Java + AI Applications

This direction builds understanding from backend development to intelligent capability integration. Practice is based on work that is understandable, verifiable and explainable.

Java Backend Practice

Practice Java fundamentals, common web services, API design, database operations and basic troubleshooting. Understand how a service receives requests, processes business logic, reads or writes data and returns results.

Foundation Skills

• Java fundamentals, collections, exceptions and object-oriented design.
• HTTP requests, responses, API parameters and basic networking.
• Database modeling, SQL, transactions and common data scenarios.

Service Development

Practice entity design, API layering, validation, exception handling, log analysis and basic performance awareness. Organize key decisions into material that can be explained clearly.

AI Application Practice

Explore large-language-model application concepts such as prompt design, retrieval-augmented knowledge bases, tool calling, conversation flow and scenario communication.

Integration Thinking

Define inputs and outputs, organize knowledge sources, decide when to call a model, handle uncertain results and explain how AI works alongside traditional system functions.

Scenarios and Communication

Use knowledge Q&A, workflow assistants, document summaries or information retrieval to understand application design. Explain the business problem, data source, system flow, model role and result validation.

General Engineering Skills

Alongside the technology direction, practice Git, requirement breakdown, debugging, API documentation, deployment basics and collaboration conventions.

Choosing a Direction

Begin with one target role and one project you can explain end to end, then fill in adjacent skills over time.