AI-101
Low Code n8n Agentic AI Development & Modern Python Programming
Master Modern Python programming with static typing and develop robust n8n workflows for Agentic AI. Learn to orchestrate plan-act-observe agent loops with tool calling, memory management, and guardrails. Gain skills in Model Context Protocol (MCP), Retrieval-Augmented Generation (RAG), and deployment (self-hosted or cloud). Prepares for L1:P1-N8N and L1:P2-FMP certifications.
Available Sections:
Details
AI-101 serves as a comprehensive gateway to Python programming for Artificial Intelligence and Low Code Agentic AI Development. This foundational course emphasizes modern Python programming skills with static typing—a cornerstone of robust, scalable AI projects. You’ll design robust n8n workflows and orchestrate plan-act-observe agent loops that call tools, keep memory, and respect guardrails. The curriculum spans foundational agentic concepts through advanced techniques, including Model Context Protocol (MCP), Retrieval-Augmented Generation (RAG), and deployment (self-hosted or cloud), preparing you for L1:P1-N8N and L1:P2-FMP certifications.
Key Learning Modules
Module 1Modern Python Programming with Static Typing
Establish a strong foundation in Modern Python programming with a focus on static typing for robust and maintainable AI applications. Learn Python syntax, data structures, control flow, and type hinting to ensure code clarity and scalability in AI projects.
Module 2Introduction to Agentic AI and n8n Workflows
Explore foundational concepts of Agentic AI and learn to design robust n8n workflows for automating AI-driven processes. Understand the principles of low-code development and how n8n integrates with AI systems.
Module 3Plan-Act-Observe Agent Loops
Master the design and orchestration of plan-act-observe agent loops, incorporating tool calling, memory management, and guardrails to ensure safe and efficient AI operations.
Module 4Advanced Agentic AI Techniques: MCP and RAG
Dive into advanced Agentic AI concepts, including Model Context Protocol (MCP) for structured AI interactions and Retrieval-Augmented Generation (RAG) for enhancing AI responses with external knowledge.
Module 5AI Deployment: Self-Hosted and Cloud
Learn to deploy AI solutions in both self-hosted and cloud environments. Understand the tools and techniques for scalable and secure AI deployment, ensuring operational efficiency.
Module 6Certification Preparation: L1:P1-N8N and L1:P2-FMP
Prepare for L1:P1-N8N and L1:P2-FMP certifications through hands-on exercises and review of key concepts in Modern Python programming and Agentic AI development with n8n.
Course Outcomes
Write proficient Modern Python code utilizing static typing for robust and maintainable AI applications.
Design and implement robust n8n workflows for Agentic AI development.
Orchestrate plan-act-observe agent loops with tool calling, memory management, and guardrails.
Apply Model Context Protocol (MCP) and Retrieval-Augmented Generation (RAG) in AI projects.
Deploy AI solutions in self-hosted or cloud environments.
Prepare for L1:P1-N8N and L1:P2-FMP certifications.
Prerequisites
There are no pre-requisites for this course.