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AI Builder: Create Agents, Voice Agents & Automations in n8n

Become an AI Builder in 3 weeks. Build low-code AI Agents & Voice Agents in n8n v2.0 using ElevenLabs, Agentic RAG, MCP

  1. Topics
  2. Development
  3. N8N Automation Platform

AI Builder: Create Agents, Voice Agents & Automations in n8n

InstructorLigency ​
Duration14h 21m
Students37.4K
Rating4.8 (4,632)
Sponsored
Price
$14.99
Coupon
None
No active coupon currently available
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Open on UdemyCurrent Udemy price

Coupon history

Comidoc has tracked 3 coupons for this course since 2026, last checked 5 months, 20 days ago. On average, a new coupon appears roughly every 80 days.

Coupon codeDiscountAddedStatusLifetime
AI_MAR2620% offMar 25, 202609:48 PM UTCExpired10d 19h
AI_FEB2620% offFeb 25, 202602:54 PM UTCExpired8d 23h
AI_BUILDER15$14.99Jan 27, 202611:25 AM UTCExpired7d 19h
Comidoc Analysis

High-Velocity Agentic Automation with n8n

Strengths

Production-Oriented Agentic Patterns

Instruction moves beyond simple API calls to cover essential production concepts like context engineering, security boundaries, and maintainable agent architectures.

Editorial course preview

What the public course preview actually shows

These 4 complementary views highlight concrete, legible examples from the course presentation.

Preview 1 of 4

This structured syllabus maps a three-week course progression, starting with workflow automation in n8n and advancing to voice agents and multi-agent systems.

Preview 2 of 4

This screenshot displays two distinct n8n workflow diagrams: one for ingesting data into a Supabase Vector Store and another for an AI Agent connected to Google Gemini and Webhooks.

Preview 3 of 4

This slide outlines practical applications of AI tools like GPT 5.2 and Gemini 3, detailing three specific projects including an equity portfolio rebalancer and autonomous sales team.

Preview 4 of 4

This overview slide outlines core curriculum topics including n8n workflows, agent loops, context engineering, voice agents in ElevenLabs, and vector embeddings.

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Learn AI Tools & Build AI Agents for Testing & QA AutomationRahul Shetty Academy - 1.3 Million QA Learners4.6 (23.1K)11h 18m
AI Automation: Build LLM Apps & AI-Agents with n8n & APIsArnold Oberleiter4.6 (9,632)14h 30m
n8n - AI Agents, AI Automations & AI Voice Agents (No-code!)
Damian Danelczyk AdaptifyAI OU
4.5 (5,535)58h 40m
The Agentic AI Engineering Masterclass 2026Prof. Ryan Ahmed, PhD, MBA | 1M+ Students | #1 Best Selling AI Courses4.4 (7,520)13h 33m
AI Agent Creation Guide: N8N, Trinity, and Claude CodeAnton Voroniuk4.4 (747)4h 59m
Master n8n AI Agents: Build & Sell AI Agents and AutomationsManthan Patel4.5 (1,204)15h 8m
n8n + MCP: Automatización y agentes de IA inteligentesFernando Herrera4.7 (3,491)17h 50m
Formação Automação com Inteligência Artificial 2026 com n8nPaulo Andrade, PhD • +540.000 Alunos4.7 (2,146)76h 20m

Diverse Project-Led Learning

The curriculum features distinct projects including financial portfolio rebalancing, conversational voice agents with RAG, and multi-agent GTM systems using MCP.

Limitations

Evolving Tool Interfaces

External platforms like ElevenLabs and n8n have undergone interface changes, which can cause navigation confusion during the lessons.

High-Speed Instructional Pacing

The delivery can feel rushed, particularly during complex technical segments like MCP, and some learners find the screen zoom insufficient for following rapid clicks.

Best suited to

  • Entrepreneurs building AI automation agencies
  • Non-coders seeking practical agent deployment
  • Product managers prototyping agentic workflows

Less suited to

  • Learners requiring slow, highly detailed troubleshooting support
  • Those seeking deep software engineering theory
  • Users expecting perfectly static tool interfaces

Comidoc Score

6.7/10

Worth considering
Beginner-friendly

Comidoc verdict

The learning path transitions from basic workflow automation to advanced multi-agent orchestration using the Model Context Protocol. It emphasizes practical builds such as voice agents and automated lead generation systems.

Instruction covers significant concepts for a low-code course, including RAG pipelines and local deployments via Docker. However, learners should be prepared for a fast pace that may require pausing videos to follow specific clicks, alongside the reality that external tool interfaces often evolve faster than course content can be updated.

This training is best suited for motivated builders and entrepreneurs who prioritize deployment velocity and real-world utility over exhaustive theoretical foundations.

Score breakdown

Curriculum depth
8.0

Covers advanced topics like RAG and MCP, though some signals suggest it remains an introductory entry point for certain learners.

Applied learning
8.0

Strong emphasis on three distinct, high-impact projects that demonstrate real-world business utility.

Clarity & experience
4.3

Instruction is generally clear but suffers from high-speed pacing and insufficient screen visibility for some users.

Currency & reliability
5.0

While covering modern protocols like MCP, learners report friction due to frequent changes in external tool interfaces.

Audience fit
6.5

Selected from the course's public promotional preview. These images document visible presentation material only; they do not represent the complete paid curriculum.

Aligns well with the goal of building practical AI tools without heavy coding requirements.

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