AI Web Application Development

Q15

AI models like GPT, Claude, Gemini, and Llama are becoming standard tools — widely available and easily accessible. The real value, however, comes from developers who know how to steer these models, ground them in real-world data, and seamlessly integrate them into user interfaces.

In this 16-week course, you’ll learn to compose AI-driven user experiences from end to end. Using Next.js, you’ll integrate server-side logic and front-end interactivity seamlessly, enabling real-time data streaming and AI-powered features. TypeScript will help you write scalable, error-free code, while Postgres and pgvector allow you to ground AI models with real-world data for applications like search or recall-augmented generation.

You’ll deploy everything smoothly using Docker, and manage your codebase with Git and GitHub for efficient collaboration. Push your creativity further with Fal.AI for image generation and ElevenLabs for voice, adding new layers of interactivity to your applications.

Key Highlights:

100% online with flexible, hands-on learning
Build 4 solo projects and 1 team-based open-source project
Led by industry-expert coaches
Work with real software repos: user stories, pull requests, and code reviews
Learn through a process that mirrors real-world development

100% funded by the

At a glance

Max. participants: 12

Duration: 16 weeks (~30 hours per week)

Cost: 9491.20 € (100% funded by the Bundesagentur für Arbeit)

Entry requirements

Computer Skills: You should be comfortable using a computer.
Web Basics: You need a basic understanding of HTML, CSS, and JavaScript.
Language Skills: Proficiency in both English and German (B1 level).

Before joining, you’ll complete an interview and pair-programming session to ensure you have the required skills to succeed.

Starting dates

Mar 10, 2025

Ends on Jul 7, 2025

Apply now

Curriculum

This course isn’t about passive learning or sitting through endless lectures. It’s about learning the skills that make you valuable in today’s world — steering AI models, grounding them with real-world data, and composing them into dynamic user experiences. Over 16 weeks, you’ll go through two phases of hands-on learning, where you build real projects that prepare you to solve real problems.

Learning Phases

Weeks 1 - 12: Individual Projects
In the first 12 weeks, you’ll complete four projects that guide you from mastering the basics of AI integration to tackling complex, multi-layered applications. These aren’t just exercises — they are real-world problems designed to teach you how to make AI models work for business needs, how to handle data, and how to build user interfaces that seamlessly integrate AI. Each project builds on the previous one, growing in complexity and depth, helping you reinforce key skills like responsive design, real-time data streaming, authentication, and data persistence — all while integrating advanced AI features.

Weeks 13 - 16: Open-Source Project
In the final 4 weeks, you'll join your peers to work on a real open-source project. This is where all your learning comes together. You’ll experience what it’s like to work in a professional development team — collaborating on code, using version control, managing CI/CD pipelines, and applying Agile methodologies. You’ll also face real-world challenges like integrating multiple AI models and solving problems in a live environment. It’s the ultimate preparation for the teamwork and problem-solving you’ll need in the industry, and it positions you to create the kind of value that businesses are searching for.

What you'll learn

A young developer working on code at his desk during sunset, with two monitors displaying programming code. The warm glow of the sunset contrasts with the cool tones of the room, creating a focused yet relaxed atmosphere. A rubber duck sits on the desk, likely used for debugging, and plants add a touch of nature to the workspace.

Integrating AI Models in Web Applications

Learn to seamlessly integrate AI into your web applications. You'll start by generating content like text, images, and audio using powerful AI models. As you progress, you'll master working with Large Language Models and other advanced tools, equipping you to transform your applications with cutting-edge AI technology. This isn't just about theory—every concept you learn will be directly applied in the projects you work on, giving you the practical skills needed to build intelligent, responsive web applications.

A developer working on a computer with code on the screen, visualizing data connections and AI models interacting above the monitor. The scene illustrates the integration of AI into web development, with vibrant digital networks extending from the computer. A rubber duck, a common debugging tool, sits on the desk, adding a touch of humor and familiarity to the workspace.

