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Oracle Cloud Infrastructure AI Foundations Associate (1Z0-1122-26) Syllabus

AI Foundations

Describing AI terminology, applications, data types and how AI, ML and deep learning relate.

14%
Weight
5
Questions
14
Marks

AI concepts

  • AI terminology
  • AI applications and use cases
  • Relationship between AI, ML and deep learning
  • Types of data used in AI

AI domains

  • Language and text tasks
  • Speech and audio tasks
  • Vision tasks
  • Decision and anomaly detection tasks

Machine Learning Foundations

Explaining supervised, unsupervised and reinforcement learning.

15%
Weight
6
Questions
15
Marks

Supervised learning

  • Classification
  • Regression
  • Training and test data
  • Model evaluation basics

Other learning types

  • Unsupervised learning and clustering
  • Reinforcement learning
  • Choosing a learning approach
  • Features and labels

Deep Learning Foundations

Explaining neural networks and common deep learning architectures.

15%
Weight
6
Questions
15
Marks

Neural networks

  • Neurons, layers and weights
  • Training with backpropagation
  • Activation functions
  • Deep learning versus classical ML

Architectures

  • Convolutional neural networks
  • Sequence models such as RNNs and LSTMs
  • Use cases for each architecture
  • Introduction to transformers

Generative AI and Large Language Models

Explaining LLMs, transformers, prompting and model customization.

14%
Weight
6
Questions
14
Marks

LLM fundamentals

  • Language models and tokens
  • Transformer architecture and attention
  • Generative versus discriminative models
  • Hallucination

Working with LLMs

  • Prompt engineering
  • In-context learning
  • Fine-tuning
  • Retrieval-augmented generation

OCI AI Portfolio

Describing Oracle's AI services, ML services, AI infrastructure and responsible AI.

14%
Weight
6
Questions
14
Marks

Services and infrastructure

  • OCI AI services overview
  • OCI Data Science and machine learning services
  • GPU infrastructure and AI superclusters on OCI
  • Choosing the right OCI service

Responsible AI

  • Responsible AI principles
  • Fairness and bias
  • Transparency and explainability
  • Oracle's approach to trustworthy AI

OCI Generative AI and Oracle Database AI capabilities

Describing OCI Generative AI and AI features in Oracle Database such as vector search and Select AI.

14%
Weight
6
Questions
14
Marks

OCI Generative AI service

  • Pretrained foundation models for chat and embeddings
  • Fine-tuning and dedicated AI clusters
  • Generative AI agents and RAG on OCI
  • Use cases for OCI Generative AI

Oracle Database AI

  • AI Vector Search
  • Vector embeddings in the database
  • Select AI natural-language queries
  • Combining vector and relational search

OCI AI Services

Matching use cases to OCI Language, Speech, Vision and Document Understanding.

14%
Weight
5
Questions
14
Marks

Language and speech

  • OCI Language for text analysis
  • OCI Speech for transcription
  • Pretrained versus custom models
  • Language use cases

Vision and documents

  • OCI Vision image analysis
  • Object detection and image classification
  • OCI Document Understanding
  • Document extraction use cases

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Timed Exams

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  • Exam-like environment
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Practice Tests

Comprehensive question bank with detailed explanations

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Visual learning tools to connect and remember concepts

  • Interactive diagrams
  • Topic relationships

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Learning Progress

AI Foundations 85%
Machine Learning Foundations 92%

Practice Test Scores

95%
Latest Score
Above passing threshold

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