In this course, we created four data exploration activities to introduce students to python and cloud computing via Jupyter Notebook frameworks. No prior understanding of coding was necessary or considered to be a prerequisite for taking this course. Students were required to generate accounts on the National Science Foundation (NSF) supercomputer, Cyverse, where all the software required for the activities is automatically installed and where the specific course workflows had been tested before the start of the course. We designed the four Jupyter Notebooks to be "computational recipes" and gave students access to the workflows throughout the 12 week course. The data exploration workflows walk students (in a tutorial-like manner) through basic data analysis strategies that focus on biochemical data, such as crystallographic structures, transcriptomics (RNA), proteomics (protein abundances) and metabolomics (metabolite abundances). Students were expected to explore and understand the content of all four of these workflows and their understanding was tested through individual, online multiple-choice assignments administered through Canvas.