AI Automation Bootcamp Curriculum | Adron Digital
Official curriculum · Cohort 1 · Version 1.0

AI Automation Bootcamp: 12 weeks of building with Make.com.

A beginner-friendly, project-based program taught directly by Adron Digital. Students learn how AI and automation work, then build, test and document real business automations on Make.com, finishing with six guided projects, an independent capstone and a portfolio.

12 weeksAbout 90 days, one module per week
Make.comCore platform for every build and project
BeginnersNo coding experience required
2 live sessions / weekLive build workshop plus live Q&A, with replays
6 projects + capstoneGraded against clear acceptance criteria
5 to 7 hrs / weekRecorded lessons, practice and assignments
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Who teaches it

Designed and delivered by Adron Digital.

Adron Digital is an AI automation and digital marketing agency based in Birmingham, Alabama. We build Make.com automations for real businesses and teach those same skills to beginners. Every lesson, live workshop, project review and piece of feedback in this bootcamp is delivered directly by our instructors. We do not resell third-party course content.

Led by Ronald, founder of Adron Digital, with more than nine years in digital marketing, an MBA with a business analytics concentration, and hands-on experience building Make.com automations for client businesses.

How the program is delivered

  • 3 to 5 recorded lessons released each week
  • Weekly live build workshop (60 to 90 min)
  • Weekly live office hours and Q&A (45 to 60 min)
  • Instructor feedback on every submitted project
  • Replays, sample data and templates in our learning hub
  • Structured cohort with a fixed start date and schedule
Learning outcomes

What students can do by graduation.

A student who completes the practical work should be able to map a business process, build and troubleshoot Make.com scenarios, integrate AI responsibly, and present a working automation as a portfolio case study or client proposal.

  • Explain AI, LLMs, AI automation and AI agents, including their limitations
  • Write effective prompts and request structured outputs
  • Understand triggers, actions, data mapping, JSON, APIs, webhooks and authentication basics
  • Build, test, monitor and troubleshoot Make.com scenarios
  • Use AI for classification, extraction, drafting and research, with validation and human approval
  • Deliver six guided automations plus an independently designed capstone
  • Estimate tool costs, protect customer data and document maintenance responsibilities
  • Create portfolio demonstrations, freelance offers and client proposals
Curriculum map

Week by week.

Six phases: Foundations (weeks 1 to 3), Build (4 to 7), Agents (8), Applications (9), Career (10 to 11) and Graduation (12). Tap any week to see its lessons, live workshop, project and submission.

Week 01AI and Automation FundamentalsFoundations

Learning objective: Explain core concepts without jargon and recognize which tasks are (and are not) good candidates for automation.

Recorded lessons

  1. Welcome and how the bootcamp works
  2. What AI is (and is not): LLMs, limitations, hallucinations
  3. Traditional automation vs AI automation
  4. The automation ecosystem: Make.com, ChatGPT, Claude, Google Workspace and APIs
  5. Career and freelance pathways with realistic beginner expectations

Live workshop

Live business process identification exercise

Hands-on project

Map five repetitive business tasks and rank them by time saved, complexity and risk.

Submission

Opportunity worksheet with one chosen automation idea

Business lab

Which simple workflows could a small business pay to have improved?

Week 02Prompt Engineering and AI CollaborationFoundations

Learning objective: Write clear instructions and get reliable, machine-readable output from AI models.

Recorded lessons

  1. Prompt structure: role, task, context, constraints, examples, format
  2. Prompt iteration and evaluating quality
  3. Working with ChatGPT and Claude
  4. Structured outputs and JSON
  5. Safe and responsible AI use: privacy, fact checking, human approval

Live workshop

Build a supervised customer inquiry classification assistant

Hands-on project

Prompts for support classification, marketing drafts and structured data extraction.

Submission

Three tested prompts with example outputs

Business lab

How prompt-based services lead to broader automation work

Week 03Data Flow, JSON, APIs and WebhooksFoundations

Learning objective: Understand how applications exchange information before building complex scenarios.

Recorded lessons

  1. Triggers, actions and conditions
  2. Business data basics: records, fields, tables, mapping
  3. Reading JSON: objects, arrays, nested values
  4. API essentials: endpoints, GET/POST, headers, authentication
  5. Webhooks explained, and how they compare to polling
  6. Drawing workflow diagrams

Live workshop

Trace a form submission across three applications

Hands-on project

Diagram a Form to Google Sheets to Email workflow and annotate fields and failure points.

