What You'll Learn
- Design and implement single-agent and multi-agent AI systems using modern agent architectures
- Build AI agents with memory, planning, reasoning, and tool-calling capabilities
- Deploy retrieval-augmented, data-driven, and multi-modal AI agents for real-world tasks
- Orchestrate, monitor, and optimize agent workflows for performance, cost, and reliability
- Apply security, governance, and responsible AI principles to production-grade agents
- Integrate AI agents into enterprise workflows across HR, finance, IT, and operations
Requirements
- No prior experience with AI agents or agent frameworks is required
- Basic familiarity with programming concepts (any language) is helpful but not mandatory
- Comfort using a computer, web tools, and cloud-based applications
- Willingness to experiment, troubleshoot, and learn through hands-on labs
- Access to a laptop or desktop with internet connectivity
- Optional: prior exposure to Python, APIs, or LLM tools will accelerate learning but is not required
Who This Course is For
- Software engineers and developers who want to build autonomous, tool-using AI agents
- Data scientists and ML practitioners expanding into agentic and multi-agent systems
- AI engineers and architects designing scalable, production-ready agent platforms
- Technical leaders and solution architects exploring enterprise AI automation
- Founders, builders, and product teams creating AI-powered applications and workflows
- Professionals transitioning into AI roles who want practical, hands-on experience with agents
Your Instructor
Siam Hossain
Executive Leader
4.6 Instructor Rating
55 Reviews
8,889 Students
8 Courses
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