AI Courses

AI (artificial intelligence) now covers everything from ChatGPT and Microsoft Copilot to classic machine learning and computer vision. Our AI courses give you practical knowledge of how to use, develop and run AI solutions, whether you use AI day to day, work as a developer or work with data and models.

AI courses

Generative AI & prompt engineering

Learn to use ChatGPT, Claude and Microsoft 365 Copilot effectively in your daily work: prompt engineering, concrete workflows and safe use of generative AI, without writing a single line of code.

LLM integration & RAG

Build your own solutions on top of large language models: call LLM APIs from Python, give the model access to your own data with retrieval-augmented generation (RAG), orchestrate with LangChain, evaluate output, and run models locally with LM Studio.

AI agents

Learn to build autonomous AI agents with tools such as Microsoft Copilot Studio, Azure AI Foundry Agent Service and Semantic Kernel. From simple single-task agents to multi-agent systems in Power Platform and Azure.

AI-assisted development

Learn to use GitHub Copilot, Claude Code, Codex and Cursor effectively in your day-to-day development, from vibe coding and rapid prototypes to maintainable, secure production code, built on the technical foundation (Git, Python, SQL, the terminal) that lets you steer the AI and evaluate the results.

Machine Learning & Deep Learning

Master machine learning and deep learning in Python with scikit-learn, TensorFlow and PyTorch, and deploy models with Azure Machine Learning and MLOps.

AI strategy & governance

Get an overview of how your organization can adopt generative AI and Microsoft 365 Copilot responsibly and strategically, from business case and governance to administration and compliance.

Azure AI & Microsoft Foundry

Databricks and Synapse Analytics/Fabric give your organization the freedom to analyze data with classic SQL or more complex code in Python/Scala.

Microsoft Copilot

Microsoft Copilot is Microsoft's AI assistant across Microsoft 365, GitHub and security work. With Copilot Studio and agents, it is also a platform where organizations build their own AI solutions. We offer courses for end users, administrators and developers.

AI in brief

AI (artificial intelligence) covers the methods and technologies that enable computers to perform tasks that used to require human insight: recognizing patterns, understanding and generating language, interpreting images and supporting decisions. Under AI, we bring together courses on everything from language models and generative AI to classic machine learning, computer vision, and the platforms and languages you use to build and run AI solutions, including Python, Azure AI, Databricks, Microsoft Fabric and Microsoft Copilot.

Three types of AI you encounter at work

AI is an umbrella term for a wide range of very different technologies, and it helps to be able to tell them apart, because they place different demands on data, skills and infrastructure.

Generative AI

Models that create new content, such as text, images, code and speech. Language models like GPT and Claude are the most widespread type right now and power most of what we call AI in the workplace today, from ChatGPT to Microsoft Copilot.

Classic Machine Learning

Models that find patterns in structured data and make predictions or classifications, such as churn, transactions, and leads. These methods are typically based on historical data and require significantly less computing power than large language models.

Deep learning and specialized models:

Neural networks applied to images, audio and time series, and the core technology behind computer vision and speech recognition. It is also the architecture that the language models in generative AI are built on.

Language models and the ecosystem around them

OpenAI's ChatGPT, Anthropic's Claude, and Microsoft's Copilot are among the most widely used large language models (LLMs), and today they are delivered through APIs, browser tools, and integrations in Microsoft 365. Together they form the foundation for most productive AI use in Danish companies right now, from using ChatGPT as an individual sounding board to automated workflows built with tools such as LangChain and RAG (retrieval-augmented generation).

From everyday user to AI development

AI in the workplace covers very different roles. As a user, you typically work with ready-made tools in Word, Excel, Teams, and the browser, such as Microsoft Copilot and ChatGPT. As a developer or data specialist, you build solutions yourself: you call LLM APIs from Python, train and evaluate models on data from Databricks or Microsoft Fabric, and version-control the code in Git. The wide range of technologies in this category reflects the fact that, in practice, AI is rarely a single tool but an interplay of language models, data, and infrastructure.

SuperUsers' approach to AI

We have taught programming, data, and cloud for more than 25 years, and we follow developments in generative AI closely. Our instructors work with the models in their own daily work, and the courses are updated continuously as tools and models evolve. This means you get courses that build on hands-on experience and focus on what actually makes a difference in your day-to-day work.