Although there are expected variations in student backgrounds, interests, motivations, expectations, and learning styles, the below prerequisites serve as a guideline of the foundational knowledge and experience that will be helpful for the successful completion of the Data Science and Predictive Analytics course.
|BS Degree or Equivalent||Quantitative methods/analytics training and coding skills||The DSPA graduate-level course requires a minimum level of quantitative skills|
|Quantitative Training||Undergraduate calculus, linear algebra and introduction to probability and statistics||These represent entry level skills required for the DSP course|
|Coding Experience||Exposure to software development or programming on the job or in the classroom||Most DS practitioners need substantial experience with Java, C/C++, HTML5, Python, PHP, SQL/DB|
|Motivation||Significant interest and motivation to pursue quantitative data analytic applications||Dedication for prolonged and sustained immersion into hands-on and methodological research|