model training " refers to the process of teaching a model to make predictions or decisions by learning the relationships between input features and the corresponding output. During training, the model is fed a large dataset where the inputs are paired with known outputs (labels). The model adjusts its internal parameters to minimize the error between its predictions and the actual outputs. Over time, the model learns to generalize from the training data to make accurate predictions on new, unseen data.


                                51. Frage
                                Which statement describes the Optical Character Recognition (OCR) feature of Oracle Cloud Infrastructure Document Understanding?

                                Antwort: A

                                Begründung:
                                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.


                                52. Frage
                                ......

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