Economic Data Analytics— EP03

After graduation, students in the Economic Data Analytics (EDA) program will master the following knowledge:

• Understand fundamental economic and business principles of the economy and enterprises, especially in banking–finance, e-commerce, and tourism sectors;

• Understand and effectively apply mathematical and statistical concepts and methods in data collection, data analysis, modeling, and statistical inference;

• Understand and effectively apply machine learning concepts and methods suitable for data analysis and big data;

• Understand and master the process of building models in data analytics and big data based on practical requirements in economics and business;

• Have the ability to design algorithms to solve economic and business problems with big data based on mathematical, statistical, and computational methods;

• Be able to combine analytical results with domain knowledge to propose recommendations that support decision-making in economics and business.

Learning outcomes in terms of skills:

• Be proficient in specialized programming languages: R, Python, SQL;

• Have skills in designing questionnaires for structured data collection and IT skills for collecting unstructured data;

• Have skills in data management, aggregation, and extraction;

• Have skills in extracting information, identifying hidden trends, and discovering new knowledge from data;

• Have skills in algorithm design and programming to solve emerging data and big data-related problems;

• Possess soft skills: information searching and summarizing, report writing, presentation, teamwork, communication and collaboration, independent working, effective work organization, time management, critical thinking, and team leadership.

Learning outcomes in terms of attitude and professional ethics:

• Possess professional ethics and responsibility;

• Comply with state laws and organizational regulations;

• Demonstrate seriousness and integrity in studying, research, and work;

• Adhere to corporate culture.

Learning outcomes in terms of foreign language and information technology:

• Achieve English proficiency at IELTS 6.0 or equivalent;

• Achieve IT proficiency with the IC3 (Internet and Computing Core Certification), an international certification on computer and Internet usage issued by Certiport (USA);

• Have the ability to use programming languages and effectively utilize software for research and applications in Economics and Business.

Graduates of the Economic Data Analytics (EDA) program can work in the following positions:

• Experts in building analytical and market forecasting models in manufacturing and service enterprises;

• Experts in developing automated segmentation models and customer support systems in banks, financial institutions, and service enterprises;

• Research and consulting specialists at domestic and international market research centers;

• Experts in research and data/big data analysis at enterprises, consulting firms, research institutes, and government agencies;

• Customer information management specialists in enterprises.

Opportunities for Further Education:

• After graduation, learners have advantages in pursuing Master’s and PhD programs in data science, data analytics, and business analytics at prestigious universities around the world.

• After graduation, students in the Data Science in Economics and Business program will master the following knowledge:

• Understand fundamental economic and business principles of the economy and enterprises, especially in sectors such as banking–finance, e-commerce, and tourism;

• Understand and effectively apply concepts and methods of mathematics and statistics in data collection, data analysis, modeling, and statistical inference;

• Understand and effectively apply machine learning concepts and methods suitable for data analytics and big data;

• Understand and master the process of building models in data analytics and big data based on practical requirements in economics and business;

• Have the ability to design algorithms to solve economic and business problems involving big data based on knowledge and methods of mathematics, statistics, and information technology;

• Have the ability to integrate analytical results with domain knowledge to propose recommendations that support decision-making in economics and business.