Advanced AI Agents: Code-Based Frameworks & System Design
Description
This hands-on technical course teaches you how to design, build, and deploy intelligent agent systems using modern Python frameworks. You’ll move beyond basic LLM prompting to create structured, debuggable, and scalable agentic workflows.
What You’ll Learn:
Smolagents Fundamentals
Understand the manager–worker architecture, build specialized tools with the
Understand the manager–worker architecture, build specialized tools with the
@tool decorator, and orchestrate multi-agent collaboration where LLMs plan, delegate, and execute tasks predictably.LangGraph for Deterministic Workflows
Master graph-based agent design: define stateful nodes, implement explicit edge-based routing, and build resumable, human-in-the-loop workflows that remain testable and production-ready.
Master graph-based agent design: define stateful nodes, implement explicit edge-based routing, and build resumable, human-in-the-loop workflows that remain testable and production-ready.
MCP (Model Context Protocol)
Learn to decouple tools from agent logic by hosting capabilities on remote servers, enabling dynamic tool discovery and secure, scalable agent-tool communication.
Learn to decouple tools from agent logic by hosting capabilities on remote servers, enabling dynamic tool discovery and secure, scalable agent-tool communication.
Boilerplate Patterns & Best Practices
Apply proven scaffolding techniques: problem-first design, self-contained node blocks, LLM-as-worker principles, and state-driven interruption/resumption for robust real-world systems.
Apply proven scaffolding techniques: problem-first design, self-contained node blocks, LLM-as-worker principles, and state-driven interruption/resumption for robust real-world systems.
Curriculum
- 11 Sections
- 42 Lessons
- 4 Weeks
Expand all sectionsCollapse all sections
- Section 1: Smolagents 1.1 - Introduction to Smolagents5
- Section 1: Smolagents 1.2 - MCP Concepts4
- Section 1: Smolagents 1.3 - Smolagents Boilerplate with Simple Tools5
- 3.1Lesson 1.3.1: Local-First Architecture Overview
- 3.2Lesson 1.3.2: Model Initialization: Establishing the Reasoning Engine
- 3.3Lesson 1.3.3: Tool Design: Defining Explicit Capabilities
- 3.4Lesson 1.3.4: Specialist Agents: ToolCalling Agents with Clear Ownership
- 3.5Lesson 1.3.5: Manager Agent & Execution Flow
- Section 1: Smolagents 1.4 - Smolagents Boilerplate Using MCP Tools6
- Section 1: Smolagents 1.5 - Problem Statement1
- Section 2: Langgraph 2.1 - Introduction to Langgraph5
- Section 2: Langgraph 2.2 - LLM & Tool Integration in LangGraph5
- Section 3: Langgraph 2.3 - Framework Comparison - Smolagents vs LangGraph5
- Section 4: Langgraph 2.4 - Boilerplate for deterministic workflow and practice2
- Section 3: Practical Agents4
- Quiz1
Instructor
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Price
₹9,999.00
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