EDUCATIONAL – PROFESSINAL PROGRAM
«DATA ANALYTICS»
Second (master’s) level of higher education
in the specialty 113 Applied Mathematics
fields of knowledge 11 Mathematics and Statistics
Qualification: Master of Applied Mathematics
| The code | Components of the Educational Program (disciplines, projects/works, practice, qualification work) | Number of Credits ECTS | Form of final control |
|---|---|---|---|
| 1 | 2 | 3 | 4 |
|
MANDATORY EDUCATIONAL COMPONENTS |
|||
| General studying | |||
| GS1 | Innovation Entrepreneurship and Startup Project Management | 3 | Test |
| GS2 | Foreign Language for Professional Purposes | 3 | Test |
| GS3 | Intellectual Property | 3 | Test |
| Specialized (Professional) Studying | |||
| SS1 | Mathematical Methods of Machine Learning 1 | 5 | Test |
| SS1 | Ill-posed Problems of Data Processing | 5 | Exam |
| SS1 | Mathematical Methods of Machine Learning 2 | 4 | Exam |
| SS1 | Nonlinear Processes and Models | 4 | Exam |
| SS1 | Metaheuristic Optimization Methods | 4 | Exam |
| SS1 | Fundamentals of Scientific Research | 5 | Exam |
| SS1 | Pre-diploma Practice | 11 | Test |
| SS1 | Certification | 19 | Test |
| Total Mandatory Components | 66 | ||
| ELECTIVE EDUCATIONAL COMPONENTS | |||
| Profiling studying | |||
| Profiling Discipline Package 1 “Big Data Intelligent Analysis” | |||
| PS1.1 | Methods and Technologies for Working with Big Data | 5 | Exam |
| PS1.2 | Graph Data Analysis | 6 | Exam |
| PS1.3 | Machine Learning Engineering | 5 | Exam |
| Profiling Discipline Package 2 “Big Data Intelligent Analysis” | |||
| PS2.1 | Analysis and Synthesis of Natural Language Information | 5 | Exam |
| PS2.2 | Signal Processing Methods | 6 | Exam |
| PS2.3 | Image Processing Methods | 5 | Exam |
| Free Choice Disciplines of Profiling Preparation (according to the list) | |||
| FCD1 | Profiling Preparation Disciplines 1 | 4 | Exam |
| FCD2 | Profiling Preparation Disciplines 2 | 4 | Exam |
| Total Elective Components | 24 | ||
| TOTAL VOLUME OF THE EDUCATIONAL PROGRAM | 90 | ||