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Oracle 1z0-1122-26 Exam Syllabus Topics:

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

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                                                  Oracle Cloud Infrastructure 2026 AI Foundations Associate Sample Questions (Q40-Q45):

                                                  NEW QUESTION # 40
                                                  What is the main function of the hidden layers in an Artificial Neural Network (ANN) when recognizing handwritten digits?

                                                  Answer: C

                                                  Explanation:
                                                  In an Artificial Neural Network (ANN) designed for recognizing handwritten digits, the hidden layers serve the crucial function of capturing the internal representation of the raw image data. These layers learn to extract and represent features such as edges, shapes, and textures from the input pixels, which are essential for distinguishing between different digits. By transforming the input data through multiple hidden layers, the network gradually abstracts the raw pixel data into higher-level representations, which are more informative and easier to classify into the correct digit categories.


                                                  NEW QUESTION # 41
                                                  What is the benefit of using embedding models in OCI Generative AI service?

                                                  Answer: B

                                                  Explanation:
                                                  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 .


                                                  NEW QUESTION # 42
                                                  Which AI domain is associated with tasks such as identifying the sentiment of text and translating text between languages?

                                                  Answer: A

                                                  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 # 43
                                                  What is " in-context learning " in the realm of Large Language Models (LLMs)?

                                                  Answer: A

                                                  Explanation:
                                                  " In-context learning " in the realm of Large Language Models (LLMs) refers to the ability of these models to learn and adapt to a specific task by being provided with a few examples of that task within the input prompt.
                                                  This approach allows the model to understand the desired pattern or structure from the given examples and apply it to generate the correct outputs for new, similar inputs. In-context learning is powerful because it does not require retraining the model; instead, it uses the examples provided within the context of the interaction to guide its behavior.


                                                  NEW QUESTION # 44
                                                  Which is NOT a category of pretrained foundational models available in the OCI Generative AI service?

                                                  Answer: B

                                                  Explanation:
                                                  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.


                                                  NEW QUESTION # 45
                                                  ......

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