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AI Automation Mastery in 18 Days

Name: AI Automation Mastery in 18 Days
Rating: 4.1 (18 reviews)

Build real AI-powered automations, workflows, and agents — from APIs to RAG to full production systems.

Created bySchool of AI

Last updated 2/2026

English

What you'll learn

Design and build end-to-end AI-powered automation systems from trigger to production deployment
Integrate LLMs (Large Language Models) into workflows using APIs, structured prompts, and JSON outputs
Implement Retrieval-Augmented Generation (RAG) using embeddings and vector databases for knowledge-based AI systems
Develop and deploy AI agents capable of multi-step reasoning and tool usage with proper guardrails
Create intelligent business automation workflows for sales, support, operations, and KPI monitoring
Apply error handling, monitoring, logging, and cost optimization techniques for production-grade reliability
Distinguish between deterministic workflows and autonomous agents, and choose the right architecture for a given use case
Ship a complete, production-ready AI automation system with governance, oversight, and measurable performance metrics

Course content

6 sections • 37 lectures • 3h 14m total length

Certificate of Completion0:29
Complete course on Udemy to receive a certificate of completion, download your Udemy certificate, email it to School of AI at gmail.com, and we will verify completion and send certificate.
Day 1 – AI Automation Fundamentals8:07
Define automation as structured, rule-based workflows and learn how AI serves as a predictive brain inside agents that execute, integrate, and leverage systems for scalable outcomes.
Hands-on: Map your first automation opportunity2:05
Day 2 – Automation Thinking9:58
Develop a systems mindset for automation by recognizing repetition, defining triggers, logic, and outputs, and visualizing workflows to turn daily tasks into scalable, proactive processes.
Hands-on: Convert a manual process into a workflow map1:56
Day 3 – APIs & Webhooks Basics9:52
Explore how APIs and webhooks enable real-time automation by exchanging JSON data, handling requests and responses, and designing scalable, interoperable workflows.
Hands-on: Make your first API call and trigger a webhook1:37

Day 4 – No-Code Automation Platforms9:22
Explore no-code automation platforms to design visual, cross-app workflows using triggers, actions, and modules, turning ideas into executable systems with rapid prototyping and strategic tool selection.
Hands-on: Build a simple cross-app workflow1:38
Day 5 – Build Your First Automation8:27
Design and deploy your first working automation by building a trigger, mapping data, connecting two apps, testing the workflow, and debugging errors for scalable automation.
Hands-on Project: Form submission → Data capture → Notification system2:03
Day 6 – Data Handling in Automations9:05
Refine automation by mastering data flow, variables, field mapping, and data cleaning and transformation to ensure clean, structured input and reliable workflows at scale.
Hands-on: Create a structured data transformation workflow1:55
Day 7 – Logic & Error Handling8:59
Apply logic, conditional branching, retries, and error handling with fallback paths to build resilient, production-grade automation that adapts, recovers, and stays reliable under real-world failures.
Hands-on: Add error handling to your workflow1:40

Day 8 – AI Model Basics9:12
Explore how large language models generate text as probabilistic predictors, mastering tokens, context windows, and temperature, and distinguish prompts from system instructions for reliable AI-powered automation.
Hands-on: Test prompts across models1:48
Day 9 – Using AI Inside Automations8:09
Embed AI as a decision engine inside intelligent automation by calling AI models via API, designing structured prompts, enforcing JSON outputs, and parsing for routing.
Hands-on Project: Build an AI-powered classification workflow1:46
Day 10 – Prompt Design for Automation8:21
Design deterministic prompts with strict output schemas and guardrails to make AI automation reliable. Reduce hallucinations, handle edge cases, and version prompts as production infrastructure.
Hands-on: Convert messy AI output into structured data1:49

Day 11 – Text-Based Task Automation8:27
Automate text-based tasks by building email drafting, CRM enrichment, and concise summaries through structured prompts and AI, with human-in-the-loop oversight to ensure safe, actionable workflows.
Hands-on: AI email reply generator1:52
Day 12 – Knowledge Automation (RAG Basics)8:33
Ground AI by connecting models to your internal knowledge with retrieval augmented generation. Build embeddings and vector databases to enable document Q&A anchored in policies and contracts.
Hands-on: Build a simple document Q&A system2:17

Day 13 – AI Agents Basics8:42
Shift from deterministic workflows to autonomous AI agents that plan, select tools, and execute actions toward a goal. Learn planning loops, memory, and guardrails that keep agents safe.
Hands-on: Create a simple task-executing agent1:42
Day 14 – Business Use Case Automation8:18
Shift from capability to business impact by designing AI automation for lead qualification, support triage, internal reporting, and KPI monitoring to move revenue, reduce cost, and speed decisions.
Hands-on Project: AI-powered support triage system1:46
Day 15 – Sales & Marketing Automation8:41
Design revenue-driven automation by implementing AI-powered lead scoring, personalized outreach, and follow-up automation that optimize campaigns and integrate with intelligent crm to accelerate growth.
Hands-on: AI-powered outbound campaign builder1:47

