MA - Information Design and Technology (Applied)

General knowledge: 11 CREDITS

Course	Credits
1. Philosophy	4
The Philosophy module has 8 chapters: The introductory chapter introduces an overview of philosophy and the history of philosophy. The next three chapters cover the basic contents of ontology, dialectic and epistemology in the history of philosophy, thereby reinforcing the dialectical materialist worldview and dialectical materialist methodology. building a dialectical thinking style for learners. The following four chapters cover the philosophical and theoretical contents of society (economic, political, social and spiritual) and human, thereby reinforcing the dialectical materialist conception of history and human life, humanitarian and revolutionary agency, helping learners to recognize and appreciate the achievements and difficulties of the Vietnamese revolution, especially in the Doi Moi period, and to apply philosophical contents to professional activities. Since equipping students with general theoretical knowledge and fundamental principles to guide cognitive and practical activities, the Philosophy course should be arranged before the specialized courses in the training program.
2. Foreign language	4
The course aims at developing knowledge and language skills that help learners be able to communicate in academic contexts. In particular, it enables learners to study issues regarding their academic majors through reading specialized reference materials and presenting their ideas in English. Topics include business and economics, employment, manufacturing, marketing, banking, business ethics, exchange rates, and international trade.
3. Research methods	3
The Scientific Research Methods course helps graduate students identify business academic and practical problems. From there, propose research/studies to solve the problems. To do this, the course will equip students with basic knowledge about research types, research designs, research methods, methods of data collection, data analysis and research result. This course provides important background knowledge and skills for students to understand the process of independently conducting an academic or applied research project in the business field. This subject is related to previous subjects such as applied statistics in business and management, as well as parallel or successor subjects such as Marketing Management, Organizational Behavior, Human Resource Management...

Subjects of Major: 9 CREDITS

Course	Credits
4. Integrated Marketing Communication	3
The course content is divided into four parts: two theoretical parts and two practical parts with case studies. In the theoretical part, the course content covers three aspects: The nature and evolution of Marketing communication (IMC), introduces IMC tools and their application in marketing decisions. Especially, this theory helps students realize the essence of marketing communication strategies in branding. The second part of the theoretical system is lectures on mass media planning, building performance metrics and how to effectively coordinate IMC tools on an integrated platform. This content is arranged in three chapters with a duration of twelve hours. In this content, we will cover the creative dimension and its role in the five IMC tools. The third part is about group exercises related to IMC research, IMC tools in terms of application. In this part, students are required to read documents, synthesize information and report on research results as required. Part four is case discussion, this content includes case discussion according to the lecturer's documents and the situation that students are required to research to present in class. This content is intended to ensure that students have a basic understanding of the subject content.
5. Data Analytics	3
The course is intended as an introduction to the field of analysis. After studying, students will understand the method of recognizing an analytical problem in the context; be able to identify and collect the necessary data sources; Skilled in data preparation, and analysis. The module also emphasizes ethical behavior, and the ability to communicate results.
6. Statistics for machine learning	3
The module aims to introduce students to modern theories, models, and methods for applying statistics to the field of machine learning. Upon completion of the module, students have the knowledge and skills to build statistically-based machine learning models, using appropriate software packages to run and present results effectively.

