BACHELOR OF APLLIED MATHEMATICS
Programme name: Applied Mathematics Code: 7460112
Mode of training: Full-time Training time: 4 years
Award: Bachelor Total number of credits: 141 credits
Programme type: Regular
Part 1
A BRIEF OVERVIEW OF THE PROGRAMME
1.1 Programme name: Applied Mathematics Programme
1.2 Programme Code: 7460112
1.3 Awarding institution: Can Tho University.
Address: Campus II, 3/2 Street, Xuan Khanh Ward, Ninh Kieu District, Can Tho City
Website: https://ctu.edu.vn/bmt.html
1.4 Award: Bachelor of Applied Mathematics
1.5 Total credits: 141
1.6 Mode of training: Full-time
1.7 Training time: 4 years (at most 8 years)
1.8 Applicants: People with high school diplomas or equivalent
1.9 Grade System: 4-grade
1.10 Graduation conditions:
- Accumulate enough modules and credits specified in the programme; cumulative common average of the whole course of 2.0 or higher (on 4-grade);
- Complete conditional courses. In addition, general average score of National Defense and Security Education courses must be 5.0 or higher (on a 10-grade);
- Not being examined for criminal liability, not being disciplined at the level of suspension of study in the last academic year.
Part 2
PROGRAMME OBJECTIVES AND EXPECTED LEARNING OUTCOMES
1. Programme objective
1.1 General programme objective
The Bachelor in Applied Mathematics (AMB) programme trains bachelors of science with in-depth knowledge of Applied Mathematics; capable of applying mathematical knowledge in the fields of science, technology, economy and society; capable of modeling real-world problems, building algorithms, processing and analyzing statistics; capable of working independently, creatively and competently in scientific research; have basic knowledge of political, social and legal sciences; Have skills in using foreign languages and using information technology.
1.2 Expected learning outcomes
The AMB graduates are expected to have ELOs as follows::
- ELO1: Train students with political qualities, professional ethics, consciously serving the people, having good health, meeting the requirements of building and protecting the fatherland.
- ELO2: Equip students with solid professional knowledge including basic knowledge and in-depth knowledge of Applied Mathematics, equipped with basic knowledge of foreign languages and informatics.
- ELO3: Train students to apply mathematical knowledge to solve practical problems through modeling, collecting, processing and analyzing data, building algorithms and performing calculations and solving forecasting problems to meet practical requirements.
-ELO4: Train students in independent work skills, collective work skills and skills adapted to the external work environment.
- ELO5: Training students capable of continuing their studies at postgraduate levels.
2. Learning outcomes of programme
Completing the AMB programme, learners master the knowledge, have skills and demonstrate the level of autonomy and personal responsibility as follows:
2.1 Knowledge
2.1.1 General knowledge
PLO1: Master the basics of Marxism- Leninism; The lines and policies of the Communist Party of Vietnam, Ho Chi Minh's ideology, physical education, national defense education meet the requirements of building and protecting the Fatherland.
PLO2: Master basic knowledge of general law, social sciences and humanities, natural sciences to meet the requirements of professional education knowledge acquisition.
PLO3: Understand and apply the basic knowledge of English or French equivalent to level 3/6 of Vietnam's foreign language capacity framework (B1 according to the European reference framework).
PLO4: Master the basics of computers, office software for learning and research.
2.1.2 Fundamental knowledge
PLO5: Master basic knowledge of Analysis such as Real Analysis, Functional Analysis, Complex Analysis, Ordinary Differential Equation, Measure Theory and Integration; basic knowledge of Algebra as Linear Algebra, General Algebra, Linear Programming, Discrete Mathematics; basic knowledge of informatics and mathematical modeling; as a foundation for learning, researching at a higher level and applying to the fields of applied mathematics.
PLO6: Master the basic knowledge of Probability theory and Statistics, in order to solve statistical problems in various fields such as Economics, Biology, Society and help learners to absorb in-depth knowledge of Statistics.
2.1.3Specialized knowledge
PLO7: Master in-depth knowledge of probability, random processes for studying statistical theory and financial mathematics.
PLO8: Master knowledge of statistics and databases to collect, process and analyze data collected for experimental research in the fields of agriculture, economy, society, medicine, and so on;
PLO9: Master the knowledge of building mathematical models as the foundation for solving forecasting problems for many different fields, drawing up decisions related to business strategies and policies in socio-economic development.
