Inside AI and Automation for Beginners: A Module-by-Module Tour

The McTaba AI and Automation course contains 10 modules, 58 lessons, and roughly 18 hours of content. It moves from foundational AI concepts through generative AI, no-code automation, APIs, and AI agents, then ends with a capstone project. The full course costs KES 4,999 (one-time, M-Pesa or card), and Module 0 is free to preview.

Module 0: Start Here

This is your orientation module, and it is entirely free. No payment needed, no commitment required.

The welcome lesson (about 7 minutes) explains how the course is structured, what you will learn, and how to get the most from the material. It sets expectations clearly: this is a beginner course designed for people without a technical background.

The glossary lesson (about 10 minutes) defines the key terms you will encounter throughout the course. Rather than assuming you already know what an API is or what "machine learning" means, this lesson builds a shared vocabulary from the start.

We made Module 0 free deliberately. You should know whether the teaching style, pacing, and platform work for you before spending anything. If the welcome lesson feels too basic or too fast, that is useful information.

Module 1: What Is AI?

This module builds the conceptual foundation. Before you can use AI tools effectively, you need to understand what AI actually is, what it can do, and (just as importantly) what it cannot do.

The lessons cover the core concepts behind artificial intelligence, including how machines process data and recognize patterns. You will learn the difference between narrow AI (systems that do one task well, like spam filtering) and the broader concept of general AI that science fiction often depicts. The module grounds everything in practical examples rather than academic abstractions.

By the end of Module 1, you should be able to explain AI in plain language to a colleague and identify where AI is already operating in tools and services you use daily.

Module 2: AI vs Automation

This is a distinction most beginners miss, and it matters for making good decisions about which tools to use.

Automation follows predefined rules. If a customer sends a payment, automatically generate a receipt. That is automation: predictable, rule-based, and reliable. AI adds a layer of decision-making based on patterns. Classifying customer emails by intent, predicting which invoices are likely to be paid late, recommending products based on browsing history: these require AI because the rules are not fixed in advance.

Module 2 draws clear lines between these concepts so that when you encounter a business problem, you can judge whether it needs simple automation, AI, or a combination of both. This distinction saves time and money in the real world, because automation is simpler and cheaper to implement for problems that do not require pattern recognition.

Module 3: Generative AI

This is where the course gets hands-on with the tools most people associate with modern AI. ChatGPT, Claude, and similar generative AI systems have changed what non-technical people can accomplish, but only if you know how to use them well.

Module 3 covers how generative AI works at a conceptual level (without requiring math or programming), and then focuses on prompting: how to write instructions that produce useful output. Good prompting is not about memorizing tricks. It is about understanding what the model needs to give you a good response, including context, constraints, and clear goals.

The lessons move from basic prompting to more structured techniques for business tasks like writing, research, data analysis, and content creation. You will practice with real scenarios rather than toy examples.

Module 4: No-Code Automation

No-code tools let you build automated workflows without writing a single line of code. This module introduces the platforms and patterns that make automation accessible to non-developers.

You will learn how to create workflows that connect different services: when a form is submitted, add the data to a spreadsheet, send a confirmation via WhatsApp, and update a CRM. These are the kinds of workflows that save hours of manual work every week for small businesses and teams across Kenya.

The module focuses on practical automation patterns that solve real problems. You will learn to identify tasks in your own work that are repetitive and rule-based, then build automations that handle them.

Module 5: APIs for Beginners

APIs (Application Programming Interfaces) are how different software systems talk to each other. This module demystifies them for beginners, because understanding APIs is the bridge between using individual tools and building integrated systems.

You will learn what an API is, how to read basic API documentation, and how to connect services together. The module uses examples relevant to the Kenyan context, including payment APIs and messaging APIs. By the end, you will understand how to connect an AI tool to other services through their APIs, even without being a programmer.

This is often the module where learners report the biggest shift in how they see technology. Once you understand that almost every modern service has an API, you start seeing connection possibilities everywhere.

Module 6: AI Agents

AI agents are systems that can take actions on your behalf, not just answer questions. This module covers the spectrum from simple chatbots that follow scripts to more sophisticated agents that can reason through multi-step tasks.

You will learn how chatbots work, how they have evolved into more capable agents, and how businesses are using them. The lessons cover how to think about designing an agent for a specific use case, such as a customer service bot that handles common queries for a Kenyan e-commerce business.

