Training Objectives
1 General objective:
Training Information Technology (IT)/Artificial Intelligence (AI) specialization engineers with personality and capacity to meet the needs of society, mastering professional knowledge and practice, being able to organize, implement and promote creativity in jobs related to the trained specialties as well as pursue further education and research.
The training program aims to:
- To equip students with fundamental knowledge of mathematics and the IT industry together with fundamental and specialized methodologies, technologies related to AI and Data science;
- Train students the necessary virtues and skills in the professional working environment, know how to apply specialized knowledge of AI specialization into practical work;
- Provide students with a strong foundation in foreign languages, science, culture and society, promoting their autonomy and creativity in study, work and life.
2 Specific objectives:
Graduates of the IT training program/AI specialization must demonstrate the following:
PO1. Have basic knowledge of social sciences, politics and law, security and defense, foundational knowledge of the IT industry & in-depth knowledge of the specialized training: techniques, methods, technologies, in-depth application areas; development trends in the world; at the same time understand the overall market, context, functions and tasks of the professions in the specialized training;
PO2. Be able to work as a full member of a professional team in the field of training: participate in designing, select techniques and technologies in line with development trends, solving technical problems; understand technology trends and user requirements; can do the complete solution development plan; performance management and change management in his or her part of the job; understand state policies in specialized fields;
PO3. Master professional skills and soft skills of the 21st century citizens (thinking skills, work skills, skills in using work tools, and life skills in a global society);
PO4. Can use English well in study and work and a second foreign language in normal communication;
PO5. Honesty, high discipline in study and work, know how to work effectively in groups; know how to behave culturally at work and in society; dynamic, creative and willing to learn constantly. Demonstrate professional attitude and behavior with the ability to conceive of ideas, design, implement and operate systems in the context of corporation and society.
Career prospects
Graduates of the AI specialization have diverse job opportunities with a number of typical positions such as:
- AI application development engineer;
- Automation system operation and robot development engineer;
- Data architect;
- AI lecturers at universities;
- Researchers in the Artificial Intelligence field;
- Experts in consulting solutions to AI application in production and business;
- Pursue further education after graduating;
- Start-up.
Program Learning Outcomes
| 1 | GENERAL KNOWLEDGE AND SKILLS |
| PLO1 | Have basic knowledge of social sciences, politics and law, security and defense, contributing to the formation of worldview and scientific methodology |
| PLO2 | Have an entrepreneurial, creative, critical, and problem-solving mindset; being capable of time management, working with specific plans and clear objectives |
| PLO3 | Communicate and work in groups effectively in academic and practical environments; Perform skills of presentation, negotiation; Receive and handle requests effectively |
| PLO4 | Be able to use English well to communicate and study and basically communicate in Japanese |
| 2 | ETHICAL QUALITIES AND ATTITUDES |
| PLO5 | Be mentally and physically strong, be capable of expressing national identity and integrating confidently into the world, be responsible for society and devoted to communities |
| PLO6 | Behave in a professional way, being responsible and having professional integrity at work, understand the conformity to labor discipline in accordance with the provisions of the Law and agencies in force |
| PLO7 | Have a spirit of self-study and lifelong learning, be capable of adapting to the constant change of technology and society |
| 3 | MAJOR KNOWLEDGE AND SKILLS |
| PLO8 | Be able to explain and apply essential knowledge of algorithms, programming and specialized mathematics related to the field of information technology |
| PLO9 | Be able to explain and apply knowledge and technologies in the field of information technology at a basic level |
| PLO10 | Be able to demonstrate skills of programming and computer problem-solving |
| PLO11 | Be able to apply knowledge of theory, practice and tools to analyze, design and deploy software applications |
| PLO12 | Be able to apply knowledge and skills of the professional field to the context of corporate and social with diverse professional requirements |
| 4 | SPECIALIZED KNOWLEDGE AND SKILLS |
| PLO13 | Be able to understand and apply mathematical knowledge and common development tools in the field of artificial intelligence |
| PLO14 | Be able to synthesize and analyze core technological knowledge and tools of artificial intelligence and data science to build intelligent systems applying artificial intelligence and data science |
| PLO15 | Apply knowledge of AI technology and data science to solve practical problems for businesses |
| PLO16 | Be able to update and utilize advanced tools and techniques in the field of AI in particular and IT in general |
| PLO17 | Be able to develop professional AI products independently and in a team based on understanding of specification, design and commercialization of AI products |
Volume of knowledge in the program
145 credits, excluding Orientation and General Training Program and Preparation English.
| No. | Module | Duration/Number of courses | Credits | Notes |
| 1 | Orientation and General Training Program | 5 weeks | 0 | Certificate |
| 2 | Preparation English | 0 – 1 year | 0 | Certificate |
| 3 | Physical Education | Interleaved | 6 | Certificate |
| 4 | Professional program, including On-the-Job-Training | 9 semesters (42 courses) |
139 | Accumulated grades |
| 4.1 | General knowledge and skills | 13 courses | 35 | |
| 4.2 | Major knowledge and skills, including OJT | 12 courses | 43 [10] | |
| 4.3 | Specialized knowledge and skills | 13 courses | 49 | |
| 4.4 | Elective knowledge and skills | 4 courses | 12 |
Admission eligibility
- In accordance with regulations on formal university enrollment; college enrollment of the Ministry of Education and Training.
- In accordance with regulations on enrollment of FPT University.
Training process, graduating conditions
- In accordance with regulations on formal university and college training of the Ministry of Education and Training.
- In accordance with regulations on training of FPT University.
Evaluation method
- In accordance with regulations on examination and assessment in the training regulations of FPT University.
A guide to implementation
Training methods:
- Most of the courses of major and specialized knowledge and skills will use materials and exams in English.
- Forms of teaching and learning: about 80% of the total courses will be deployed in the form of on-campus teaching (offline) and 20% will be studied online (on FPT-Coursera platform, etc.) with assessment tests are performed at school. There will be 1 online course/term on average.
- Sandwich model: The overall training program is implemented in 4 phases, students must complete the previous period before moving to the following one:
- Phase 1: Preparation (from 1 to 3 semesters), students are required to get a general English level equivalent to IELTS 6.0 before moving to learn professional programs;
- Phase 2: Foundation and concentration (the first 5 semesters);
- Phase 3: On-the-Job-Training (semester 6);
- Phase 4: Enhance professional knowledge, ensure necessary and sufficient conditions for graduation (the last 3 semesters).
Teaching and Learning Methods:
- Choose teaching and learning methods that help promote students’ experiences in university such as group work experiences, internship experiences and academic experiences in various forms within courses and learning periods.
- Exploit and apply a variety of teaching and learning methods such as social constructionism, experiencing, learning through projects, collaboration, etc. to enhance students’ active learning, facilitate and instruct learners to access and utilize knowledge from different learning materials and utilize the strengths of methods in the new technology era.