Agentic AI in Practice: From LangGraph to OpenClaw
Data Science Academy
AI Engineering & Agent Systems
Build real AI agents and production-ready autonomous AI systems
AI is rapidly moving beyond simple chatbots and prompt-based tools. The next generation of AI systems are autonomous agents that can reason, plan tasks, use external tools, retrieve knowledge, and collaborate with other agents to complete complex work.
However, most developers and AI practitioners still struggle to understand how to design and engineer these systems in practice. Tutorials often focus on isolated demos, but they rarely teach the architecture, workflows, and engineering patterns required to build reliable agent systems.
This course bridges that gap.
You will learn how to design real agentic AI architectures using modern frameworks such as LangChain, LangGraph, RAG pipelines, vector databases, and the Model Context Protocol (MCP). Instead of just experimenting with prompts, you will understand how to build stateful agents, multi-agent systems, tool integrations, and production-ready AI workflows.
By the end of the course, you will have a clear mental model of how modern AI agent systems are designed, orchestrated, and deployed, giving you the skills to build next-generation AI applications and automation systems.
What you’ll learn
Learn how to design, build, and deploy autonomous AI agents using modern frameworks and real-world agent architectures.
Build agents using LangChain and LangGraph to execute structured workflows.
Understand ReAct, planner-executor, and supervisor-worker agent patterns
Create reliable agent pipelines with deterministic execution flows.
Implement tool calling and structured outputs for agent actions
Connect agents to APIs, databases, and external services
Design agent-tool interaction loops for complex task execution.
Build RAG pipelines using vector databases like FAISS or Pinecone
Design short-term and long-term memory for intelligent agents.
Use embeddings and context injection for knowledge retrieval.
Build role-based agent teams that coordinate tasks and share results
Build role-based agent teams that coordinate tasks and share results.
Implement communication patterns and shared memory across agents.
Understand MCP architecture including clients, servers, and tool registries.
Build MCP-compatible tools and integrate external systems.
Use MCP to connect AI agents with APIs, data sources, and services.
Implement logging, tracing, and observability for AI workflows
Optimize latency, reliability, and cost of agent systems.
Design scalable deployment architectures for autonomous agents.
Learn directly from Data
Data Science Academy
Building real-world AI systems, agents, and production ML architectures.
Who this course is for
Developers who want to build AI agents, tool integrations, and autonomous workflows using modern AI frameworks.
Professionals working with LLMs or ML who want to learn agent architectures and production AI systems.
Tech builders and founders interested in creating AI agents, multi-agent systems, and intelligent automation.
What's included
Live sessions
Learn directly from Data Science Academy in a real-time, interactive format.
Lifetime access
Go back to course content and recordings whenever you need to.
Community of peers
Stay accountable and share insights with like-minded professionals.
Certificate of completion
Share your new skills with your employer or on LinkedIn.
Maven Guarantee
This course is backed by the Maven Guarantee. Students are eligible for a full refund up until the halfway point of the course.
Course syllabus
Week 1
Day 1 - Foundations of Agentic AI
Day 2 - LLM Foundations for Agent Systems
Day 3 - Introduction to LangChain and Agent Frameworks
Day 4 - LangGraph Deep Dive
Day 5 - Advanced Agent Design Patterns
Day 6 - Memory Systems for Agentic AI
Day 7 - Tool Integration & External Systems
Week 2
Day 8 - Multi-Agent Systems
Day 9 - Model Context Protocol (MCP)
Day 10 - Production Agent Systems
Day 11 - OpenClaw Agent Framework
Schedule
Live sessions
2 hrs / week
Projects
4 hrs / week
Async content
14 hrs / week
Frequently asked questions
$400
USD