Program name: Applied Mathematics
Education level: Master
Specialization: Applied Mathematics
Specialized code: 60.46.01.12
Training orientation: Research
Graduation: Master of Science
TRAINING OBJECTIVES:
General objective:
The goal of the program is to train a master in Applied Mathematics with a solid knowledge of theory, proficiency in practice to be able to design and implement algorithms and scientific calculations, as well as apply for solving scientific and technical problems arising from reality; have the ability to work independently, creatively and with a systems thinking approach; be able to adapt to changes in computational science and technology; capable of self-researching and developing theoretical problems in the field of Mathematics, Applied Mathematics.
Detail goal:
After completing the training course, the Master in Applied Mathematics will have:
- Ability to grasp in-depth knowledge of Applied Mathematics and know how to apply it to make math applications;
- Knowledge of scientific computing programming;
- Ability to independently research and work in a multidisciplinary research team;
- Ability to research and express mathematical problems and apply them in practice.
Admission and enrollment:
About the entrance exam:
Candidates must take the following subjects:
- Advanced math
- English
- Computational Algebra
About diplomas:
Contestants must be one of the following:
CODE OF STUDENT GROUP CODE
| College majors | University program* | |||
| 5 years – 155 credits | 4.5 years – 141 credits | 4 years – 128 credits | ||
| Right majors | Mathematics, Mathematics and Informatics, Information Technology | A1 | A2 | A3 |
| Near majors | Electronics and Telecommunications, Mechanics and Informatics, Mechatronics | B1 | B2 | B3 |
| * Must satisfy both time requirements and number of credits |
Other subjects will be considered and decided by the School of Applied Mathematics and Informatics.
About seniority:
- Persons with a good diploma or higher may take the exam right after graduating from a regular university;
- The remaining cases must have at least one year of working experience in the field related to Mathematics, Mathematics – Information and Information Technology.
Complementary:
- Candidates who belong to subjects A1, A2 and A3 do not have to take additional knowledge;
- Candidates who belong to subjects B1, B2, B3 must take 9 additional credits.
Exemptions:
- Candidates in subjects A1, B1 are exempted from 21 credits;
- Candidates in subjects A2, B2 are exempted from 12 credits;
- The remaining subjects are not exempt,
Training time:
- Credit-based training course.
- The duration of the training course designed for subjects A1, B1 is 1 year (2 main semesters)
- The duration of the training course designed for subjects A2, B2 is 1.5 years (3 main semesters)
- The duration of the training course designed for the remaining subjects is 2 years (4 main semesters).
NUMBER OF CREDIT ENTIRE COURSE: 60 CREDITS
OVERALL STRUCTURE OF THE TRAINING PROGRAM:
| Content | Number of credits | |
| Part 1. General knowledge (Philosophy, English) | 9 | |
| Part 2. Basic and specialized knowledge | Required knowledge base | 6 |
| Optional knowledge base | 6 | |
| Required specialized knowledge | 15 | |
| Elective specialized knowledge (*) | 9 | |
| Part 3. Thesis | 15 | |
| Total credits | 60 |
LIST OF SPECIALIZED COURSES:
| Content | Code | Course name | Credits | Volume |
| BASIC COURSE | ||||
| General knowledge | SS6011 | Philosophy | 3 | 3(3−1−0−6) |
| FL6010 | English | 6 | 6(3-6-0-12) | |
| Core courses | MI5030 | Optimal control | 3 | 3(3−1−0−6) |
| MI5040 | Random models and applications | 3 | 3(3−1−0−6) | |
