Machine learning is becoming more and more applied within business and academia alike. This has led researchers to look inwards and discuss whether the current way of teaching and learning machine learning is the right way. Within this train of thought, one must investigate the characteristics of teaching and learning. Namely, what are the competences required to learn, and in what order should these be learned. This research paper focuses on realizing the answer to that question by combining past research papers on how to define competences, how to establish an order of competences, and how to establish competences through the help of questionnaires answered by academics within the machine learning sector teaching Computer Science students. The results from the academic analysis and the resulting data from the questionnaires are combined to organize a result, established through two different methods used by researchers. To conclude, the paper is reflected upon, and its merits, demerits, and trade-offs are summarized, presenting a final recommendation for any future work done on this topic.