AI Agents Architecture Java Course Syllabus

Overview: This course provides a comprehensive introduction to building AI agents using Java, with a strong focus on enterprise-grade applications. Designed for developers with prior Java experience, it blends core AI concepts with practical implementation techniques. The curriculum spans six modules, totaling approximately 15-18 hours of content, combining lectures, hands-on labs, case studies, and assessments. Learners will gain experience in designing scalable AI systems, integrating neural networks, natural language processing, and computer vision into Java-based environments, and deploying intelligent agents in production. Ideal for software engineers aiming to bridge traditional backend development with modern AI capabilities.

Module 1: Foundations of Computing & Algorithms

Estimated time: 2 hours

• Review of core computing concepts and algorithmic thinking
• Introduction to tools and frameworks used in AI development with Java
• Interactive lab: Building practical solutions using Java
• Case study analysis: Real-world applications of AI agents
• Assessment: Quiz and peer-reviewed assignment

Module 2: Neural Networks & Deep Learning

Estimated time: 4 hours

• Introduction to neural networks and deep learning fundamentals
• Implementation of neural networks using Java-based frameworks
• Hands-on exercises applying deep learning techniques
• Guided project work with instructor feedback
• Review of tools and frameworks for deep learning in Java

Module 3: AI System Design & Architecture

Estimated time: 4 hours

• Introduction to AI system design principles
• Architecting scalable and maintainable AI agents in Java
• Hands-on exercises in designing AI agent workflows
• Assessment: Quiz and peer-reviewed assignment

Module 4: Natural Language Processing

Estimated time: 2 hours

• Introduction to NLP concepts and Java-based libraries
• Hands-on exercises in text processing and language modeling
• Applying prompt engineering techniques with large language models
• Discussion of best practices and industry standards
• Guided project work with instructor feedback

Module 5: Computer Vision & Pattern Recognition

Estimated time: 3 hours

• Introduction to computer vision and pattern recognition
• Implementing image processing pipelines in Java
• Review of tools and frameworks for computer vision
• Discussion of best practices and real-world use cases
• Assessment: Quiz and peer-reviewed assignment

Module 6: Deployment & Production Systems

Estimated time: 3 hours

• Deploying AI agents in enterprise environments
• Case study analysis: Real-world deployment challenges
• Best practices for monitoring and maintaining AI systems
• Assessment: Quiz and peer-reviewed assignment

Prerequisites

• Proficiency in Java programming
• Familiarity with software engineering fundamentals
• Basic understanding of algorithms and data structures

What You'll Be Able to Do After

• Design and implement AI agents using Java for enterprise applications
• Apply neural networks and deep learning techniques in Java environments
• Integrate natural language processing and computer vision capabilities
• Deploy scalable AI systems in production settings
• Use computational thinking to solve complex engineering problems with AI