PLO10: Master knowledge of Numerical analysis, programming languages, computing bases in mathematical software (SPSS, R, Matlab, Maple,...) and the ability to program and solve practical problems, which have multi-parameter, big data and multi-dimension.
2.2 Skills
2.2.1 Hard skills
PLO11: Modeling the problems posed by reality in the fields of science and technology, economics, life ... From there, make forecasts for models.
PLO12: Collect secondary and primary data, analyze metrics, use basic and in-depth statistics for evaluation.
PLO13: Build algorithms, computer programs, use mathematical software (Matlab, Maple,..) and statistical software (SPSS, R, ...) to solve the problem of computing and processing statistics.
2.2.2 Soft skill
PLO14: Use foreign languages effectively in communication and scientific research.
PLO15: Proficient in applied informatics, application of information technology and modern means in research.
PLO16: Form teamwork skills to promote coordination and strengthen critical ability.
PLO17: Forming communication skills; presenting electronically, using different forms of electronic communication (email, website, online seminars) to adapt to the working environment outside of society.
2.3 Attitudes/ Self-control and individual responsibility
PLO18: Maintain confidence, enthusiasm, passion, adapt to change, work independently, be willing to work with others, consider and accept other perspectives. Always build a professional image at work.
PLO19: Adhere to the professional ethics of your profession, be aware of the position, the importance of your standards and ethical principles, have a proper attitude to your mistakes.
PLO20: Form a sense of lifelong learning, always update information in your specialized field to have attitudes as well as handle changes, update in a suitable and effective way.
3. Job position:
- Statistical analysts and processors at statistics departments, banks, insurance companies, data processing companies;
- Experts in charge of synthesis, statistics and scientific research in state agencies;
- Researchers at centers and research institutes in Mathematics;
- Lecturers at colleges and universities
4. Ability to study, improve level after graduation
- Meet the requirements of studying at postgraduate levels in the fields of Mathematics Statistics, Analysis, Methods of Teaching Mathematics and Economics Mathematics.
- Conducting in-depth specialized studies on probability and statistics
5. Refer to when developing a training program
- National: Applied Mathematics programme of Hue University, Vinh University, Saigon University, Academy of Science and Technology.
- International: Applied Mathematics programme of Yale University (USA), University of Colorado (USA), University of Auckland (New Zealand).
6. Programme
No. |
Code |
Course Title |
Credits |
Required |
Elective |
Lecture |
Lab |
Prerequisite |
Parallel course |
Semester |
General education knowledge |
||||||||||
1 |
QP006 |
National Defense Education – Security 1 (*) |
2 |
2 |
|
30 |
|
Arranged by major |
||
2 |
QP007 |
National Defense Education – Security 2 (*) |
2 |
2 |
|
30 |
|
Arranged by major |
