In the current Artificial Intelligence (AI) spring, the rapid development affects different areas differently, and the same is true for professional development on AI. In some areas there is a need for a narrow and specialised training on specific AI tools and techniques. Regarding artificial intelligence in education (AIED), several research studies have highlighted the need for a broader professional development that involves all teachers and instructional designers. This study has investigated the design and implementation of a 7.5 ECTS standalone distance course on AIED and its first preliminary evaluation. The course participant group consisted of a high percentage of fulltime working teachers with a clearly higher average age than most courses at a department of education. The aim of the study is to explore the course participants opinions and their feedback in the very first version of this course. With the idea of iterative design science research, the results from this study will be used for input for the updates and redesign of the next course versions. Data were collected in a mix of discussion fora postings, course webinars and the official course evaluation. Findings show that the heutagogical design approach was appreciated by the course participants. Solutions to several assignments could be seen as takeaways for further discussions on how to implement AIED in the course participants daily workplace activities. This also seems to be the case for course participants working in other professions such as journalists, lawyers and in digital media. What was appreciated most was the combination of concrete workshops, reflection essays and group discussions in course webinars. Regarding the assignments it was appreciated that it was clearly stated to what degree AI-tools were allowed in the creation of solutions. Areas of development could be found regarding the relatively high workload, and the problem of organising course participants in communities of practice for group work and the exchange of experiences. The conclusion is that the main course structure with the four sections of 1) Introduction and tool testing, 2) AI in Education, 3) Multimodal AI, and 4) Discussion webinars as knowledge cafés should be maintained, but that all sections should be revised and updated in the next course version.