AI Agents & Automation for Business: Build No-Code Systems

In this lecture, students will learn what AI agents are and how they use instructions, data, tools, memory, and decision-making capabilities to complete tasks. They will explore practical examples of AI agents used for customer support, lead management, appointment booking, content creation, and business administration. By the end of the lecture, students will be able to explain how an AI agent works and distinguish it from a basic chatbot or traditional software application.

In this lecture, students will learn how business automation uses technology to complete repetitive tasks with limited manual effort. They will explore triggers, actions, conditions, data movement, notifications, integrations, and approval processes. Practical examples will include automated customer follow-ups, lead capture, invoice notifications, data entry, appointment reminders, and report generation. By the end of the lecture, students will be able to identify business processes that can be automated and describe the basic structure of an automation workflow.

In this lecture, students will discover practical ways small businesses can use AI to reduce operating costs, respond to customers faster, generate leads, create marketing content, organize data, and improve productivity. They will examine examples from retail, consulting, education, hospitality, professional services, and online businesses. By the end of the lecture, students will be able to identify high-impact AI opportunities within a small business and connect each opportunity to a measurable business result.

In this lecture, students will learn how to communicate effectively with ChatGPT and other generative AI tools. They will understand how role, task, context, examples, constraints, and output format influence the quality of an AI response. Students will practise transforming vague instructions into clear and structured prompts. By the end of the lecture, they will be able to write reusable prompts that produce more accurate, relevant, and business-focused results.

In this lecture, students will learn how to use ChatGPT to support sales and marketing activities. They will create prompts for social-media content, promotional campaigns, product descriptions, sales messages, customer personas, lead-generation ideas, advertising copy, and follow-up communication. By the end of the lecture, students will be able to produce structured marketing content that matches a defined audience, offer, platform, and business objective.

In this lecture, students will learn how to create prompts for professional and consistent customer support. They will develop responses for frequently asked questions, complaints, refunds, order updates, appointment requests, service enquiries, and difficult customer situations. Students will also learn how to define escalation rules and protect sensitive information. By the end of the lecture, they will be able to design a customer-service prompt that reflects a company’s policies, tone, and service standards.

In this lecture, students will learn how to use ChatGPT for everyday administrative and office tasks. They will create prompts for reports, meeting summaries, emails, proposals, agendas, data-cleaning instructions, project updates, standard operating procedures, and executive summaries. By the end of the lecture, students will be able to turn unstructured information into clear, professional, and actionable business documents.

In this lecture, students will be introduced to n8n as a visual workflow automation platform. They will explore the n8n workspace, workflow canvas, nodes, credentials, executions, templates, and integration options. Students will see how n8n connects applications and moves data automatically between them. By the end of the lecture, they will be able to navigate the platform and explain how n8n supports no-code and low-code business automation.

In this lecture, students will learn how workflows begin and how tasks are performed inside n8n. They will examine trigger nodes, action nodes, input data, output data, fields, parameters, expressions, connections, and execution results. Students will also learn how information passes from one node to another. By the end of the lecture, they will be able to read a simple workflow and explain the purpose of each connected node.

In this practical lecture, students will build and test their first n8n workflow. They will configure a trigger, add an action node, map information between nodes, execute the workflow, inspect the results, correct errors, and activate the automation. By the end of the lecture, students will have a functioning workflow and understand the basic process for creating, testing, troubleshooting, and publishing an n8n automation.

In this lecture, students will learn how to structure Google Sheets as a simple and reliable business database. They will create clearly defined columns for customer details, lead sources, contact information, order records, dates, workflow stages, payment status, and follow-up activities. Students will also learn the importance of unique identification numbers, consistent field names, data validation, and clean formatting. By the end of the lecture, they will have a structured Google Sheets database ready to connect with automation tools.

In this lecture, students will learn how to capture leads from an online form and automatically save the submitted information in Google Sheets. They will connect tools such as Tally or Google Forms to n8n, receive customer information through a trigger, map the submitted fields, and create a new database record. Students will also test the workflow to ensure that each lead is recorded correctly. By the end of the lecture, they will have a working automated lead-capture system.

In this lecture, students will learn how to use Google Sheets and n8n to track customers, enquiries, orders, payments, and follow-up activities. They will create workflow stages such as new lead, contacted, interested, payment pending, completed, and closed. Students will also learn how to search for existing customers, update records, prevent unnecessary duplicates, and maintain accurate order histories. By the end of the lecture, they will have a basic customer and order-tracking system for managing business operations.

