Exam Questions for Oracle 1z0-1122-26 in PDF Format

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Oracle 1z0-1122-26 Exam Syllabus Topics:

SectionWeightObjectives
Deep Learning Foundations15%- Deep Learning and neural networks
  • 1. Convolutional Neural Networks (CNN) architectures
    • 2. Recurrent Neural Networks, LSTMs, and sequence models
      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
          Generative AI and Large Language Models15%- Generative AI concepts
          • 1. Embeddings, Retrieval-Augmented Generation (RAG), and LLMs
            • 2. Transformers, prompt engineering, and fine-tuning
              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
                  Machine Learning Foundations15%- Machine Learning fundamentals
                  • 1. Supervised learning: regression and classification
                    • 2. Reinforcement learning basics and model evaluation concepts
                      • 3. Unsupervised learning: clustering and dimensionality reduction
                        OCI Generative AI and Oracle 23ai10%- OCI Generative AI Service features
                        • 1. Oracle 23ai Vector Database integration
                          • 2. Generative AI capabilities on OCI
                            AI Foundations10%- Artificial Intelligence basics and terminology
                            • 1. AI, Machine Learning, and Deep Learning relationship
                              • 2. AI applications, use cases, and responsible AI principles

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                                Oracle Cloud Infrastructure 2026 AI Foundations Associate Sample Questions (Q35-Q40):

                                NEW QUESTION # 35
                                What key objective does machine learning strive to achieve?

                                Answer: C

                                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 # 36
                                How does AI enhance human efforts?

                                Answer: D

                                Explanation:
                                AI enhances human efforts by processing large volumes of data quickly and accurately, performing complex computations that would be time-consuming or impossible for humans to handle manually. This allows humans to focus on more strategic, creative, and decision-making tasks, leveraging AI ' s ability to provide insights, automate repetitive processes, and support decision-making. AI does not physically enhance human capabilities, nor does it replace human workers in all tasks. Instead, it serves as an augmentation tool, amplifying human productivity and capabilities.


                                NEW QUESTION # 37
                                How does Oracle Cloud Infrastructure Document Understanding service facilitate business processes?

                                Answer: C

                                Explanation:
                                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.


                                NEW QUESTION # 38
                                Emma is developing a customer support chatbot for an e-commerce website. The chatbot needs to provide accurate and up-to-date return policies, which change frequently. She initially tries fine-tuning but finds that the model still uses outdated information. Which approach should Emma use instead?

                                Answer: D

                                Explanation:
                                Retrieval-Augmented Generation is the appropriate approach when a chatbot must answer using information that changes frequently. Oracle defines RAG as a technique that retrieves information from specific external data sources and augments an LLM ' s response with that retrieved context, producing grounded answers.
                                Oracle Docs Oracle further explains that RAG can incorporate information that is more current than the model
                                ' s original training data and that knowledge repositories can be continually updated without retraining the underlying LLM. Oracle Docs Fine-tuning is better suited to adapting model behavior or specialization, not continuously changing factual information. Prompt engineering and zero-shot prompting control how instructions are presented but do not independently supply current return-policy data. Therefore, RAG is the correct solution for providing accurate, current, organization-specific policy responses.


                                NEW QUESTION # 39
                                What is a key advantage of using dedicated AI clusters in the OCI Generative AI service?

                                Answer: D

                                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 # 40
                                ......

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