Building Intelligent Applications with Spring AI

Overview

Dive into building intelligent applications with Spring AI, mastering model integration, data analysis, and smart feature development for enhanced application capabilities.

Syllabus

• Introduction to Spring AI
Overview of AI in application development
Introduction to the Spring AI ecosystem
Setting up the development environment
• Understanding AI Models
Types of AI models: ML, DL, NLP, etc.
Selecting the appropriate AI model for your application
Overview of popular AI libraries and frameworks
• Model Integration with Spring AI
Introduction to Spring AI integration tools
Integrating pre-trained models into Spring applications
Building custom models with Spring AI
• Data Analysis and Management
Data pre-processing techniques
Strategies for data management and storage
Using databases and cloud services with Spring
• Smart Feature Development
Designing smart features for user interaction
Implementing intelligent recommendations
Real-time prediction and analytics
• Enhancing Application Capabilities
Building scalable applications with AI capabilities
Optimizing application performance
Security and privacy considerations in AI applications
• Case Studies and Practical Applications
Real-world examples of intelligent applications
Hands-on project: Build an intelligent application using Spring AI
Review and class presentations
• Evaluation and Future Trends
Assessing the effectiveness of AI features
Staying updated with AI advancements and libraries
Future trends and directions in AI and Spring
• Conclusion and Next Steps
Recap of key concepts
Resources for further learning
Certificates of completion and feedback session

Subjects

Programming