1. Objectives

Training Data Analytics Academic Program engineers belonging to the Artificial Intelligence major who possess political qualities, ethics, professional responsibility, and a sense of community service; possessing knowledge, professional skills, and research capacity commensurate with the training level; possessing good health, well-meeting labor demands in the period of international integration and the Fourth Industrial Revolution.

Specific objectives (POs - Programme Objectives) of the Data Analytics Academic Program:

• PO1. Have basic knowledge of natural sciences, social sciences, comprehensive, specialized, and advanced knowledge in the field of Data Science and Artificial Intelligence;
• PO2. Have the ability to research, solve problems, and provide expert-level proposals and conclusions in the field of Data Science and Artificial Intelligence;
• PO3. Have skills to work independently, work in teams, soft skills, and the ability to use foreign languages for learning, work, and career development;
• PO4. Have good ethics to work and be useful to the community.

The above POs are also commensurate with the knowledge, skills, and attitudes that learners need to achieve after completing the Data Analytics specialization at the university.

2. Expected Learning Outcomes

Graduates of the Data Analytics Academic Program Engineer program need to achieve the following Programme Learning Outcomes (PLOs):

a. PLO1. Have ethics, responsibility towards the profession and community;

• PI1.1 Be honest in work.
• PI1.2 Have responsibility towards work and community.
• PI1.3 Comply with regulations, technical processes, and safety rules while performing work.

b. PLO2. Communicate and work in teams effectively;

• PI2.1 Present and speech on issues.
• PI2.2 Draft documents and reports with proper structures according to regulations.
• PI2.3 Work in teams effectively.

c. PLO3. Have critical, creative, and entrepreneurial thinking;

• PI3.1 Comment on and evaluate scientific reports.
• PI3.2 Propose IT solutions corresponding to reality.
• PI3.3 Formulate startup projects.

d. PLO4. Have the ability to use foreign languages in communication and in the field of IT, Data Science, and Artificial Intelligence;

• PI4.1 Use foreign languages to present issues in the field of IT, Data Science, and Artificial Intelligence.
• PI4.2 Have the ability to use foreign languages in communication (Reach English proficiency level 4/6 of the Vietnamese Foreign Language Proficiency Framework. With an international Toeic English certificate, a minimum of 600 is required).

e. PLO5. Apply knowledge of natural sciences, social sciences, computer science, and artificial intelligence to solve basic problems;

1. PI5.1 Apply knowledge of natural sciences and IT to solve IT application problems.
2. PI5.2 Apply knowledge of social sciences into practical work.

f. PLO6. Apply knowledge of Data Science and Artificial Intelligence to process and analyze data;

1. PI6.1 Process and organize data.
2. PI6.2 Analyze and visualize data.
3. PI6.3 Build and administer a complete database for an application software.

g. PLO7. Apply knowledge of Data Science and Artificial Intelligence to build prediction models;

• PI7.1 Build prediction models.
• PI7.2 Evaluate prediction models.

h. PLO8. Have the ability to develop data analysis tools.

• PI8.1 Develop data analysis tools.
• PI8.2 Evaluate data analysis tools.

The program is designed flexibly with many topics and elective courses. Besides the core courses, students can learn and explore through advanced courses such as: Data Analytics, time series data analysis, big data processing,...; Understand and work with many different types of data such as tabular, text, audio, image, video in fields such as: Business, finance, economics, society,... After graduating according to this DA Academic Program orientation, students can build and evaluate prediction models, and develop data analysis tools.