AI, machine learning and data topics for Java developers, from Spring AI to general LLM concepts.
1. Spring AI
See the full Spring AI Tutorial for building AI apps with Spring Boot.
2. AI and LLM Concepts
- LLM Terms Every Developer Should Know (Glossary)
- Model Context Protocol (MCP) Explained for Java Developers
- MCP Tool Poisoning: A Local Demo and Defenses in Python
- LLM Token Costs: Estimate and Reduce Them in Java Apps
- Best Machine Learning Libraries for Java in 2026
- Fine-Tune an OpenAI ChatGPT Model: Step-by-Step Example
- Getting Started with ChatGPT API and Python
- Context Bloat in AI Agents: Causes, Cost and How to Fix It
- Run LLMs Locally for Java: Ollama vs Docker Model Runner vs LM Studio
- RAG Explained: Retrieval Augmented Generation for Java
- Fine-Tuning vs RAG vs Prompt Engineering for LLM Apps
- Prompt Injection in LLM Apps: Risks and Defenses
- Spring AI vs LangChain4j vs Embabel vs AgentScope Java
3. LangChain4j
- Getting Started with LangChain4j and Spring Boot
- LangChain4J Structured Output Example (JSON Response)
- Multi-Agent AI in Java with LangChain4j Example
4. AI Applications With Python
- How to Extract Data From Invoices With AI in Python
- How to Screen Resumes Against a Job Description With AI
- How to Find Root Cause of Errors in Logs With AI
5. Data Analytics and Computer Science Fundamentals
- What Is Data Analytics and How Can You Get Started?
- Big O Notation: Measuring the Algorithm Efficiency
6. Coding Agents
Happy Learning !!
