Intellectual Data Analysis
The course introduces students to the full cycle of creating machine learning models for research purposes. The main stages of the semester: analysis of an applied problem and formulation of the problem, building a model, performing a computational experiment, error analysis. The result of the work of a group of students is a library of models for a fixed applied problem or class of problems.
Evaluated: the student’s qualifications and his personal contribution to the project.