Learning about technical topics is a continuous process and is often difficult for both new students, as well as experienced researchers. The difficulty comes, in part, from the lack of pre-requisite knowledge. In this paper, we address the problem of determining prerequisites of a given technical concept as input. Previous work on this problem did not focus on retrieving ``crucial'' pre-requisites.  In contrast, we make use of a \emph{technical knowledge-base}, a structured source that contains \emph{explicit relationships} between concepts to retrieve crucial prerequisites. We also show that such embeddings can be used to improve the recall by accurately determining the most ``similiar" concept and returning its pre-requisites, taking advantage of the fact the ``similar'' concepts share common pre-requisites. Our user-evaluation shows that the pre-requisites generated by our method are accurate and effective.