Building Agentic AI Systems for Developers

Overview

These hands-on courses equip developers and engineers with the technical skills to design, build, and deploy autonomous AI agents using frameworks to automate complex workflows and create intelligent, decision-making systems. Developers will work with multiple frameworks including AutoGen, LlamaIndex, and LangGraph while building real-world applications such as advanced chatbots and task automation systems.Learn implementation patterns and responsible AI principles.Evaluate and experiment with emerging agentic technologies.Implement multiagent AI systems using the AutoGen framework.Build and deploy autonomous AI agents with LlamaIndex.

Syllabus

• Introduction to Agentic AI Systems
Overview of autonomous AI agents
Key concepts in agentic AI
Practical applications and use cases
• Agent Frameworks Overview
Introduction to AutoGen
Introduction to LlamaIndex
Introduction to LangGraph
• Designing Autonomous AI Agents
System architecture for AI agents
Workflow automation design patterns
Building decision-making capabilities
• Working with AutoGen
Setting up the development environment
Implementing multiagent AI systems
Practical exercises with AutoGen
• Working with LlamaIndex
Integrating LlamaIndex with AI systems
Building and deploying autonomous agents
Task automation with LlamaIndex
• Working with LangGraph
Graph-based AI system design
Connecting LangGraph with other frameworks
Enhancing system intelligence with graph approaches
• Building Advanced Chatbots
Designing intelligent conversational agents
Implementing natural language understanding
Use cases and practical exercises
• Task Automation Systems
Designing robust automation workflows
Incorporating AI agents in business processes
Case studies and real-world applications
• Implementing Responsible AI
Principles of ethical AI development
Bias and fairness in AI systems
Ensuring transparency and accountability
• Evaluating Emerging Agentic Technologies
Exploring new frameworks and tools
Experimenting with cutting-edge agentic technologies
Future trends in autonomous AI systems
• Course Project
Planning and designing a real-world AI agent
Developing, testing, and deploying the agent
Presenting and discussing project outcomes
• Conclusion and Next Steps
Review of key concepts and skills
Guidance for further learning and development
Opportunities in the field of agentic AI systems

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Taught by

Kumaran Ponnambalam, Jose Luis Latorre, Harshit Tyagi and Ray Villalobos

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Subjects

Computer Science