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AI Agents in Java with Generative AI Specialization

A rigorous, Java-centric specialization that equips developers to architect, implement, and deploy sophisticated AI agents for real-world enterprise automation.

access

Lifetime

level

Beginner

certificate

Certificate of completion

language

English

What will you learn in AI Agents in Java with Generative AI Specialization Course

  • Implement autonomous AI agents in Java that process unstructured data, make decisions, and execute complex workflows

  • Dynamically adopt expert personas and build multi-agent collaboration systems with memory sharing and coordination

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  • Architect trustworthy, safe agent frameworks using staged execution, reversible actions, and safety patterns

  • Apply prompt engineering to design agent behaviors before writing code and translate designs into Java implementations

Program Overview

Course 1: AI Agents in Java with Generative AI

⏳ 11 hours

  • Build a complete Java-based AI agent framework, from goals/actions/memory/environment components to tool integration

Course 2: AI Agent Architecture in Java with Generative AI

⏳ 7 hours

  • Implement expert-persona systems, multi-agent orchestration, and safety mechanisms using Java’s reflection and annotation processing

Course 3: Prompt Engineering for ChatGPT

⏳ 18 hours

  • Master prompt patterns—zero/few-shot, chain-of-thought—and build complex ChatGPT-based applications that integrate seamlessly with Java agents

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Job Outlook

  • Roles: AI Engineer (Java), Agentic Systems Architect, ML Engineer, Software Developer specializing in autonomous agents.

  • Industries: Enterprise automation, fintech, IoT platforms, and large-scale software solutions.

  • Salaries: $100K–$150K USD for developers with Java-based AI/agent expertise.

  • Growth: Demand for Java agentic systems is rising as organizations automate complex business workflows and integrate LLM capabilities into enterprise software.

9.7Expert Score
Highly Recommendedx
Vanderbilt’s three-course series delivers end-to-end mastery: from foundational agent architectures to advanced patterns and prompt engineering. Its hands-on Java projects ensure that graduates not only understand theory but can implement, debug, and deploy robust AI agents in real business contexts.
Value
9
Price
9.2
Skills
9.4
Information
9.5
PROS
  • Deep dive into core agentic principles with Java’s enterprise capabilities
  • Three project-driven courses totaling 36 hours of hands-on work
  • Covers safety, memory, multi-agent coordination, and prompt engineering
CONS
  • Assumes solid Java background—less suited for absolute beginners
  • Relies on paid OpenAI API access for examples

Specification: AI Agents in Java with Generative AI Specialization

access

Lifetime

level

Beginner

certificate

Certificate of completion

language

English

FAQs

  • Basic AI knowledge is helpful but not mandatory.
  • A solid Java background is essential.
  • Focus is on building autonomous AI agents, not general AI theory.
  • Hands-on projects help you learn by implementing real-world AI agents.
  • Prompt engineering and agent orchestration are taught step by step.
  • Yes, the course teaches full-stack agent implementation in Java.
  • Includes multi-agent coordination, memory sharing, and safety patterns.
  • You’ll learn to integrate agents with tools and workflows in production environments.
  • Real-world labs simulate enterprise automation scenarios.
  • Prepares learners for roles in fintech, IoT, and large-scale software solutions.
  • AI Engineer (Java).
  • Agentic Systems Architect.
  • ML Engineer specializing in autonomous agents.
  • Software Developer for enterprise AI automation.
  • Salaries range $100K–$150K USD for skilled Java agent developers.
  • Focused on Java-centric autonomous agent architectures.
  • Covers multi-agent orchestration, safety patterns, and prompt engineering.
  • Emphasizes production-ready agent systems rather than theoretical models.
  • Provides hands-on labs to build, test, and deploy real AI agents.
  • Unlike generic AI courses, it is tailored to enterprise automation with Java.
  • Yes, access to paid OpenAI API is needed for some examples.
  • Knowledge of Java’s reflection and annotation processing is recommended.
  • Labs simulate real-world integration of AI models into Java agents.
  • Basic understanding of APIs helps in customizing agent behavior.
  • The course guides learners through safe and effective API use.
AI Agents in Java with Generative AI Specialization
AI Agents in Java with Generative AI Specialization
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