AI Agents in Java with Generative AI Syllabus
Full curriculum breakdown — modules, lessons, estimated time, and outcomes.
Overview: This course provides a practical introduction to building AI agents in Java with a focus on generative AI and enterprise applications. Designed for developers with Java experience, it covers core AI concepts, system design, and deployment techniques. With approximately 15-20 hours of content, learners will gain hands-on experience through labs, case studies, and projects, culminating in a final project that demonstrates real-world AI application development.
Module 1: Foundations of Computing & Algorithms
Estimated time: 4 hours
- Review of tools and frameworks commonly used in practice
- Case study analysis with real-world examples
- Interactive lab: Building practical solutions
- Applying computational thinking to solve complex engineering problems
Module 2: Neural Networks & Deep Learning
Estimated time: 3 hours
- Introduction to key concepts in neural networks and deep learning
- Hands-on exercises applying neural networks techniques
- Understanding core AI concepts including deep learning
- Assessment: Quiz and peer-reviewed assignment
Module 3: AI System Design & Architecture
Estimated time: 2 hours
- Introduction to key concepts in AI system design & architecture
- Case study analysis with real-world examples
- Guided project work with instructor feedback
- Discussion of best practices and industry standards
Module 4: Natural Language Processing
Estimated time: 2 hours
- Introduction to key concepts in natural language processing
- Review of tools and frameworks commonly used in practice
- Hands-on exercises applying natural language processing techniques
- Implement prompt engineering techniques for large language models
Module 5: Computer Vision & Pattern Recognition
Estimated time: 3 hours
- Case study analysis with real-world examples
- Guided project work with instructor feedback
- Discussion of best practices and industry standards
- Hands-on exercises applying pattern recognition techniques
Module 6: Deployment & Production Systems
Estimated time: 4 hours
- Hands-on exercises applying deployment & production systems techniques
- Interactive lab: Building practical solutions
- Assessment: Quiz and peer-reviewed assignment
- Build and deploy AI-powered applications for real-world use cases
Prerequisites
- Familiarity with Java programming
- Basic understanding of software development principles
- Experience with backend systems (recommended)
What You'll Be Able to Do After
- Apply computational thinking to solve complex engineering problems
- Design algorithms that scale efficiently with increasing data
- Implement prompt engineering techniques for large language models
- Build and deploy AI-powered applications using Java
- Design intelligent systems using modern AI frameworks and libraries