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Spring AI 2.0 - Theory - Free Course!
New
125 students
Spring AI 2.0 - Theory - Free Course!
Mastering Spring AI 2.0 - GenAI, Advisors, Memory Management, RAG, Vector Databases, Tool Calling, and MCP
Created byYuval Ishay
Last updated 11/2026
English
English [Auto],
What you'll learn
- Master Spring AI: Seamlessly connect your Spring Boot apps to top LLMs like ChatGPT, Claude, and Gemini using clean, familiar Java code.
- Vector DBs & RAG: Easily store and query enterprise data using advanced vector databases like Pinecone, Redis, Postgres, and MongoDB.
- Advanced AI Patterns: Implement Chat Memory, Function/Tool Calling, Advisor APIs, and the cutting-edge Model Context Protocol (MCP).
- Production Ready: Build secure, reliable AI features with built-in Observability and Guardrails without learning complex new SDKs.
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Course content
10 sections • 22 lectures • 1h 56m total length
Requirements
- Basic knowledge of Java and the Spring Boot framework is required.
- A computer capable of running a Java IDE (IntelliJ).
- Ablitiy to A small budget to purchase API keys (e.g., Gemini) to follow along.
Description
AI Disclosure: This course contains the use of artificial intelligence.
Transform into a Senior AI Engineer with the Most Modern Tech Stack in the Java Ecosystem.
Generative AI is no longer just a trend—it is shifting the foundation of enterprise software architecture. Traditional Java applications are rapidly evolving into intelligent, AI-native systems capable of autonomous reasoning, real-time context retrieval, and complex task execution.
This FREE and Theoretical course is build specifically for Java Architects and development leaders who want to step into the AI future of software development. You won't just learn how to connect an API to a chatbot; you will master the art of designing and building complex, autonomous, and cost-effective enterprise AI applications using the latest standards: Spring AI 2.0.0
What You Will Learn in the Course:
The Shift to AI-Native: Understanding the fundamental architectural transition required to upgrade traditional Spring architectures to support heavy generative capabilities.
Retrieval-Augmented Generation (RAG): Learn how to securely connect your private enterprise data to Large Language Models (LLMs) such as Gemini using high-performance vector databases.
Autonomous AI Agents and Tool Calling: Moving beyond passive chatbots. Learn the theory of building proactive AI agents capable of automatically selecting and executing internal Java functions (Tool Calling) to interact with your databases, external APIs, and business logic in real time.
Model Context Protocol (MCP): Understand the open protocol that has become the industry standard for AI data integration. .
Prompt Engineering and Structured Outputs: Learn how easy Spring AI helps us to return well-defined, type-safe Java objects instead of raw, unpredictable text.
This free course is composed of content taken directly from the very first theoretical lessons of each section in our full-scale, comprehensive Spring AI course. Whenever you feel ready to jump straight into the code, configure your development environment, and explore the deep implementation details step-by-step, you are always welcome to join us in the full course!
Stop watching the AI revolution from the sidelines. Upgrade your Java stack, master Spring AI, and start building the future of enterprise software today!
Who this course is for:
- Java & Spring Boot Developers looking to easily integrate AI into their existing backend applications.
- Backend Engineers who want to leverage LLMs like ChatGPT, Claude, and Gemini with Java Tools
- Software Architects interested in modern AI architectures like Vector DBs, RAG, and the MCP protocol.
- Tech Professionals wanting to upgrade their skills and stay highly competitive in the GenAI market.