Master of Mathematics and Informatics Training Program (Applied from school year 2018-2019)

Program Name:      Mathematics and Informatics

Training qualifications: Master of Science

Major: Mathematics and Informatics

Training orientation: Research

Diploma:        Master of Science

1. Training objectives 

1.1 General objective

  • To create high-quality human resources in the field of Mathematics and Informatics to meet the demands of agencies, organizations, enterprises… to serve the developing requirements of economy, society, security and national defense, international integration;
  • To train masters with solid knowledge of applied mathematics majors, mathematical foundations for informatics, inherit and promote at a higher level than university-level competencies in computer science majors: understanding and mastering the foundations required mathematics, advanced specialized knowledge of a number of applied models of mathematics and informatics, strong in theory and good practical skills in algorithm implementation and scientific computation, access to scientific research activities;
  • To train math-informatics experts with high professional qualifications, research ability and creative ability, apply knowledge to solve theoretical or practical problems, be able to teach at university level, adapt and effectively meet the requirements of society in the process of globalization or continue to study and research at a higher level.

1.2 Specific objective

At the end of the program, students major in research-oriented Mathematics and Informatics have the following competencies:

  1. Having solid foundational and professional knowledge, capable of participating in solving related problems in the field of applied mathematics or computer science;
  2. Having the ability to teach Maths – Informatics and good expression of applied Maths – Informatics problems;
  3. Having professional skills and personal qualities necessary for career success: scientific and professional working methods, good systems thinking and analytical thinking; being able to integrate with an international environment;
  4. Having social skills necessary to work effectively in a multidisciplinary team and integrate with an international environment;
  5. Having the ability to self-train, self-update knowledge and self-doing scientific research; ability to explore practical problems, apply knowledge and creative scientific and technical achievements to solve real-life problems.

2. Learning outcomes

Graduates of the Mathematics and Informatics program have the following professional knowledge, skills and competencies:

 Learning OutcomesCompetency Level (*)
1Apply professional knowledge to be able to work effectively in the field of application of Mathematics and Informatics to meet the requirements of modern society5
1.1Have the ability to effectively apply basic knowledge of mathematics, computer science and basic science, know how to explore, process and evaluate the value of scientific information.5
1.2Have the ability to well apply core professional knowledge, adapt to different jobs in the field of computer science (describe, calculate and simulate systems, processes and build software; research, analyze, develop solutions, design processes…).4
1.3Have the ability to teach and research mathematics and informatics in universities and research institutes; or continue to study as a doctoral student majoring in mathematics – informatics.4
1.4Have the ability to apply knowledge of mathematics in analyzing and solving a specific theoretical or practical problem.4
2Professional skills and personal qualities required for career success5
2.1Have skills in idea-discovery, argument, analysis, synthesis, questioning and problem-solving in theory or in practice.6
2.2Have systematic, synthetic, logical and critical thinking.5
2.3Creative, persistent and serious, with ethics and professional responsibility.5
2.4Have skills to research, experiment and explore knowledge, self-training skills and quickly adapt to the development of science and technology and to real life.5
2.5Have a good understanding of contemporary issues and a sense of lifelong learning.5
3Social skills needed to work effectively in a multidisciplinary, multicultural and multinational working environment5
3.1Have the ability to work independently and have organizational skills and teamwork skills.5
3.2Communicate effectively through writing, presentation, discussion, negotiation, mastering of situations, proficient and effective use of modern information processing tools and means.4
3.3Have good English skills, English level equivalent to B1 level.4
4Ability to analyze, form ideas, participate in the design, implementation and administration of mathematical and informatical models to solve problems of organization and society4
4.1.Have the ability to detect problems, synthesize, analyze and exploit scientific, social and economic information domestically and internationally.4
4.2.Understand the environment and operations of domestic and international organizations, financial institutions, and laws.4
4.3Have the ability to discover ideas, build and develop projects, systems as well as implement applied math – informatics solutions and products according to the requirements of economic and social organizations.4

(*) Notes on Bloom’s capacity scale:

1Have the ability to remember
2Have the ability to understand
3Have the ability to apply
4Have the ability to analyze
5Have the ability to synthesize
6Have the ability to evaluate

3. Whole courses mass of knowledge 

 Group of knowledgeMaster of science
1General Knowledge:-    Philosophy-    English (not counting the number of credits, requiring students to get the standard output)3 credits
2Foundation major courses, advanced major courses (required)15 credits
3Research-oriented or apply-oriented major courses (optional)12 credits
4Graduation thesis15 credits
 Total:45 credits


4. Admission and enrollment

4.1 About the entrance exam

Candidates must take the entrance exam with 3 following subjects:

  • Advanced Maths
  • English
  • Computational Algebra

4.2 About the candidates

Candidates must have graduated from university in one of the following groups:

  Graduated major Graduated university   
  Graduated from Hanoi University of Science and Technology (*)Other universities,   
Right majorMathematics, Mathematics – Informatics, Information TechnologyA1A2   
Near majorElectronics and Telecommunications, Mecha-informatics, MechatronicsB1B2   
  (*) and other universities that HUST recognizes credits in the university curriculum    
  • Candidates who are exempted from courses and those who have to take additional courses will be considered and decided by the School of Applied Mathematics and Informatics.
  • Other candidates are decided by the School of Applied Mathematics and Informatics.
  • For those who register for application-oriented learning: no seniority is required.

