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Oracle 1z0-1122-26 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Deep Learning Foundations15%- Deep Learning and neural networks
  • 1. Convolutional Neural Networks (CNN) architectures
    • 2. Recurrent Neural Networks, LSTMs, and sequence models
      Topic 2: Introduction to OCI AI Services20%- OCI AI Service APIs
      • 1. OCI Language, Vision, Speech, and Document Understanding services
        • 2. OCI Select AI and AI service use cases
          Topic 3: OCI AI Portfolio15%- Overview of OCI AI offerings
          • 1. OCI Data Science and GPU-based compute infrastructure
            • 2. AI Services, ML Services, and AI Infrastructure overview
              Topic 4: Generative AI and Large Language Models15%- Generative AI concepts
              • 1. Embeddings, Retrieval-Augmented Generation (RAG), and LLMs
                • 2. Transformers, prompt engineering, and fine-tuning
                  Topic 5: AI Foundations10%- Artificial Intelligence basics and terminology
                  • 1. AI, Machine Learning, and Deep Learning relationship
                    • 2. AI applications, use cases, and responsible AI principles
                      Topic 6: OCI Generative AI and Oracle 23ai10%- OCI Generative AI Service features
                      • 1. Oracle 23ai Vector Database integration
                        • 2. Generative AI capabilities on OCI
                          Topic 7: Machine Learning Foundations15%- Machine Learning fundamentals
                          • 1. Unsupervised learning: clustering and dimensionality reduction
                            • 2. Reinforcement learning basics and model evaluation concepts
                              • 3. Supervised learning: regression and classification

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                                Oracle Cloud Infrastructure 2026 AI Foundations Associate Sample Questions (Q46-Q51):

                                NEW QUESTION # 46
                                Which feature is NOT available as part of OCI Speech capabilities?

                                Answer: B

                                Explanation:
                                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.


                                NEW QUESTION # 47
                                What is the primary benefit of using Oracle Cloud Infrastructure Supercluster for AI workloads?

                                Answer: C


                                NEW QUESTION # 48
                                Which is NOT a category of pretrained foundational models available in the OCI Generative AI service?

                                Answer: D

                                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 # 49
                                Which feature of OCI Speech helps make transcriptions easier to read and understand?

                                Answer: C

                                Explanation:
                                The text normalization feature of OCI Speech helps make transcriptions easier to read and understand by converting spoken language into a more standardized and grammatically correct format. This process includes correcting grammar, punctuation, and formatting, ensuring that the transcribed text is clear, accurate, and suitable for various use cases. Text normalization enhances the usability of transcriptions, making them more accessible and easier to process in downstream applications.
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                                NEW QUESTION # 50
                                What feature of OCI Data Science provides an interactive coding environment for building and training models?

                                Answer: B

                                Explanation:
                                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.


                                NEW QUESTION # 51
                                ......

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