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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: 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 3: 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 4: Machine Learning Foundations15%- Machine Learning fundamentals
              • 1. Reinforcement learning basics and model evaluation concepts
                • 2. Supervised learning: regression and classification
                  • 3. Unsupervised learning: clustering and dimensionality reduction
                    Topic 5: 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
                        Topic 6: OCI Generative AI and Oracle 23ai10%- OCI Generative AI Service features
                        • 1. Generative AI capabilities on OCI
                          • 2. Oracle 23ai Vector Database integration
                            Topic 7: 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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                                Oracle Cloud Infrastructure 2026 AI Foundations Associate Sample Questions (Q24-Q29):

                                NEW QUESTION # 24
                                What key objective does machine learning strive to achieve?

                                Answer: D

                                Explanation:
                                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.


                                NEW QUESTION # 25
                                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 # 26
                                You are working on a project for a healthcare organization that wants to develop a system to predict the severity of patients ' illnesses upon admission to a hospital. The goal is to classify patients into three categories - Low Risk, Moderate Risk, and High Risk - based on their medical history and vital signs. Which type of supervised learning algorithm is required in this scenario?

                                Answer: A

                                Explanation:
                                In this healthcare scenario, where the goal is to classify patients into three categories-Low Risk, Moderate Risk, and High Risk-based on their medical history and vital signs, a Multi-Class Classification algorithm is required. Multi-class classification is a type of supervised learning algorithm used when there are three or more classes or categories to predict. This method is well-suited for situations where each instance needs to be classified into one of several categories, which aligns with the requirement to categorize patients into different risk levels.


                                NEW QUESTION # 27
                                What can Oracle Cloud Infrastructure Document Understanding NOT do?

                                Answer: A

                                Explanation:
                                Oracle Cloud Infrastructure (OCI) Document Understanding service offers several capabilities, including extracting tables, classifying documents, and extracting text. However, it does not generate transcripts from documents. Transcription typically refers to converting spoken language into written text, which is a function associated with speech-to-text services, not document understanding services. Therefore, generating a transcript is outside the scope of what OCI Document Understanding is designed to do .


                                NEW QUESTION # 28
                                What is the primary benefit of using Oracle Cloud Infrastructure Supercluster for AI workloads?

                                Answer: A


                                NEW QUESTION # 29
                                ......

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