5. Training duration

  • The training program follows the credits-based system.
  • The standard designed training program is 1.5 years (3 main semesters).

6. Exemption

List of students considered for exemption will be considered by the council on a case-by-case basis for the students in group A1 having the engineering degree from University of Science and Technology (*) according to the list of courses of the practical program but not more than 15 credits.

7. Training process and graduation conditions

The training process is organized according to the credits-based system, in accordance with the Regulations on organization and management of postgraduate training of Hanoi University of Science and Technology, promulgated under Decision No ………./QĐ-ĐHBK-SĐH on …… month ….. year …………. of the Principal of Hanoi University of Science and Technology.

8. Grading scale

Letter grading scale (A, B, C, D, F) and corresponding 4-point scale are used to assess official learning outcomes. A 10-point scale is used for the component scores of the module.

 10-point scale (component)4-point scale    
Letter grading Score     
Not PassedBelow 4.0F0   

* Graduation Thesis Only: A grade of C or higher is considered a pass.

9. Curriculum

Group of knowledgeCourse codeCourse nameCreditsVolume
General knowledgeSS6010Philosophy3 
FL6010English Self-study 
Required knowledge (15 credits) MI5032 Optimal Control22(2-1-0- 4)
MI5042Random Models and Applications22(2-1-0-4) 
MI5022Computer Security22(2-1-0-4) 
MI6230Graph Theory33(3-1- 0-6) 
MI5060Artificial Intelligence22(2-1-0-4) 
MI5050Modeling and Simulation22(2-1-0-4) 
MI5142Advanced Database22(2-1- 0-4) 
Elective knowledge (12 credits) divided into 2 modules Applied Mathematics Module   
MI6132Advanced Numerical Methods33(2-2-0-6) 
MI6010 Applied Algebra33(2-2- 0-6) 
MI4150 Identification Theory33(3-1-0-6) 
MI6060Financial Math Modeling33(2-2-0-6) 
MI6090Multi-Objective Optimization33(2-2- 0-6) 
MI6040 Multidimensional Statistics33(2-2-0-6) 
MI6050Advanced Algorithms and Parallel Computing33(2-2-0-6) 
MI6310Integral Transform of Convolution Type and Applications33(2-2-0-6) 
MI6351 Seminar I33(1-2-2-6) 
MI6352 Seminar II33(1-2-2-6) 
Mathematical foundations for Informatics Module    
MI6100Image Processing33(2-2-0-6 ) 
MI6150Geographic Information Systems (GIS)33(2-2-0-6) 
MI6140Data Mining33(2-2-0-6) 
MI4010 Automata Theory and Formal Languages​​33( 3-1-0-6) 
MI6050Advanced Algorithms and Parallel Computing33(2-2-0-6) 
MI4312Mathematical foundations of fuzzy systems33(2-2-0-6) 
MI6070Machine Learning33(2-2-0-6) 
MI6080Internet of Things33(2-2-0-6) 
MI6351 Seminar I33(1-2-2-6) 
MI6352 Seminar II33 (1-2-2-6) 
ThesisLV6001 Graduation Thesis1515(0-0-30-50)

Students A1: Engineering graduates according to the 2009 training model are considered exempt from 15 credits in elective knowledge group; Engineering graduates according to the training model in 2017 are considered exempted from no more than 15 credits in the elective knowledge group.

Supplemental courses Catalog

Students A2, B1, and B2 must take supplementary (preparatory semester) from 9 to 15 credits of courses in the following category. Specific students and additional courses are decided by the School of Applied Mathematics and Informatics.

ContentsCoursesModule NameCreditsVolume
Additional Major courses (9 – 15 credits) MI3020Functional Calculus33(3−1−0−6)
MI3040Numerical Analysis33(3−1−0−6 ) 
MI3060Data Structures and Algorithms33(3−1−0−6) 
MI4090Programming Techniques33(3−1−0−6) 
MI3090Database33(3−1−0− 6) 
MI3030Probability and Statistics33(3−1−0−6) 

Source: ap-dung-tu-nam-hoc-2018-2019/