Submission

Labeled workflow architecture diagram

Business lab

How to scope an integration before quoting a client

Week 04Make.com FundamentalsBuild

Learning objective: Build, test and explain a first end-to-end Make.com scenario.

Recorded lessons

  1. Getting started in Make: scenarios, modules, connections, usage
  2. Your first scenario: trigger, action, test run
  3. Google Sheets operations: create, search, update, map
  4. Filters and routers
  5. Scheduling and debugging with execution history

Live workshop

Build the lead capture scenario from scratch

Hands-on project

Project 1: Form to Sheets lead capture with owner notification.

Submission

Working scenario, screenshot, sample test and a 2 minute demo

Business lab

Packaging lead capture for small businesses

Week 05Business Process AutomationBuild

Learning objective: Automate routine operations with the right safeguards.

Recorded lessons

  1. Process discovery: current state, repeatability, exceptions
  2. Email workflows: drafts, notifications, formatting
  3. Google Workspace integrations: Forms, Sheets, Gmail, Drive
  4. Follow-up logic: statuses, timers, deduplication
  5. Testing and documentation for handover

Live workshop

Build a customer follow-up system with approval before any outbound message

Hands-on project

Project 2: Inquiry tracker with scheduled follow-up reminders and duplicate prevention.

Submission

Working workflow, test cases and setup notes

Business lab

Pricing ongoing workflow maintenance

Week 06AI-Powered Automation with MakeBuild

Learning objective: Add AI to a workflow without giving it unchecked authority.

Recorded lessons

  1. Connecting AI models: API keys, tokens, usage cost
  2. AI calls inside a Make scenario
  3. Classification and extraction
  4. AI drafting with human review
  5. Validation and safety: JSON checks, fallbacks, privacy, cost caps

Live workshop

Build and test AI email triage using synthetic customer data

Hands-on project

Project 3: AI email triage that categorizes inquiries and creates drafts for approval.

Submission

Scenario, classification test set, sample drafts and cost notes

Business lab

Positioning AI-assisted inbox management responsibly

Week 07APIs, Webhooks and ReliabilityBuild

Learning objective: Connect an external API and handle failure conditions properly.

Recorded lessons

  1. The HTTP module: methods, URLs, headers, bodies
  2. JSON parsing and nested arrays
  3. Custom webhooks: creating, testing, validating payloads
  4. Errors and retries: timeouts, rate limits
  5. Production basics: logging, idempotency, credentials, handover

Live workshop

Create an API reporting pipeline and simulate failures

Hands-on project

Project 4: Pull data from a sample API, transform it and update a reporting sheet.

Submission

Scenario, API request example, error test and documentation

Business lab

Estimating integration scope and risk

Week 08AI Agents with Make.comAgents

Learning objective: Build a narrowly scoped, supervised AI agent in Make.com.

Recorded lessons

  1. What makes an AI agent: model, instructions, tools, decisions
  2. Agent design: permissions, context, guardrails
  3. Make AI Agent capabilities and setup
  4. Building a research agent with approved sources
  5. Agent testing and safety: prompt injection, tool limits, human approval

Live workshop

Build a bounded research agent with a review checkpoint

Hands-on project

Project 5: Supervised research agent that drafts a structured report from approved sources.

Submission

Agent demo, evaluation checklist and failure analysis

Business lab

When a client needs an agent vs a simpler workflow

Week 09Applied Business Automation SystemsApplications

Learning objective: Adapt reusable automation patterns to real business needs.

Recorded lessons

  1. AI content drafting with editorial approval
  2. Review management: intake, draft response, human review
  3. Invoice triage: document intake, extraction, exception queue
  4. Marketing reporting: data collection and KPI summaries
  5. Voice AI overview: components, use cases, cost and complexity

Live workshop

Instructor walkthrough of real-world style business automations using sample data

Hands-on project

Project 6: Choose one: content drafting, invoice triage or marketing report assistant.

Submission

Working workflow, user instructions and video demo

Business lab

Turning a reusable workflow into a defined service package

Week 10Freelancing, Niches and Service OffersCareer

Learning objective: Create a realistic offer around a validated business problem.

