  In this paper we describe our experience in developing curriculum courses
aimed at graduate students in emerging computational fields, including biology
and medical science. We focus primarily on computational data analysis and
statistical analysis, while at the same time teaching students best practices
in coding and software development. Our approach combines a theoretical
background and practical applications of concepts. The outcomes and feedback we
have obtained so far have revealed several issues: students in these particular
areas lack instruction like this although they would tremendously benefit from
it; we have detected several weaknesses in the formation of students, in
particular in the statistical foundations but also in analytical thinking
skills. We present here the tools, techniques and methodology we employ while
teaching and developing this type of courses. We also show several outcomes
from this initiative, including potential pathways for fruitful
multi-disciplinary collaborations.