Subject of Minor: 27 CREDITS

Course	Credits
7. Information Design and Content Strategy	3
This module equips students with knowledge about information design and content strategy development, including: information identification methods, information design, content strategy formulation and solution evaluation, new concept of information access and formulation of information design as a form of data preparation and data availability in an information and communication strategy. Simultaneously perfecting application skills based on automatic and intelligent technology systems for the fields of: Marketing, supply chain, financial services and banking.
8. Advanced Data Mining	3
This module aims to equip students with knowledge and skills to apply advanced methods of Data Mining in economic data analysis, the ability to participate in data mining projects for research and management in the fields of marketing, logistics, supply chain, finance, banking.
9. Social Network Data Analytics	3
This module equips students with knowledge and skills to apply technology methods (ICT) in collecting and analyzing social network data, and applying them to big data mining projects for research and management in the fields of: marketing, logistics, supply chain, finance, banking.
10. Natural Language Processing	3
Equip students with basic knowledge about natural language processing processes including: data collection, data cleaning, feature extraction, processing model building. Students will be provided with knowledge about the necessary libraries to collect and build data sets from Internet sources such as news sites, Wikipedia, social networks such as Twitter, Facebook, Youtube, commercial sites, etc. e-commerce such as Shopee, Tiki. In the steps of data cleaning and extraction, in addition to the general steps, students are also introduced to steps that are specifically applied to Vietnamese data. Regarding the processing model, students will be provided with basic knowledge of Machine Learning and Deep Learning to be able to solve basic problems such as classification, clustering, text summarization, machine translation. Students will practice using the Python language on the Google Colab virtual machine during the course. At the end of the course, students are able to collect and build English or Vietnamese data sets for natural language processing problems and know how to develop Machine Learning and Deep Learning models to solve these problems.
11. Data Visualization	3
The course aims to equip students with foundational knowledge and practice skills related to exploiting big data warehouses (DW) in an intuitive and diverse manner with popular tools to serve the needs of customers services for business activities.
- Elective: Select 4 out of 7	12

12. Big data and applications	3
This module equips students with knowledge and skills to apply technology methods (ICT) in applying big data in business areas such as product design, marketing, and supply chain management, finance - banking and decision making.
13. Machine learning and econometrics	3
By completion of this module, students will be able to rely on computer assistance to specify, estimate, and ensure the application of machine learning and econometric models to solving analytical and forecasting problems. Students are able to design and use statistical packages to build a computer solution for practical problems related to the fields of economics, finance, management and decision making. Students also have the ability to discuss in depth the issues that arise in the analysis of empirical data.
14. Digital Marketing Analytics	3
This module helps students understand the digital media used in modern marketing communications; Analytical methods and tools to measure the effectiveness of marketing communications in the digital environment.
15. Artificial Intelligence for Business	3
This module aims to equip learners with knowledge of Artificial Intelligence (AI) problem solving methods, skills to apply AI methods to practical problems of the socio-economic field. On that basis, helping learners with the necessary knowledge and skills to participate in the development of software projects for research and management in the fields of marketing, supply chain management, financial analysis main, credit activity analysis.
16. High Performance Computing	3
This module aims to equip learners with basic knowledge of high performance computing (HPC) systems, HPC problems and methods; covers HPC models, principles, evaluation methods, and applications of HPC for applied data science. On that basis, it helps learners master the knowledge about HPC, the necessary skills in applying and exploiting HPC systems to serve data science problems in enterprises, especially enterprises in the field of HPC: marketing, supply chain management, financial analysis, credit and insurance.
17. Blockchain technology and Metaverse	3
This module aims to equip students with knowledge and applications of Blockchain in solving economic problems, Having skills in analyzing and evaluating opportunities for Blockchain application in businesses, skills in choosing solutions, technologies, means and ways of implementing Blockchain to solve real problems, especially problems that other solutions cannot do. Having knowledge and skills to build a simple Blockchain System, create smart contracts, cryptocurrency. In addition, students will understand how the virtual world of Metaverse will take place in the near future, the concept of Metaverse will change the old definitions of information and communication.
18. Marketing Technology	3
Upon completion of this module, students will be able to rely on computer support and especially data science to solve analytical problems and forecast information, advertising and communication strategies in the digital world. Students have the ability to strategize, design and master data analysis tools/software before or in a marketing strategy. And especially having the ability to build a customer database that is transparent and consistent with the customer journey itself. Students will also be able to engage in in-depth discussions on issues that arise in the analysis of empirical data directly related to marketing, communication and advertising.

Graduation Internship: 13 CREDITS

Course	Credits
19. Extra - Curriculum Report	3

20. Assignment	3

21. Project	7

UEH Master

General knowledge: 11 CREDITS

Subjects of Major: 9 CREDITS

Subject of Minor: 27 CREDITS

Graduation Internship: 13 CREDITS

Total credits: 60 CREDITS