Module 6 builds on everything from the previous modules. You need the AI foundations from Modules 1 through 3, the automation concepts from Module 4, and the API understanding from Module 5 to see how agents tie these pieces together.

Module 7: The African Tech Stack

This is where the course diverges most sharply from international AI programmes. Module 7 focuses on the tools and platforms that define the technology landscape in Africa, with particular attention to Kenya.

M-Pesa is the obvious example. Any AI or automation workflow targeting Kenyan users needs to account for mobile money as the dominant payment method. The module also covers WhatsApp Business (the primary customer communication channel for millions of African businesses), local SaaS tools, and the specific infrastructure considerations that come with building for markets where mobile-first is the only option.

If you have taken other AI courses and found the examples irrelevant to your daily reality, this module fills that gap. It contextualizes everything you have learned in the previous modules within the ecosystem you actually work in.

Module 8: Responsible AI

AI creates real risks when used carelessly: biased decisions, privacy violations, misinformation, job displacement. Module 8 addresses these directly, because knowing how to use AI tools is not enough. You also need to know when not to use them, and how to use them responsibly.

The lessons cover bias in AI systems (and why it matters especially in contexts like loan approvals and hiring in Kenya), data privacy considerations, the ethics of AI-generated content, and how to think critically about AI outputs rather than trusting them blindly.

This module is not a lecture about abstract ethical theory. It covers practical questions: How do you check if an AI recommendation is biased? What data should you never feed into a public AI tool? How do you explain AI-assisted decisions to people affected by them?

Module 9: Capstone Project

Everything comes together here. The capstone is not a multiple-choice test. It is a project where you apply the skills from all previous modules to build something functional.

You will define a problem, select appropriate tools (AI, automation, APIs), design a solution, and build it. The capstone gives you a portfolio piece you can show to employers, clients, or colleagues. It is the most valuable part of the course, because it proves you can integrate multiple skills into a working outcome.

The capstone is also where you will encounter real-world friction: tools not behaving as expected, workflows breaking, AI outputs requiring iteration. That friction is part of the learning. Working through it builds the problem-solving instinct that separates someone who completed a course from someone who can actually do the work.

Who should skip this course?

Honesty matters more than a sale. You should skip AI and Automation for Beginners if you already write code and work with APIs professionally. The course is designed for beginners, and the pacing will feel slow for experienced developers. You should also skip it if you want to become a machine learning engineer. This course covers AI literacy and practical application, not model training or data science.

If you want a career transition into software engineering, the course is a useful starting point, but it is not sufficient on its own. Read more about who the course is for and who should skip it for a fuller picture.

If you are deciding between this self-paced course and a more intensive format, the format comparison guide lays out the trade-offs plainly.

How to get started

Start with the free Module 0. The welcome lesson takes about 7 minutes, and the glossary lesson takes about 10 minutes. By the time you finish both, you will know whether the teaching style works for you.

If it does, enrollment opens access to all 10 modules at KES 4,999, one-time, paid by M-Pesa or card. No subscriptions, no upsells, no expiring access.

FAQ

How long does it take to complete all 10 modules?

The course contains roughly 18 hours of content across 58 lessons. At a pace of one hour per day, you can finish in about three weeks. At a more relaxed pace of a few hours per week, expect four to six weeks. The course is self-paced, so there are no deadlines.

Do I need any software or special equipment?

You need a device with internet access. A laptop is ideal, but the platform works on mobile as well. For the hands-on modules (generative AI, no-code automation, APIs), you will use free-tier versions of tools that run in your browser. No installations or paid software are required.

Can I skip modules and jump to the ones I care about?

Technically yes, but the modules are designed to build on each other. Skipping Module 5 (APIs) and jumping to Module 6 (AI Agents) will leave gaps in your understanding. We recommend going in order, at least on your first pass.

What if I get stuck on a lesson or project?

The course is designed for beginners, so lessons are structured to minimize confusion. If you do get stuck, each lesson provides context and examples to work through. The capstone project in Module 9 is the most challenging part, but by that point you will have built skills across all previous modules.

Is the capstone project graded?

The capstone is a practical project, not an exam. You complete it at your own pace and it becomes part of your portfolio. The certificate of completion is issued when you finish all modules, including the capstone.