Data Mining (DM) is one of the most offered courses in data analytics education. However, the design and delivery of DM courses present a number of challenges and issues that stem from the DM's interdisciplinary nature and the industry expectations to generate a broader range of skills from the analytics programs. In this research, we identified and compared frequencies of the contents and skills of DM course syllabi in various data analytics programs. We also identified and systemized DM contents and skills in the analytics job market and compared them with the contents and skills from DM syllabi. Based on these analyses and comparisons, we developed four different templates of the DM contents and skills for a DM course at various levels of the analytics education that include: specialized graduate analytics program (MS), general graduate program (MBA), specialized undergraduate analytics program (BS), and general undergraduate program (BSBA). These templates may be specifically useful for educators to design new or improve existing DM courses in data analytics curricula.