No-Code AI Agents and Automation for Business

Distinguish an AI assistant, an automation, and an agent, then identify the level of complexity a task actually needs.

Score possible automation ideas by frequency, clarity, value, reviewability, and risk.

Create a complete workflow map with controls for privacy, errors, and human review.

Check your understanding before continuing. You need at least 70% to pass.

Write prompts that specify role, context, task, source input, constraints, output format, and a quality check.

Request consistent tables, records, checklists, drafts, and field-value outputs that another person or workflow can use.

Build a small test set, identify failure patterns, and improve a prompt without overfitting it to one example.

Organize approved prompts so another person can use them correctly and know when human review is required.

Check your understanding before continuing. You need at least 70% to pass.

Select tools by function, cost, data policy, integrations, and maintainability instead of chasing every new platform.

Translate a workflow map into the building blocks used by Zapier, Make, n8n, and similar platforms.

Prepare clean, minimal, well-labelled data and protect sensitive information throughout the workflow.

Build and test a manual AI workflow that converts messy tasks into priorities and a realistic follow-up plan.

Identify email tasks that benefit from AI drafting and define which messages require direct human handling.

Create a two-stage email workflow that first interprets the message and then drafts a response from verified information.

Build a respectful follow-up sequence that changes purpose over time and stops when the recipient responds or opts out.

Assemble and test a complete inquiry-to-reviewed-draft workflow.

Translate business fit into observable qualification criteria without using AI to make unfair or unsupported judgements.

Apply a rubric consistently and route leads to a suitable response, clarification, nurture, or escalation path.

Turn qualification gaps into natural questions, useful sales responses, and concise CRM records.

Build an intake-to-next-action lead workflow with explainable scoring and human control.

Create a campaign brief that connects audience, problem, offer, proof, channel, and call to action before generating content.

Transform a verified source into channel-specific assets while preserving meaning and avoiding invented claims.

Define a usable voice guide and review AI drafts for specificity, accuracy, usefulness, and human tone.

Build a repeatable workflow from campaign brief to approved weekly content calendar and performance learning.

Produce decision-ready summaries that preserve source meaning, uncertainty, actions, and important exceptions.

Plan research, collect credible sources, distinguish evidence from inference, and verify claims before use.

Turn verified notes and evidence into a concise report with a clear argument, limitations, and recommended actions.

Build a workflow that summarises source material, creates an evidence table, and produces a verified report draft.

Check your understanding before continuing. You need at least 70% to pass.

Define what a support assistant may answer, what sources it may use, and when it must hand off to a person.

Build clear, current, source-linked knowledge entries that an AI assistant can use reliably.

Test routine, ambiguous, adversarial, emotional, and out-of-scope questions before exposing an assistant to customers.

Assemble a knowledge-grounded FAQ assistant design with tested escalation and maintenance controls.

Select a business-owner, marketing, freelancer, admin, or customer-support workflow and define measurable success.

Create the working prototype, test normal and exception paths, and improve it using recorded evidence.

Present the automation clearly to an employer, client, or business owner without exaggerating its capability.

Pass this final assessment with at least 70% to complete the certificate requirement.