In this lecture, students will learn how to prepare the WhatsApp Business Cloud API for automation. They will explore the Meta for Developers environment, create or configure an application, connect a WhatsApp Business account, obtain the required identification details, and understand the role of access tokens and test phone numbers. Students will also learn how to protect credentials and prepare the account for integration with n8n. By the end of the lecture, they will understand the technical foundation required for WhatsApp automation.

In this lecture, students will learn how to create an automated WhatsApp response system using the WhatsApp Business Cloud API and n8n. They will configure a webhook to receive incoming messages, extract the sender’s details and message content, process the request, and send an appropriate reply. Students will also explore rule-based responses and AI-generated customer-support messages. By the end of the lecture, they will have a basic WhatsApp automation that can receive and respond to customer enquiries.

In this lecture, students will build a customer follow-up system that combines WhatsApp, n8n, and a customer database. The workflow will record customer enquiries, classify their status, schedule follow-up messages, and update the database when customers respond or complete an action. Students will also learn how to avoid excessive messaging, respect customer preferences, and transfer complex cases to a human team member. By the end of the lecture, they will have an automated follow-up process for improving customer engagement and lead conversion.

In this lecture, students will learn how to use AI to create a structured 30-day content calendar for a business, product, service, or personal brand. They will define the target audience, business objective, content themes, publishing platforms, formats, and calls to action. Students will generate ideas for educational, promotional, engaging, trust-building, and conversion-focused content across platforms such as Instagram, Facebook, TikTok, LinkedIn, and WhatsApp. By the end of the lecture, they will have a practical monthly content plan that can be adapted and automated.

In this lecture, students will learn how to design a simple AI-supported sales funnel that guides potential customers from awareness to purchase. They will explore the major funnel stages, including traffic generation, landing pages, lead capture, qualification, follow-up, offer presentation, payment, and post-purchase communication. Students will also learn how AI and automation can personalise messages, organize leads, and support faster follow-up. By the end of the lecture, they will be able to map a complete sales funnel for a product or service.

In this lecture, students will learn how to add payment links from platforms such as Paystack, Flutterwave, or Stripe to a sales funnel. They will explore how customers move from a landing page or message to a secure payment page and how automation can respond after payment. Students will learn how to send confirmation messages, update customer records, notify the business, deliver the next instruction, and follow up with customers whose payments are incomplete. By the end of the lecture, they will understand how to connect payment activity with an automated customer journey.

In this lecture, students will discover practical AI automation services they can offer to businesses, entrepreneurs, organisations, and professionals. These services include automated lead capture, WhatsApp customer support, appointment booking, customer follow-up, content creation, email automation, data management, sales funnels, payment notifications, and business reporting systems. Students will learn how to identify a client’s operational problem and match it with an appropriate automation solution. By the end of the lecture, they will be able to create a clear service catalogue based on the skills developed throughout the course.

In this lecture, students will learn how to price AI automation services based on the value delivered, project complexity, required tools, implementation time, ongoing costs, and level of support. They will explore one-time setup fees, monthly retainers, maintenance packages, consultation fees, and tiered service options. Students will also learn how to avoid underpricing and communicate the financial value of saving time, improving customer service, or increasing sales. By the end of the lecture, they will be able to create clear pricing packages for different types of clients.

In this lecture, students will learn practical methods for finding clients locally and internationally. They will explore direct outreach, referrals, social media, LinkedIn, freelance platforms, business communities, networking events, partnerships, and personal branding. Students will learn how to identify businesses with automation problems, conduct a simple business audit, present a relevant solution, and write personalised outreach messages. By the end of the lecture, they will have a repeatable client-acquisition strategy for promoting their AI automation services.

In this capstone lecture, students will combine the major skills learned throughout the course to build a complete business automation system. The final project may include lead capture, customer data storage, conditional processing, AI-generated responses, WhatsApp communication, follow-up automation, payment verification, and business notifications. Students will plan the workflow, connect the required tools, map the data, test each stage, correct errors, and document the completed system. By the end of the lecture, they will have a functional project that can be demonstrated to employers, clients, or business partners.

In this concluding lecture, students will review the knowledge and practical skills developed throughout the course. They will learn how to improve their projects, build a professional portfolio, document their workflows, continue practising, and present their automation skills to clients or employers. Students will also receive guidance on choosing a specialisation, developing advanced skills, and turning their course projects into real business solutions. By the end of the lecture, they will have a clear professional action plan for continuing their AI automation journey.

In this lecture, students will learn how to write a professional proposal for an AI automation project. They will identify the client’s current problem, explain the recommended solution, define the project scope, list the expected deliverables, establish a timeline, present the investment, and clarify support arrangements. Students will also learn how to explain technical solutions in simple business language and connect the proposed automation to measurable outcomes. By the end of the lecture, they will be able to prepare a clear and persuasive proposal for a potential client.