||
3 |
QP008 |
National Defense Education – Security 3 (*) |
3 |
3 |
|
20 |
65 |
Arranged by major |
||
4 |
QP009 |
National Defense Education – Security 4 (*) |
1 |
1 |
|
10 |
10 |
Arranged by major |
||
5 |
TC100 |
Physical Education 1+2+3 (*) |
1+1+1 |
|
3 |
|
90 |
|
|
I,II,III |
6 |
XH023 |
Basic English Course 1 (*) |
4 |
|
10 credits for English or French |
60 |
|
|
|
I,II,III |
7 |
XH024 |
Basic English Course 2 (*) |
3 |
|
45 |
|
XH023 |
|
I,II,III |
|
8 |
XH025 |
Basic English Course 3 (*) |
3 |
|
45 |
|
XH024 |
|
I,II,III |
|
9 |
XH031 |
Level B2 English 1 (*) |
4 |
|
60 |
|
XH025 |
|
I,II,III |
|
10 |
XH032 |
Level B2 English 2 (*) |
3 |
|
45 |
|
XH031 |
|
I,II,III |
|
11 |
XH033 |
Level B2 English 3 (*) |
3 |
|
45 |
|
XH032 |
|
I,II,III |
|
12 |
FL001 |
Basic French Course 1 (*) |
4 |
|
60 |
|
|
|
I,II,III |
|
13 |
FL002 |
Basic French Course 2 (*) |
3 |
|
45 |
|
FL001 |
|
I,II,III |
|
14 |
FL003 |
Basic French Course 3 (*) |
3 |
|
45 |
|
FL002 |
|
I,II,III |
|
15 |
FL007 |
Intensive French 1 (*) |
4 |
|
60 |
|
FL003 |
|
I,II,III |
|
16 |
FL008 |
Intensive French 2 (*) |
3 |
|
45 |
|
FL007 |
|
I,II,III |
|
17 |
FL009 |
Intensive French 3 (*) |
3 |
|
45 |
|
FL008 |
|
I,II,III |
|
18 |
TN033 |
Basic informatics (*) |
1 |
1 |
|
15 |
|
|
|
I,II,III |
19 |
TN034 |
Basic informatics in lab (*) |
2 |
2 |
|
|
60 |
|
TN033 |
I,II,III |
20 |
ML014 |
Marxist – Leninist Philosophy |
3 |
3 |
|
30 |
|
|
|
I,II,III |
21 |
ML016 |
Marxist – Leninist Polotical Economy |
2 |
2 |
|
|
|
ML014 |
|
|
22 |
ML018 |
Scientific Socialism |
2 |
2 |
|
45 |
|
ML016 |
|
I,II,III |
23 |
ML019 |
History of the communist party of Vietnam |
2 |
2 |
|
30 |
|
ML018 |
|
I,II,III |
24 |
ML021 |
Ho Chi Minh’s thought |
2 |
2 |
|
45 |
|
ML019 |
|
I,II,III |
25 |
KL001 |
General law |
2 |
2 |
|
30 |
|
|
|
I,II,III |
26 |
ML007 |
General logic |
2 |
|
2 |
30 |
|
|
|
I,II,III |
27 |
XH028 |
Overview of Sociology |
2 |
|
30 |
|
|
|
I,II,III |
|
28 |
XH011 |
Basic Vietnamese culture |
2 |
|
30 |
|
|
|
I,II,III |
|
29 |
XH012 |
Vietnamese in use |
2 |
|
30 |
|
|
|
I,II,III |
|
30 |
XH014 |
General management documents and archives |
2 |
|
30 |
|
|
|
I,II,III |
|
31 |
KN001 |
Transferable skills |
2 |
|
20 |
20 |
|
|
I,II,III |
|
32 |
KN002 |
Entrepreneurship and innovation |
2 |
|
20 |
20 |
|
|
I,II,III |
|
33 |
TN195 |
Basics of C programming |
3 |
3 |
|
30 |
30 |
TN033 |
|
I,II,III |
34 |
TN100 |
Research Mehthodology |
2 |
2 |
|
30 |
|
|
|
I,II,III |
35 |
SP304 |
Linear programming |
2 |
2 |
|
30 |
|
|
|
I,II,III |
36 |
TN347 |
Discrete Mathematics |
3 |
3 |
|
45 |
|
|
|
I,II,III |
Total: 49 credits (Required: 34 credits; Elective: 15 credits) |
||||||||||
Basic professional knowledge |
||||||||||
37 |
TN188 |
Analysis 1 |
3 |
3 |
|
45 |
|
|
|
I,II |
38 |
TN156 |
Analysis 2 |
3 |
3 |
|
45 |
|
TN188 |
|
I,II |
39 |
TN157 |
Analysis 3 |
3 |
3 |
|
45 |
|
TN156 |
|
I,II |
40 |
TN158 |
Linear algebra and analytic geometry 1 |
2 |
2 |
|
30 |
|
|
|
I,II |
41 |
TN220 |
Linear algebra and analytic geometry 2 |
3 |
3 |
|
45 |
|
TN158 |
|
I,II |
42 |
TN160 |
General algebra |
3 |
3 |
|
45 |
|
TN220 |
|
I,II |
43 |
TN440 |
Probability and statistic |
