Hacking the future

Finding a suitable job, course of study or apprenticeship is an important choice for pupils after finishing school in order to ensure a good, satisfactorily life. This choice is currently decided by questionnaires, personal talks with professionals or merely by the grades the pupils got at school. In our project we followed another approach by evaluating the browser history of the pupil in order to find out their fields of interest. The browser history is especially interesting as it also contains the pupils private interests that could be integrated in their prospective life. We used a two-step algorithm that links the browser history to attribute words. In the next step the probability of those attributes within the browser history results in a variety of possible jobs suggestions that apply to these attributes. As a result, we show the most likely job interests with a percentage value. My role was to feed and sort the data for the ML and then to run and evaluate the ML algorithms.