"Our tailored course provided a well rounded introduction and also covered some intermediate level topics that we needed to know. Clive gave us some best practice ideas and tips to take away. Fast paced but the instructor never lost any of the delegates"
Brian Leek, Data Analyst, May 2022
AI-Assisted Java Development
AI Tools, Prompting, and Code Quality
Testing and Implementation
Git Workflows, Code Quality, and Practical Integration
Git Workflows and Commit Discipline
Git History and Commit Discipline
Interactive Rebase for Clean History
Code Review Standards
Integration into Development Pipeline
GitHub Actions for CI/CD
Code Analysis Tools
Branch Protection and Status Checks
End-to-End Development Cycle
Real-World Patterns and Advanced Scenarios
Advanced AI Usage Patterns
Architectural Decisions with AI
Debugging and Security with AI
Identifying and Fixing AI Mistakes
Performance Analysis
Integration
Team Standards and AI Playbook
Handling AI Limitations
Code Review
• Java developers looking to improve productivity with AI-assisted development
• Software engineers interested in integrating AI into their daily workflow
• Technical leads and architects evaluating AI adoption within development teams
• QA engineers and developers involved in testing and code quality
• Development teams seeking practical, responsible use of AI in software engineering
"Our tailored course provided a well rounded introduction and also covered some intermediate level topics that we needed to know. Clive gave us some best practice ideas and tips to take away. Fast paced but the instructor never lost any of the delegates"
Brian Leek, Data Analyst, May 2022
“JBI did a great job of customizing their syllabus to suit our business needs and also bringing our team up to speed on the current best practices. Our teams varied widely in terms of experience and the Instructor handled this particularly well - very impressive”
Brian F, Team Lead, RBS, Data Analysis Course, 20 April 2022
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This practical course shows Java developers how to use AI to accelerate coding, testing, debugging, and code reviews while maintaining high standards of quality and reliability. Participants will learn effective prompting techniques, AI-assisted development workflows, and best practices for integrating AI into modern software engineering processes.
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