Building Autonomous AI Agents
About This Course
This three-day hands-on course address the challenge of moving beyond traditional Artificial Intelligence (AI) Chatbot toward building autonomous AI agents capable of reasoning, decision-making and interaction dynamic environments. It equips participants with skills in building and deploying AI agents using framework such as LangGraph, as well as integrating tools and Application Programming Interface (API)s to enhance functionality. Participants will also learn to implement planning and memory for adaptive, context-aware behavior, and best practice for multi-agent systems design, orchestration and coordination.
What You'll Learn
While many developers are familiar with Large Language Model (LLM)s and prompt engineering, there is a shortage of expertise in orchestrating agents with planning, memory and tool use. This course fills that skills gap with practical training aligned to industry needs.
By the end of this course, participants will be able to:
- Explain the core concepts, architecture, and components of autonomous AI agents and their differences from traditional AI applications.
- Design and implement autonomous AI agents with planning, tool use, and
memory integration.
- Apply multi-agent collaboration and responsible autonomy principles, including guardrails, reliability, and cost optimization.
- Evaluate and deploy AI agents in a practical environment to validate real-world
performance.
Entry Requirements
Participants should have:
• Basic proficiency in Python programming.
• Familiarity with APIs and JSON data formats.
• Foundational understanding of AI/ML concepts.