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🤖 Oracle Cloud Infrastructure (OCI) Generative AI Course

The Oracle Cloud Infrastructure (OCI) Generative AI Course provides an in-depth technical introduction to Large Language Models (LLMs) and their applications. This course explores LLM architecture, fine-tuning techniques, multimodal models, language agents, and code models, along with practical use cases in OCI’s Generative AI ecosystem.

Learners will gain hands-on experience with OCI Generative AI Service, OCI Generative AI Agents, and the Oracle 23ai Database. Through demonstrations and guided exercises, you’ll learn to implement Retrieval-Augmented Generation (RAG) pipelines and build intelligent chatbots integrated with OCI services.

This course also prepares you for the Oracle Cloud Infrastructure 2025 Generative AI Professional Certification — your next step toward mastering enterprise-grade Generative AI solutions.


🎯 Course Objectives

After completing this course, you will be able to:

  • 🧠 Explain Large Language Models (LLMs) and their architecture, training, and applications.
  • ⚙️ Use OCI Generative AI Service and OCI Generative AI Agents Service proficiently.
  • 💬 Build a chatbot using OCI Generative AI Agents Service and Retrieval-Augmented Generation (RAG).
  • 🏗 Understand and utilize Oracle 23ai Database as a Vector Store for RAG-based workflows.

🌍 OCI Generative AI Service Availability

Currently, the OCI Generative AI Service is available in the following regions:

  • 🇺🇸 US Midwest (Chicago)
  • 🇩🇪 Germany Central (Frankfurt)
  • 🇬🇧 UK South (London)

⚠️ Please ensure you subscribe to one of these regions to access OCI Generative AI features.


🚀 Benefits to You

By completing this course, you will:

  • ✅ Become proficient in building Generative AI solutions using OCI Generative AI, OCI Agents, and Oracle 23ai Vector Store.
  • 💡 Learn to design and deploy RAG-based chatbots integrated with OCI infrastructure.
  • 🧩 Understand the security architecture and deployment models of OCI Generative AI.
  • 🏆 Gain expertise aligned with the OCI 2025 Generative AI Professional Certification.
  • 💼 Acquire industry-ready skills that differentiate you in a rapidly evolving AI landscape.

🧰 Skills You Will Learn

🔹 Fundamentals of Large Language Models (LLMs)

  • LLM basics, architectures, and prompt engineering
  • Fine-tuning methods and T-Few techniques
  • Fundamentals of code models, multimodal LLMs, and language agents

🔹 OCI Generative AI Deep-Dive

  • Working with Pretrained Foundational Models (generation, summarization, embeddings)
  • Understanding Dedicated AI Clusters and Generative AI Security Architecture
  • Performing model inference and deploying fine-tuned models

🔹 Build a Conversational Chatbot

  • Design Retrieval-Augmented Generation (RAG) workflows
  • Implement Vector Databases and Semantic Search using Oracle 23ai
  • Build chatbots using LangChain Framework (prompts, models, memory, chains)
  • Trace, evaluate, and deploy chatbots on OCI infrastructure

📚 Prerequisites

Before enrolling in this course, you should have:

  • A basic understanding of Machine Learning and Deep Learning concepts
  • Familiarity with Python programming

📘 Course Resources & References

Here are the key learning resources for this course:


☁️ Cloud Family

  • Cloud Platform: Oracle Cloud Infrastructure (OCI)
  • Course Type: Professional Hands-On Course
  • Focus Area: Generative AI, Large Language Models, and AI Agents

🏁 Conclusion

The OCI Generative AI Course empowers you to design, fine-tune, and deploy next-generation AI solutions using Oracle’s cutting-edge cloud ecosystem. From mastering LLM fundamentals to building production-ready chatbots, you’ll gain the skills to innovate responsibly and efficiently in the era of Generative AI.


© Oracle Cloud Infrastructure | Generative AI Professional Learning Path (2025 Edition)

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The Oracle Cloud Infrastructure (OCI) Generative AI Course provides an in-depth technical introduction to Large Language Models (LLMs) and their applications. This course explores LLM architecture, fine-tuning techniques, multimodal models, language agents, and code models

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