Day 16 – Operations Automation8:35
Automate tasks, intelligent alerts, and approval routing with internal AI assistants to strengthen governance and reduce operational friction across back-office processes.
Hands-on: Build an internal AI ops bot3:29
Day 17 – Monitoring & Optimization8:12
Shift from building to measuring by implementing monitoring and optimization of AI automation. Measure execution success, accuracy, cost, and latency; implement logging and feedback loops to create observable, scalable infrastructure.
Hands-on: Add logging + performance tracking2:00
Day 18 – Build & Ship Your System8:12
Design, test, and ship a complete production-ready AI automation system by integrating all components with guardrails, monitoring, and documentation to deliver measurable business impact.
Final Capstone Project: Build a complete AI-powered automation system3:23

Requirements

No prior AI experience required — this course starts from fundamentals and builds step-by-step
Basic computer literacy (comfortable using web applications and online tools)
Familiarity with spreadsheets or simple digital tools is helpful but not mandatory
An interest in automation, AI systems, or improving business workflows
A laptop or desktop computer with reliable internet access
Willingness to experiment, test workflows, and learn by building

Description

“This course contains the use of artificial intelligence”

Welcome to AI Automation Mastery in 18 Days, a structured, hands-on program designed to help you build real-world AI-powered automation systems from scratch — and take them all the way to production.

This course is your complete roadmap to mastering AI automation, workflow design, no-code automation tools, API integrations, webhooks, LLM integration, prompt engineering, RAG (Retrieval-Augmented Generation), AI agents, and production deployment.

Over 18 focused days, you will learn how to design, build, monitor, and optimize intelligent systems that automate real business processes.

You will begin by mastering automation fundamentals, understanding the difference between AI vs automation vs agents, and learning how to break down workflows into structured triggers, logic, and outputs. From there, you’ll move into API development basics, REST APIs, JSON handling, and webhook triggers so you can connect applications seamlessly.

Next, you’ll build real workflows using modern no-code automation platforms like Make, Zapier, and n8n, learning data mapping, conditional logic, and error handling. You will integrate OpenAI models, enforce structured JSON outputs, and design deterministic prompts for reliable results.

You’ll then level up with AI model integration, learning how Large Language Models (LLMs) work, how to control token usage, reduce hallucinations, and design robust AI-driven decision engines.

A major highlight of this course is mastering RAG architecture and vector databases, where you’ll build intelligent systems that retrieve and reason over your own documents. You’ll understand embeddings, semantic search, and how to build a complete document Q&A system powered by AI.

From there, you’ll explore AI agents, learning how to design systems that perform multi-step reasoning, use tools dynamically, and operate with guardrails. You’ll compare deterministic workflows vs autonomous agents, and learn when each architecture is appropriate.

The final modules focus on business automation, including:

Lead qualification automation
AI-powered support ticket routing
Sales and marketing automation
CRM enrichment with AI
Internal operations automation
KPI monitoring systems
Intelligent alerting workflows

You’ll also learn critical production skills like:

AI monitoring and observability
Cost optimization for API usage
Latency reduction
Logging and performance tracking
Governance and guardrails
Deployment best practices

By the end of this course, you won’t just understand AI automation — you will have built a complete end-to-end AI automation system from trigger to execution to monitoring.

This course is ideal for:

AI engineers
Automation specialists
Product managers
Startup founders
Operations leaders
Anyone building AI-native systems

If you want to master AI workflows, automation architecture, LLM integration, RAG systems, and agentic AI design — and build production-ready intelligent systems — this course gives you the complete blueprint.

Welcome to the future of AI-powered automation infrastructure.

Who this course is for:

AI Engineers & Developers who want to move beyond prompts and build production-grade automation systems
Automation Specialists looking to integrate LLMs, RAG, and AI agents into real workflows
Product Managers who want to design AI-powered features and intelligent business systems
Startup Founders & Entrepreneurs building AI-native products or internal automation infrastructure
Operations Leaders seeking to reduce manual processes and improve internal efficiency
Sales & Marketing Professionals who want to implement AI-driven lead scoring, personalization, and campaign automation
Technical Consultants & Freelancers who want to offer AI automation services to clients
Business Analysts & Strategists interested in leveraging AI for measurable performance improvement
Professionals transitioning into AI Engineering, Automation Architecture, or Agentic AI roles
Anyone serious about building real-world, production-ready AI systems, not just experimenting with tools

AI Automation Mastery in 18 Days

What you'll learn

Explore related topics

Course content

Foundations of Automation Thinking7 lectures • 34min

No-Code Workflow Building8 lectures • 43min

AI Model Integration6 lectures • 31min

Knowledge & Text Automation4 lectures • 21min

AI Agents & Business Automation6 lectures • 31min

Operations & Production Systems6 lectures • 34min

Requirements

Description

Who this course is for: