Oracle Cloud Infrastructure 2026 AI Foundations Associate: 1z0-1122-26 Exam

"Oracle Cloud Infrastructure 2026 AI Foundations Associate", also known as 1z0-1122-26 exam, is a Oracle Certification. With the complete collection of questions and answers, ExamcollectionPass has assembled to take you through 49 Q&As to your 1z0-1122-26 Exam preparation. In the 1z0-1122-26 exam resources, you will cover every field and category in Oracle Cloud Infrastructure Certification helping to ready you for your successful Oracle Certification.

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  • Exam Code: 1z0-1122-26
  • Exam Name: Oracle Cloud Infrastructure 2026 AI Foundations Associate
  • Certification Provider: Oracle
  • Corresponding Certification: Oracle Cloud Infrastructure
  • Updated: Sep 08, 2026
  • No. of Questions: 49 Questions & Answers with Testing Engine
  • Download Limit: Unlimited

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Oracle 1z0-1122-26 Exam Syllabus Topics:

SectionWeightObjectives
Deep Learning Foundations15%- Deep Learning and neural networks
  • 1. Recurrent Neural Networks, LSTMs, and sequence models
    • 2. Convolutional Neural Networks (CNN) architectures
      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
            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 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
                        AI Foundations10%- Artificial Intelligence basics and terminology
                        • 1. AI, Machine Learning, and Deep Learning relationship
                          • 2. AI applications, use cases, and responsible AI principles
                            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

                                Oracle Cloud Infrastructure 2026 AI Foundations Associate Sample Questions:

                                Question 1

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

                                A. Text Generation
                                B. Language Detection
                                C. Text Classification
                                D. Sentiment Analysis


                                Question 2

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

                                A. Accelerated Data Science (ADS) SDK
                                B. Notebook sessions
                                C. Model catalog
                                D. Conda environment


                                Question 3

                                Lisa is working on a project that involves transcribing thousands of audio files stored in Oracle Cloud. She wants to process multiple files efficiently instead of transcribing them one by one. Which OCI Speech feature should Lisa use?

                                A. Profanity filtering
                                B. Confidence scoring
                                C. Timestamping
                                D. Batch support


                                Question 4

                                You are training a logistic regression model to classify emails as spam or not spam. The model is currently classifying too many emails as spam. What would you do to adjust the model?

                                A. Decrease the number of iterations.
                                B. Increase the regularization parameter.
                                C. Decrease the weight of the feature representing the presence of certain keywords.
                                D. Increase the threshold value for classification.


                                Question 5

                                What is the difference between classification and regression in Supervised Machine Learning?

                                A. Classification and regression both assign data points to categories.
                                B. Classification and regression both predict continuous values.
                                C. Classification assigns data points to categories, whereas regression predicts continuous values.
                                D. Classification predicts continuous values, whereas regression assigns data points to categories.


                                Solutions:

                                Question 1
                                Answer: A
                                Question 2
                                Answer: B
                                Question 3
                                Answer: D
                                Question 4
                                Answer: D
                                Question 5
                                Answer: C

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