Building Your Own AI Applications for Non-Programmers – Websites, Automations, Databases and Chatbots

Training process

Training needs analysis

If you have specific requirements regarding the training programme, we will carry out a training needs analysis for you. This will guide us on which aspects of the programme should receive greater emphasis, so that the training programme meets your specific needs.

What will you gain?

Understand how a web app works - You will see what happens from a browser click to a server response, so you can plan your own website or app more confidently and better judge what AI should build for you.

Get comfortable with Git and GitHub - You will learn how to track changes, restore earlier versions, and publish your project in a repository, so your collaboration with AI coding agents stays organized and clear.

Launch projects with AI coding agents - You will set up your workspace, explore Claude Code and Codex, and learn how to assign tasks, review edits, and keep development safe while building your application.

Build and publish your own website - You will go through the full process from goals and content to design, mobile responsiveness, and GitHub-based deployment, leaving the training with a working website.

Give AI better instructions - You will learn how to write clear specs, break work into stages, manage context, and create reusable instructions, so the agent delivers more predictable and accurate results.

Connect apps to APIs and databases - You will understand JSON, endpoints, and core backend concepts, then use Supabase and safely connect your own application to external services and structured data.

Create a customer support chatbot - You will build a chat widget, connect it to a language model, and handle cases such as order status, returns, FAQs, and smooth handoff to a human team member when needed.

Improve testing, security, and deployment - You will learn how to test apps with AI support, spot bugs and security risks, protect user data, and then deploy, monitor, back up, and control the ongoing cost of your app.

Training programme

1. How a website and web application work

the path of a request from the browser to the server – basics of the HTTP protocol,
frontend and backend – roles of the individual layers of the application,
HTML, CSS and JavaScript – the most important concepts without the need to learn syntax,
domain, DNS and hosting,
what the entire process of creating and publishing a web application looks like.

2. Git and GitHub in working with AI agents

what a repository and the history of changes what it is,
commits, branches and restoring earlier versions,
delegating Git operations to an AI agent,
controlling changes performed by the agent,
GitHub as a place for storing and publishing the project.

3. AI agents for code creation – Claude Code and Codex

how agentic coding differs from a classic conversation with a chatbot,
Claude Code, Codex and other tools supporting the creation of applications,
preparation and configuration of the work environment,
launching the first project,
agent permissions and approval of changes,
limits, costs and safe work with agents.

4. Practical project – creating a website with the help of AI

defining the goal and project requirements,
preparing materials for the website,
presentation of the offer, services and prices,
customer references and integration of the map,
refining the appearance of the website,
creating a responsive version for phone and computer,
publishing the website from the GitHub repository.

5. Effective collaboration with an AI agent

preparation of a good specification of the application,
defining the goal and functionality,
the agent's work planning mode,
dividing large tasks into smaller stages,
CLAUDE.md and AGENTS.md files,
creating permanent instructions for the agent,
managing session context,
detecting and correcting errors with the help of AI AI.

6. Skills and subagents

what skills are and when it is worth creating them,
consolidating repetitive ways of an agent's work,
creating your own skill from scratch,
preparing a description of the task and model examples,
using additional materials and instructions,
creating subagents with a separate context,
subagent as a code reviewer,
subagent as an application tester,
using ready-made skills and plugins,
assessing the security of external extensions.

7. Practical project – team work schedule

defining tasks, deadlines and owners,
determining dependencies between tasks,
building the project timeline,
preparing a Gantt chart,
signaling the risk of delays,
import of tasks from CSV files,
storing data in the browser,
generating a status report to PDF,
use of your own skill,
automatic code quality control by the agent.

8. API and communication between applications

what API is and what it is used for,
requests and responses between systems,
the structure of data JSON,
endpoints and basic backend tasks,
connecting applications with external services,
secure storage of API keys and secrets,
use of the API of Claude and GPT models,
building AI functions in your own application.

9. Databases in web applications

what an application needs a database for,
tables, records, fields and relationships,
designing the structure of the database data with the help of AI,
preparation of the data model,
working with the Supabase cloud database,
saving and reading data from the application.

10. Practical project – AI chat for customer service

defining the scope of matters handled by the chatbot,
order status, returns and product availability,
preparation of the subagent team,
planning, coding, testing and reviewing agent,
preparation of the product, orders, returns and FAQ database,
creation of a chat widget on the website,
integration of the chat with the language model,
equipping the model with tools for checking data,
forwarding unusual matters to an employee,
storing conversation history.

11. Testing and application security

automatic tests prepared by the AI agent,
controlling the correctness of the operation of the application,
use of MCP servers,
testing the application in a manner similar to user operation,
searching for potential security vulnerabilities with the help of AI,
protection of user data,
basic principles of processing personal data in accordance with GDPR.

12. Publishing and maintaining applications

preparation of the application for deployment,
basics of using Docker,
selection of hosting or a server,
publication of the application on the internet,
connecting your own domain,
monitoring the operation of the application,
creating backup copies,
updates and project maintenance,
control of the operating costs of the application.

What are the prerequisites for participating in the training?

Comfortable computer use - You should be able to move around your operating system, install simple programs, work with files and folders, and use a web browser without needing extra support.

Basic internet literacy - You should understand how to use online services, forms, and web accounts, because the training involves cloud tools, external platforms, and publishing a live project.

Readiness for basic English - You should be comfortable with simple technical English, since some tool names, interface messages, and documentation will appear in English while working with AI agents.

Clear task description skills - You should be able to describe a goal, key steps, and the expected outcome clearly, because the training focuses on giving effective AI instructions and structuring project work.