NBI · 30 YH credits · 2026
Artificiell intelligens – programmering Python
Python for data analysis, visualization, secure programming, FastAPI, and practical AI integration.
I lecture on data science, AI, and MLOps for teams that need more than a trend overview. I break down how the technology works, where it is useful, and where its limits matter, then connect those ideas to decisions people make at work.
Discuss a lecture or workshopTell me about the audience, the topic, and what they should be able to do afterward.

A clear introduction or deeper technical talk, shaped around the questions your audience needs answered.
A working session that connects concepts to your team’s use cases and decisions.
A structured learning path that joins technical foundations with practical exercises.
Examples from vocational higher education, combining explanations, hands-on labs, and applied projects.
NBI · 30 YH credits · 2026
Python for data analysis, visualization, secure programming, FastAPI, and practical AI integration.
NBI · 30 YH credits · 2026
I taught the later part of this course, covering dimensionality reduction, clustering, model deployment, and group projects.
Nackademin · 30 YH credits
CI/CD for machine learning, including automated tests, data validation, model delivery, Docker, and Kubernetes.
Nackademin · 25 YH credits
Protecting data and ML models through IAM, risk analysis, secure deployment, and compliance with GDPR and NIS2.
Three students describe what it is like to learn with me. Their reviews are published on Superprof.
I am a partner at Yrkeshögskoleutbildarna and teach at JENSEN education. I also build AI systems and write about critical reasoning, which keeps my teaching close to practical engineering and good evidence.