Real-World AI Agents Training in Astana, Kazakhstan

This course focuses on the design, development, and deployment of AI agents capable of functioning in real-world environments—from digital workflows to physical systems. It covers agent architectures, reasoning, tool-use, APIs, multi-agent collaboration, and integration into business or operational pipelines. Emphasis is placed on practical applications (customer service, process automation, research, operations) and responsible deployment.

Foundations of Real-World AI Agents

• Evolution: From chatbots → LLMs → Agentic AI

• Core components: perception, planning, reasoning, action

• Types of agents: reactive, deliberative, hybrid

• Real-world applications: customer service, RPA, business intelligence, healthcare, finance

Tool-Using Agents

• Prompt engineering for autonomous workflows

• API integration (search engines, CRMs, booking systems, productivity tools)

• Knowledge retrieval (databases, vector stores, RAG)

• Error handling, fallbacks, and resilience in real-world settings

Multi-Agent Systems & Complex Workflows

• Architectures for multi-agent collaboration (specialist vs. generalist agents)

• Coordination and communication strategies among agents

• Human-in-the-loop integration for oversight and corrections

Deployment, Monitoring & Responsible AI

• Deploying agents in enterprise environments (cloud, Docker, APIs)

• Logging, monitoring, and feedback loops for agent performance

• Evaluation metrics for real-world success (accuracy, reliability, efficiency)

• Risks and governance: hallucinations, compliance, safety controls

Hands-on Exercises

Summary and Conclusion