Generative AI for Java and Spring Developers

Overview

Generative AI skills boost tech salaries by up to 50 percent (CIO Dive). Java developers with strong AI skills are in-demand!

This four-course specialization gives Java and Spring developers GenAI skills for building AI-powered apps that businesses desperately need. Java developers use generative AI to build intelligent applications, automate code generation, enhance productivity, and integrate advanced AI features like chatbots, recommendation engines, and NLP into Java and Spring-based systems.

In this program, you’ll identify essential tools and real-world applications for AI-generated text, imagery, audio, and more. Enhance your productivity with prompt engineering skills, best practices for AI development, and real-world AI tool experience.

You’ll develop GenAI skills for writing and improving code, designing apps, solving problems, and addressing AI-assisted programming ethical concerns. You’ll learn how to set up a Java environment optimized for AI libraries, and use Deeplearning4j to build neural network apps, image recognition, and recommendation systems in Java.

You’ll master debugging, deploying, and managing Spring AI apps with robust configuration, logging, and error handling. Complete this specialization ready to design and integrate AI-powered service layers, RESTful APIs, and components into Spring apps.

Share your portfolio projects with your peers, managers, and prospective employers. Reap the rewards of developing your career and sign up today!

Syllabus

• Introduction to Generative AI
Overview of generative AI concepts
Impact of AI skills on tech careers
• Setting up AI Development in Java
Configuring a Java environment for AI
Essential AI libraries and tools for Java
Introduction to Deeplearning4j
• Generative AI Techniques and Applications
AI-generated text, imagery, audio
Real-world AI applications in Java and Spring
Integrating AI features: chatbots, recommendation engines, NLP
• Prompt Engineering and AI Best Practices
Developing prompt engineering skills
Best practices for AI development in Java
Addressing ethical concerns in AI-assisted programming
• Building AI-powered Applications in Java and Spring
Automating code generation
Designing intelligent applications
Real-world examples of AI-powered app components
• AI-powered Application Development with Deeplearning4j
Building neural network applications in Java
Implementing image recognition systems
Developing recommendation systems
• Advanced AI Features in Spring
Creating AI-powered service layers
Designing RESTful APIs with AI components
Integrating AI into Spring-based systems
• Debugging, Deploying, and Managing Spring AI Applications
Robust configuration for AI applications
Effective logging and error handling
Deployment strategies for AI applications
• Portfolio Development and Career Advancement
Developing a portfolio of AI projects
Sharing projects with peers, managers, and potential employers
Leveraging AI skills for career growth and salary benefits

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Taught by

Antonio Cangiano, Ramanujam Srinivasan, Rav Ahuja and Skill-Up EdTech Team

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Subjects

Computer Science