Typical difficulties in learning probabilistic subjects are concerned with big data, complicated formulas and inconvenient figures in statistical analyses. The present research considers the usage of innovative teaching methods (e.g. electronic summary of lectures, presentations of lecture courses, task solution templates, electronic training materials for seminar studies) supported by the CAS (computer algebra system) Mathematica, as suggested by the authors for several topics of the course 'Supplementary Chapters of Probability Theory'. These methods help to solve tasks requiring routine calculation and simplify the ability to find analytical and graphical dependencies in the tasks under consideration. Visualisation possibilities built in the CAS contribute to students' comprehension of new theoretical material and complicated probabilistic notions. The article contains examples of CAS-performed tasks including the calculation and visualisation of the notions of the conditional probability density function, conditional expectation, order statistics and running maximum. The purpose of the suggested CAS-based materials is to solve a whole class of tasks of similar types; it is possible to obtain new results by varying the input data without spending much time elaborating the solution method. The methods using innovative teaching materials yield advantages to both students and teachers. These methods simplify and individualise the process of education, shorten the time necessary for students' independent work and motivate students to achieve the results. Moreover,