Building Scalable Full-Stack Web Applications

It’s not just about AI—your app needs a solid foundation. You’ll dive into the latest web technologies like TypeScript and Next.js to build scalable, maintainable applications. Learn how to create robust client-server architectures with server-side rendering, static site generation, and API routes. You’ll also get hands-on with state management and server actions, ensuring your applications are as efficient as they are powerful.

A developer stands in front of a laptop, explaining a complex network of AI models and processes visualized behind her. The image illustrates the concept of chaining AI models to perform multi-step tasks. A rubber duck sits on the desk, symbolizing the debugging process. The scene emphasizes the strategic integration and optimization of AI technologies to create intelligent applications.

Chaining and Integrating AI Models for Intelligent Applications

Good AI developers know that it’s not just about using a single model. It’s about combining them to get the best results. You’ll learn to chain AI models together—think of models writing prompts for other models—to perform complex, multi-step tasks. From text generation and image creation to speech processing, you’ll discover how to integrate models from different providers, optimizing performance and cost. As AI features mature, this skill will set you apart, allowing you to build more efficient, intelligent applications.

A developer working on a computer screen, designing a user interface with various layout elements visible. The image highlights the process of implementing responsive and accessible UI/UX designs. A rubber duck, commonly used for debugging, sits on the desk, adding a familiar touch to the scene. The environment suggests a focus on creating user-friendly and inclusive applications.

Implementing Responsive and Accessible UI/UX Designs

A good app isn’t just about looks—it’s about making sure everyone can use it. You’ll master UI and UX design principles while sharpening your coding skills. Learn how to create responsive designs that work on any device and ensure accessibility for all users. This module covers essential tools like Figma, design systems, and atomic design principles. You’ll also dive into CSS frameworks like Tailwind to build interfaces that are both visually appealing and user-friendly.

A developer sits at a desk, analyzing a complex flowchart on the screen that visualizes Agile workflows and processes. The image highlights the practical application of Agile methodologies in software development. A rubber duck, commonly associated with debugging, is placed on the desk, adding a familiar and lighthearted element to the workspace.

Agile Methodologies in Software Development

Shipping features is what it’s all about. You’ll master Agile methodologies—not as buzzwords, but as practical tools to get things done. Learn how to use frameworks like Scrum and Kanban to keep projects on track. From daily stand-ups to sprint planning and retrospectives, you’ll gain hands-on experience in managing the workflows that get features out the door. Plus, you’ll tackle real-world challenges like effort estimation, technical debt, and handling bugs and feature requests, all within the dynamics of an Agile team.

A developer sits at a desk, reviewing code on a monitor with the text bubble "LGTM" (Looks Good To Me) displayed. The scene highlights the process of code review and version control. A rubber duck, symbolizing debugging, is placed on the desk. The setting emphasizes the importance of careful code management and review in the development process.

Version Control and CI/CD

Even if you’re not a DevOps engineer, knowing how your code makes it to production is crucial. You’ll learn the fundamentals of version control with tools like Git and GitHub, covering everything from branching and merging to managing pull requests. Then, dive into Continuous Integration/Continuous Deployment (CI/CD) with tools like GitHub Actions and Vercel. You’ll set up pipelines that automate testing, integration, and deployment, ensuring your applications are always ready for production.

A developer sits at a desk, engaged in a virtual interview displayed on one monitor, with a job application and resume visible on another screen. A thought bubble above shows job search elements like resumes and applications, reflecting the focus on career development and job preparation. A rubber duck, symbolizing the debugging process, sits on the desk. The scene emphasizes the importance of strategic job search techniques, guided by professional insights.

Career Development and Job Preparation

This isn’t just about landing your first job—it’s about building a successful career in tech. Guided by experienced developers, you’ll learn how to craft resumes and cover letters that truly showcase your skills. But we go beyond that. You’ll optimize your LinkedIn profile, develop a strong professional brand, and master interview techniques with real-world insights. Plus, you’ll get strategic advice on spotting good teams and companies, helping you navigate the job market not just for now, but for the long haul.

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