Application of intelligent expert systems for structuring and automation of laboratory activities in the educational process has been analysed. It is shown that combination of teaching materials with cross-references and transitions by the means of expert systems allows educators to make optimal decisions on time, set priorities and prepare more effective laboratory classes. The implementation of expert systems for classification sections of academic disciplines in both engineering and technical sciences and humanities has been discussed. An algorithm for making decisions by an expert system, where the main emphasis is given to laboratory tasks and work with laboratory equipment, is proposed. It is shown how to develop a new expert system which can help university educators prepare remote laboratory work, and also to use of virtual simulators or effective practical training. The proposed expert systems can be used for classifying thematic sections of a wide range of disciplines, including natural sciences, engineering, and humanities. They can be used for preparing new courses and training new educators in different areas. Thus expert systems are described as high-scale software units without restrictions on the depth of the question tree and the number of logical branches of the classifier.