| Elective courses | MI5080 | Modern numerical methods | 3 | 3(3−1−0−6) |
| MI5070 | Digital signal processing and applications | 3 | 3(3−1−0−6) | |
| MI5060 | Algorithmic logic | 3 | 3(3−1−0−6) | |
| MI4150 | Identity Theory | 3 | 3(3−1−0−6) | |
| SPECIALIZED COURSE | ||||
| Required majors | MI6010 | Applied Algebra | 3 | 3(2−2−0−6) |
| MI6020 | Operators | 3 | 3(2−2−0−6) | |
| MI6030 | Optimization Theory | 3 | 3(2−2−0−6) | |
| MI6040 | Multidimensional Statistics | 3 | 3(2−2−0−6) | |
| MI6050 | Advanced Algorithms and Parallel Computing | 3 | 3(2−2−0−6) | |
| Elective majors | MI6060 | Financial Math Model | 3 | 3(2−2−0−6) |
| MI6070 | Mathematical Physics Equations in Technology | 3 | 3(2−2−0−6) | |
| MI6080 | Display Engineering | 3 | 3(2−2−0−6) | |
| MI6090 | Multi-objective Optimization | 3 | 3(2−2−0−6) | |
| MI6091 | Differential Equations and Applications | 3 | 3(2−2−0−6) | |
| MI6100 | Digital Image Processing | 3 | 3(2−2−0−6) | |
| MI6110 | Combination Optimization | 3 | 3(2−2−0−6) | |
| MI6122 | Propulsion Systems and Applications | 3 | 3(2−2−0−6) | |
| MI6130 | Modern Numerical Analysis | 3 | 3(2−2−0−6) | |
| MI6140 | Data Mining | 3 | 3(2−2−0−6) | |
| MI6150 | Geographic Information System (GIS) | 3 | 3(2−2−0−6) | |
| MI6300 | Modeling Complex Systems | 3 | 3(2−2−0−6) | |
| MI6310 | Convolutional Integral Transforms and Applications | 3 | 3(2−2−0−6) | |
| Essay | LV6001 | Graduation Essay | 15 | 15(0−2−30−50) |
LIST OF ADDITIONAL COURSES:
| Content | Code | Course name | Credits | Volume |
| Additional knowledge | MI3020 | Functional Calculus | 3 | 3(2−2−0−6) |
| MI3040 | Numerical analysis | 3 | 3(2−2−0−6) | |
| MI3030 | Probability statistics | 3 | 3(2−2−0−6) |
Subjects to additional study:
| No. | Subject | Additional credit number | Specific additional courses * | Note |
| 1 | Subjects of group A | 0 | No additional study required | |
| 2 | Subjects of group B | 9 | MI3020, MI3030, MI3040 |
LIST OF COURSES FOR EXEMPTION:
| No. | Subject | Code | Khối lượng | Note |
| 1 | Optimal control | MI5030 | 3(3−1−0−6) | Obligatory |
| 2 | Random Models and Applications | MI5040 | 3(3−1−0−6) | Obligatory |
| 3 | Modern Numerical Method | MI5080 | 3(3−1−0−6) | Optional |
| 4 | Digital Signal Processing and Applications | MI5070 | 3(3−1−0−6) | Optional |
| 5 | Algorithmic Logic | MI5060 | 3(3−1−0−6) | Optional |
| 6 | Identity Theory | MI4150 | 3(3−1−0−6) | Optional |
| 7 | Financial Math Model | MI6060 | 3(2−2−0−6) | Optional |
| 8 | Mathematical Physics Equations in Technology | MI6070 | 3(2−2−0−6) | Optional |
| 9 | Display Engineering | MI6080 | 3(2−2−0−6) | Optional |
| 10 | Multi-objective Optimization | MI6090 | 3(2−2−0−6) | Optional |
| 11 | Differential Equations and Applications | MI6091 | 3(2−2−0−6) | Optional |
| 12 | Digital Image Processing | MI6100 | 3(2−2−0−6) | Optional |
| 13 | Combination Optimization | MI6110 | 3(2−2−0−6) | Optional |
| 14 | Propulsion Systems and Applications | MI6121 | 3(2−2−0−6) | Optional |
| 15 | Modern Numerical Analysis | MI6130 | 3(2−2−0−6) | Optional |
| 16 | Data Mining | MI6140 | 3(2−2−0−6) | Optional |
| 17 | Geographic Information System (GIS) | MI6150 | 3(2−2−0−6) | Optional |
| 18 | Modeling Complex Systems | MI6300 | 3(2−2−0−6) | Optional |
| 19 | Convolutional Integral Transforms and Applications | MI6310 | 3(2−2−0−6) | Optional |
List of subjects eligible for exemption from the course:
| No. | Subject | Exempt credit number | Specific exempt courses | Note |
| 1 | A1, B1 | 21 | Course no. 1, no. 2; 6 credits from course no. 3 to no. 6 and 9 credits from course no. 7 to no. 19 | |
| 2 | A2, B2 | 12 | Elective course no. 1, no. 2 and no. 6 credits from course no. 3 to no. 6 | |
| 3 | Other objects | 0 | Not exempt |