4 |
4 |
|
60 |
|
|
|
I,II |
44 |
TN162 |
Ordinary differential equations |
3 |
3 |
|
45 |
|
TN156 |
|
I,II |
45 |
TN189 |
Complex analysis |
3 |
3 |
|
45 |
|
TN156 |
|
I,II |
46 |
TN344 |
Numerical analysis |
3 |
3 |
|
45 |
|
TN156 |
|
I,II |
47 |
TN464 |
Real analysis |
3 |
3 |
|
45 |
|
TN156 |
|
I,II |
48 |
TN191 |
Functional analysis |
3 |
3 |
|
45 |
|
|
|
I,II |
49 |
TN164 |
Measure and integral theory |
3 |
3 |
|
45 |
|
TN157 |
|
I,II |
50 |
TN169 |
English for statistical mathematics |
2 |
|
2 |
30 |
|
XH024 |
|
I,II |
51 |
XH019 |
French for Science and Technology |
2 |
|
30 |
|
XH006 |
|
I,II |
|
Total: 41 credits (Requỉed: 39 credits; Elective: 2 credits) |
||||||||||
Professional knowledge |
||||||||||
52 |
TN372 |
Mathematical models |
3 |
3 |
|
45 |
|
TN156 |
|
I,II |
53 |
TN368 |
Advanced statistics |
3 |
3 |
|
45 |
|
TN440 |
|
I,II |
54 |
TN346 |
Analysis of statistical data |
3 |
3 |
|
45 |
|
TN440 |
|
I,II |
55 |
TN426 |
Applications of informatics in mathematics |
3 |
3 |
|
30 |
30 |
TN440 |
|
I,II |
56 |
TN355 |
Bayes statistics |
3 |
3 |
|
45 |
|
TN440 |
|
I,II |
57 |
TN441 |
Multi-dimensional statistics |
3 |
3 |
|
30 |
30 |
TN440 |
|
I,II |
58 |
TN170 |
Field trip |
1 |
1 |
|
|
30 |
|
|
I,II |
59 |
TN370 |
Advanced probability |
3 |
3 |
|
45 |
|
TN440 |
|
I,II |
60 |
TN442 |
Random process |
3 |
3 |
|
45 |
|
TN440 |
|
I,II |
61 |
TN472 |
Applied statistics |
3 |
3 |
|
30 |
30 |
TN440 |
|
I,II |
62 |
TN358 |
Time series analysis |
2 |
2 |
|
30 |
|
TN440 |
|
I,II |
63 |
TN443 |
Socio-economic statistics |
3 |
|
11 |
30 |
30 |
TN440 |
|
I,II |
64 |
TN462 |
Seminar in Applied mathematics |
2 |
|
30 |
|
TN440 |
|
I,II |
|
65 |
TN467 |
Statistics classification and discriminant |
3 |
|
45 |
|
TN440 |
|
I,II |
|
66 |
TN369 |
Statistics forecast |
3 |
|
45 |
|
TN440 |
|
I,II |
|
67 |
TN251 |
Limit theorems of probaility theory |
3 |
|
45 |
|
TN440 |
|
I,II |
|
68 |
TN255 |
Seminars on probability theory |
2 |
|
30 |
|
TN440 |
|
I,II |
|
69 |
CT177 |
Data structures |
3 |
|
30 |
30 |
|
|
I,II |
|
70 |
TN470 |
Partial differential equations and apllications |
2 |
|
30 |
|
TN162 |
|
I,II |
|
71 |
TN201 |
Image processing techniques |
2 |
|
30 |
|
|
|
I,II |
|
72 |
TN360 |
Graduation thesis |
10 |
|
10 |
|
300 |
≥ 105 credits |
|
I,II |
73 |
TN253 |
Graduation assay |
4 |
|
|
120 |
≥ 105 credits |
|
I,II |
|
74 |
TN254 |
Introduction to Financial mathematics |
3 |
|
45 |
|
TN442 |
|
I,II |
|
75 |
KT320 |
Economical Mathematics model |
3 |
|
45 |
|
TN156 |
|
I,II |
|
76 |
TN352 |
Theory of nonlinear programming |
2 |
|
30 |
|
SP304 |
|
I,II |
|
77 |
TN354 |
Algorithm of optimization |
2 |
|
30 |
|
SP304 |
|
I,II |
|
78 |
SG245 |
Convex analysis |
2 |
|
30 |
|
TN156 |
|
I,II |
|
79 |
SP328 |
Set-valued analysis |
2 |
|
30 |
|
TN157 |
|
I,II |
|
80 |
TN204 |
Information system design |
3 |
|
30 |
30 |
|
|
I,II |
|
81 |
TN469 |
Advanced numerical methods |
3 |
|
45 |
|
TN344 |
|
I,II |
|
82 |
TN278 |
Dynamical systems |
3 |
|
45 |
|
TN156 |
|
I,II |
|
Total: 51 credits (Required: 30 credits; Elective: 21 credits) |
||||||||||
Total: 141 credits (Required: 103 credits; Elective: 38 credits) |