• major techniques of knowledge and data engineering;
• methods of knowledge extraction;
• linguistic means of knowledge and data description.

• Machine Learning;
• Methods of Natural Language Processing.

Data mining techniques. Theoretical aspects of knowledge extraction. Psychological aspect. Linguistic aspect. Epistemological aspect of knowledge extraction. Structuring methods. Evolution of knowledge acquisition systems. Methods of knowledge acquisition. Domain. Domain description language. Semiotic model of domain. Strategies of knowledge acquisition. Methods of knowledge classification and systematization. Theoretical aspects of knowledge structuring. Hierarchical approach. Traditional structuring methodology. Object-structural approach. Methods of knowledge compilation. Communicative methods. Passive methods. Active individual methods. Active batch methods. Textual methods. Methods of structuring. Latent knowledge structure. Semantic space and graduation. Identification of "hidden" knowledge structures . Repertory grid technique. Construct detection method. Repertory grid analysis.

• Литвин В. В. Методи та засоби інженерії даних та знань / В. В. Литвин // навчальний посібник з грифом МОНУ. – Львів : «Магнолія-2006», 2012. – 241 с.
• Глибовець М.М., Олецький О.В. Штучний інтелект. – К.: КМ Академія, 2002. –
• Представление и использование знания / под ред. Х.Уэно, М.Исидзука. - М.: Мир, 1989.
• Гаврилова Т. А. Базы знаний интеллектуальных систем / Т.А.Гаврилова, В.Ф.Хорошевский. –СПб: Питер, 2001. – 384с.
• Рассел С. Искусственный интеллект / С.Рассел, П.Норвиг. – М.,С.-П.,К.: Вильямс, 2006. – 1408с.

• Current control (40%): written reports on laboratory work, essay, oral examination;
• Final control (60% of exam): in written, verbally.