Next session: 24 Apr 2026
AI Courses
Start building your AI skills with our AI courses
Artificial Intelligence is rapidly transforming how software is built and how organizations operate. From AI-assisted development and copilots to intelligent applications, professionals who know how to apply AI effectively gain a clear advantage. Standing still equals falling behind.
The real question is: how will you use AI in your work? Whether you want to work more efficiently with AI tools, build copilots and agents, integrate AI into applications or learn how to use data to train models, our AI training helps you develop the practical skills to start applying AI today.
Working Smarter with AI |
1
day |
Copilot Studio |
GitHub Copilot |
AI Development |
Data Science with Python |
Next session: 10 Aug -
14 Aug 2026 5
days |
Python Development |
4
days |
Microsoft 365 |
2
days |
| Price | Days | Apr | May | Jun | Jul | Aug | Sep | ||
|
UAIT
|
Working Smarter with AI: ChatGPT new | 475€ | 1 | 24 | 12 | 7 | 25 | ||
|
UM365CT
|
Working Smarter with AI: Microsoft 365 Copilot new | 475€ | 1 | 23 | 26 | 4 | |||
| Price | Days | Apr | May | Jun | Jul | Aug | Sep | ||
|
UPILOT
|
Building your own Agents with Copilot Studio | 1450€ | 3 | 26 | 29 | 17 | |||
| Price | Days | Apr | May | Jun | Jul | Aug | Sep | ||
|
UDCO
|
AI Assisted Development with GitHub Copilot new | 975€ | 2 | 16 | 4 | 16 | 27 | ||
| Price | Days | Apr | May | Jun | Jul | Aug | Sep | ||
|
UADAI
|
Developing AI-Powered Apps with C# and Azure AI | 1850€ | 4 | 20 | 8 | 3 | 21 | ||
|
UAMAI
|
Developing AI-Powered Apps with Python and Azure AI | 1850€ | 4 | 26 | 10 | 28 | |||
| Price | Days | Apr | May | Jun | Jul | Aug | Sep | ||
|
UTORCH
|
Building Neural Networks with PyTorch new | 2200€ | 5 | 10 | |||||
|
UADS
|
Building your own Models with Azure Machine Learning | 1450€ | 3 | 27 | 13 | 28 | |||
| Price | Days | Apr | May | Jun | Jul | Aug | Sep | ||
|
UPD
|
Python for Data and AI Engineers new | 1850€ | 4 | 18 | 13 | 24 | |||
| Price | Days | Apr | May | Jun | Jul | Aug | Sep | ||
|
UM365C
|
Managing Microsoft 365 Copilot | 975€ | 2 | 7 | 9 | 17 | |||
Work Smarter with AI tools
Many professionals want to benefit from AI today. In our courses Working Smarter with AI: ChatGPT and Working Smarter with AI: Microsoft 365 Copilot, you learn how to use modern generative AI tools to enhance your daily workflow, automate tasks, analyze information and create simple, practical AI solutions.
LOW-CODE AI DEVELOPMENT
Standard AI tools like ChatGPT are powerful out of the box, but remain relatively generic and limited when it comes to integrating with your own data, processes and systems.
Low-code platforms like Microsoft Copilot Studio address this by enabling organizations to build tailored, AI-driven agents that connect to internal data sources, automate workflows and support real business scenarios. They are especially valuable when customization and integration are required, without the need for technical or programming expertise.
Our course Building your own agents with Microsoft Copilot Studio teaches you how to quickly create and deploy custom agents tailored to your business needs.
GitHub Copilot
AI is the new foundation of software development. Tools like GitHub Copilot help developers write code faster, reduce repetitive work and focus on higher-value tasks. The real value emerges when these tools are tailored to your context: your codebase, standards and architecture. Using custom instructions and specialized agents leads to more relevant code, less rework and a faster development cycle. Today, understanding how to work with AI-assisted development tools is becoming a fundamental skill for every developer.
Want to speed up your development process? Enroll in our 2-day course AI Assisted Development with GitHub Copilot.
Developing AI-Powered Apps
Modern AI platforms such as Azure AI, combined with evolving libraries and agent frameworks, make it possible to build and deploy LLM-based solutions and agents in a structured and scalable way. This becomes especially relevant when customization, control and integration with existing applications are key. With the right approach, developers can add advanced AI capabilities to their applications, without needing to be data scientists.
To support this, we offer two dedicated courses: one focused on C# developers and one tailored for Python developers.
AI Development with C#
Our course Developing AI-Powered Apps with C# and Azure AI is tailored for professional C# developers. Gain hands-on experience with key libraries such as Microsoft Extensions AI and Microsoft Agent Framework and learn to seamlessly integrate pre-built AI services and Large Language Models into your .NET apps.
AI Development with Python
Our course Developing AI-Powered Apps with Python and Azure AI is tailored for professional Python developers. Gain hands-on experience with key libraries such as Microsoft Agent Framework and the Microsoft Foundry SDK and learn to seamlessly integrate pre-built AI services and Large Language Models into your Python projects.
Data Science & Machine Learning
While tools like LLMs and copilots focus on integrating AI into applications, data science is about building custom models tailored to specific business problems. When accuracy, control or domain-specific insights are critical, pre-built AI is often not sufficient.
Techniques such as neural networks and classical machine learning allow organizations to train models on their own data and solve targeted challenges like forecasting, anomaly detection or classification. To support this, we offer two courses.
Building Neural Networks with PyTorch
Build and train neural networks from scratch using PyTorch. In our hands-on course Building Neural Networks with PyTorch, you’ll learn how to design, train and optimize deep learning models with full control over architecture and performance.
Azure Machine Learning with Python
Learn how to develop, train and deploy machine learning models using Python and Azure Machine Learning. Our course Building your own Models with Azure Machine Learning focuses on practical implementation, from data preparation to model operationalization in a cloud environment.