Recorded lessons

  1. Finding automation opportunities
  2. Choosing a niche
  3. Service packaging: audit, implementation, support, training
  4. Pricing and profitability
  5. Prospecting ethically

Live workshop

Review student service offers and scope boundaries

Hands-on project

One clearly scoped service offer, price estimate and discovery questionnaire.

Submission

Offer sheet and pricing calculator

Business lab

Fixed-fee builds vs monthly support

Week 11Portfolio, Proposals and Client DeliveryCareer

Learning objective: Show evidence of competence and plan a professional handover.

Recorded lessons

  1. Portfolio case studies: problem, solution, demo, limitations
  2. Freelance profiles: Upwork, Fiverr, LinkedIn
  3. Discovery calls and proposals
  4. Client delivery: onboarding, permissions, documentation, training
  5. Career development roadmap

Live workshop

Portfolio critique and mock discovery calls

Hands-on project

Publish two case studies, draft a proposal and record a demo video.

Submission

Portfolio links, proposal and client handover checklist

Business lab

Building credibility without inventing client results

Week 12Capstone and GraduationGraduation

Learning objective: Design, test and present an independent automation.

Recorded lessons

  1. Choosing the business problem and success measure
  2. Planning the architecture
  3. Building and testing: happy path, edge cases, errors
  4. Documentation and demo
  5. Next steps: maintenance, portfolio, career plan

Live workshop

Student capstone demos and constructive review

Hands-on project

Capstone: An end-to-end Make.com automation solving a clearly defined business problem.

Submission

Problem brief, architecture, working scenario, test log, cost note, 3 to 5 minute demo and case study

Business lab

Turning a capstone into a credible first sales conversation

Guided projects

Six Make.com projects, each with acceptance criteria.

ProjectMinimum workflowAcceptance criteria
1. Lead captureForm submission → Google Sheets record → owner notificationCorrect mapping, successful test, handles a blank optional field
2. Customer follow-upInquiry intake → status tracking → follow-up reminderNo duplicates, clear status logic, no unapproved customer messages
3. AI email triageSample message → AI classification → human-approved draftCorrect categories, structured output, documented fallback
4. API reportingSample API → JSON parsing → Google Sheets reportValid request, correct mapping, evidence of error handling
5. Research agentApproved sources → bounded agent task → report for reviewSource traceability, human approval, safe tool permissions
6. Business automationContent drafting, invoice triage or reporting assistantMeets the selected brief, test evidence, handover instructions
CapstoneAn independent end-to-end automation for a defined business problemProblem brief, architecture, working scenario, test log, cost note, demo and case study
Assessment

How students are graded.

ComponentWeight
Weekly exercises30%
Six guided projects30%
Capstone30%
Portfolio and presentation10%

Certificate of completion: 70% overall, a submitted capstone and all core technical projects. One documented resubmission is allowed. This is a course completion certificate, not an accredited industry certification.

Capstone rubric

What a strong capstone shows.

DimensionPoints
Problem definition and workflow design20
Functional automation and data mapping30
Testing, error handling and safe permissions20
Documentation and cost awareness15
Demonstration and communication15
Tools and learner support

Built for beginners, wherever they learn from.

CORE PLATFORM

Make.com

Every guided project and the capstone are built in Make.com: scenarios, routers, HTTP, webhooks, error handling and AI agents.

AI MODELS

ChatGPT and Claude

Used for prompting practice and inside Make scenarios, always with validation and human approval for anything customer-facing.

BUSINESS APPS

Google Workspace

Forms, Sheets, Gmail and Drive, the everyday tools most small businesses already use.

LEARNING HUB

Lessons, replays, templates

Recorded lessons, dated live replays, downloadable Make scenario templates, workbooks and sample datasets.

LOW BANDWIDTH

Learn on your schedule

Replays and downloadable files support learners with intermittent connectivity or busy schedules.

SAFE PRACTICE

Synthetic data only

All demos and projects use sample data. No real customer information, passwords or API keys are ever shared.

Our teaching standards

Practical, honest and responsible.

  • Make.com is the single core workflow platform, so students go deep instead of wide
  • Human approval is taught for customer messages, financial actions and publishing
  • API costs, privacy, permission scopes and platform limits are explained before every demo
  • Projects are modular so students can succeed without buying expensive software
  • Simulated practice projects are clearly separated from real client work in portfolios
  • No promises of guaranteed jobs, clients or income
Cohort 1 · Founding students

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