What will you learn in Building AI Agents and Agentic Workflows Specialization course
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Understand the fundamentals of AI agents and how they differ from traditional AI systems.
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Learn how to design and build autonomous, task-oriented AI agents.
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Implement agentic workflows using large language models (LLMs).
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Integrate tools, APIs, and memory systems into agent architectures.
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Build multi-agent systems for complex problem-solving tasks.
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Apply safety, monitoring, and responsible AI principles in agent-based systems.
Program Overview
Introduction to AI Agents and Agentic Systems
⏳ 3–4 weeks
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Learn what AI agents are and how they operate autonomously.
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Understand agent planning, reasoning, and decision-making concepts.
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Explore real-world use cases of agent-based AI systems.
Designing Agent Architectures
⏳ 4–5 weeks
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Learn about memory, tools, and environment interaction.
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Build single-agent workflows using LLM-based reasoning.
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Understand orchestration and state management.
Multi-Agent Systems and Tool Integration
⏳ 4–5 weeks
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Design multi-agent collaboration frameworks.
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Integrate APIs, databases, and external tools into agent workflows.
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Build scalable, modular agent systems.
Deployment, Safety, and Monitoring
⏳ 3–4 weeks
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Deploy agent-based applications in production environments.
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Monitor performance and control agent behavior.
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Apply guardrails and responsible AI practices.
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Job Outlook
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Highly relevant for AI Developers, ML Engineers, and Automation Engineers.
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Growing demand for professionals skilled in AI agents and workflow automation.
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Valuable for roles such as AI Application Engineer, Agent Systems Developer, and AI Automation Specialist.
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Aligns with emerging trends in generative AI, LLM orchestration, and enterprise automation.
