Video course · 15 chapters · 338 min · certificate
Spring AI for Java Developers: Build Intelligent Apps with Modern LLMs
Build AI-powered Java applications with Spring AI: setup and a first app, AI and LLM concepts, prompt engineering, chat clients and streaming, structured output, multimodal, chat memory, LLM limitations and security, RAG, tools, MCP servers, local models with Ollama, observability, testing and evaluations.
What you'll learn
- Build a first Spring AI application
- Use chat clients, streaming and system messages
- Return type-safe structured output
- Add memory, RAG and tools
- Connect MCP servers and local models
- Observe, test and evaluate AI apps
Chapters
15 chapters · 337:40-
18:30
01Setup Members
Introduction and setup
API keys and project.
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23:40
02Concepts Members
First app and AI concepts
ML, deep learning, LLMs.
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20:35
03Prompting Members
Prompt engineering and Spring AI overview
Techniques and why Java.
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25:55
04Chat Members
Chat clients, streaming and system messages
The ChatClient API.
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29:50
05Output Members
Structured output and multimodal
Type safety and media.
-
13:50
06Memory Members
Chat memory
Conversation state.
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20:10
07Safety Members
Limitations, guarding and prompt stuffing
Hallucinations and context.
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19:45
08RAG Members
RAG
Retrieval augmented generation.
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23:25
09Tools Members
Tools and function calling
Calling Java methods.
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29:40
10MCP Members
MCP servers
Model Context Protocol.
-
33:10
11Local Members
Open source and local models
Ollama, Docker, LM Studio.
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22:45
12Ops Members
Observability
Prometheus and Grafana.
-
15:15
13Testing Members
Testing and evaluations
Evaluating AI output.
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26:00
14Testing Members
Deterministic vs non-deterministic testing
Best practices.
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15:10
15Careers Members
AI portfolio and wrap-up
What's next.
Jobs this course suits
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