Master of Science Program in Management of Analytics and Data Technologies (MADT)
Master of Science Program in Management of Analytics and Data Technologies (MADT)
The development of the Master of Science Program in Management of Analytics and Data Technologies aims to produce personnel who are capable of creating values from data using their abilities to manage analytics and data technologies. This is related and responding to the missions of the Institute, which are to focus on producing graduates at the graduate studies levels who have leadership skills, are capable of developing knowledge, research and academic services related to development management. The hope is for personnel in the country to have sufficient potential in order to develop the country sustainably. The goals of the program also aim at developing master’s degree graduates to understanding the application of analytics and data technologies in order to create real values from data. Additionally, they will have an understanding related to modern and correct analytics and data technologies along with leadership skills, responsibilities and abilities to work smoothly with others.
Potential careers
- ประธานผู้บริหารฝ่ายข้อมูล
- Data Scientists Manager
- Data Engineer Manager
- Data Savvy or Data Translator
- Privacy Manager
- Data Governance Facilitator
- Startup
| Plan A2: Thesis | Plan B: Non-thesis | |
| Foundation courses | Non-credit | Non-credit |
| Core courses | 15 credits | 6 credits |
| Elective courses (Minimum) | 9 credits | 18 credits |
| Independent study | – | 3 credits |
| Comprehensive exam | Exam | Exam |
| Oral exam | – | Exam |
| Thesis (Passed thesis) | 12 credits | – |
| Not less than | 36 credits | 36 credits |
| ND 4000 | Foundation for Graduate Studies | 3(3 – 0 – 6) |
| LC 4001 | Reading Skills Development in English for Graduate Studies | 3(3 – 0 – 6) |
| LC 4002 | Integrated English Language Skills Development | 3(3 – 0 – 6) |
| LC 4011* | การซ่อมเสริมการพัฒนาทักษะการอ่านภาษาอังกฤษสำหรับบัณฑิต | 3(3 – 0 – 6) |
| LC 4012* | Remedial Integrated English Language Skills Development | 3(3 – 0 – 6) |
| MADT 4001 | Introduction to Data Analytics | 3(3 – 0 – 6) |
| MADT 4002 | English for Business Communications | 3(3 – 0 – 6) |
Note 1. Requirements and exceptions for foundation courses shall be in accordance with an announcement of the School/Institute except those for English foundation courses offered by the Graduate School of Language and Communication, which shall be in accordance with the conditions of the English for Graduate course.
- In case the English for Graduate Studies course is revised, supplementary English foundation courses required in this program shall change according to the revised English for Graduate Studies course.
- Regular program students are required to enroll in 2 courses: LC 4001 Reading Skills Development in English for Graduate Studies Levels and LC 4002 Integrated English Skills Development while special programs students are required to enroll in 1 English language course: MADT 4002 English for Business Communication.
- Students may be exempt from MADT 4001 Foundation of Data Analysis and MADT 4002 English for Business Communication, which shall be in accordance with an announcement of the school.
(2) Core courses designed for students to have the specific knowledge and expertise including the followings: (15 credits of the core courses are required for Plan A2 and Plan B)
| MADT 6001 | Fundamentals of Business Analytics | 3(3 – 0 – 6) |
| MADT 6002 | Introduction to Data Technologies | 3(3 – 0 – 6) |
| MADT 6003 | Professional Culture in Data Analytics | 3(3 – 0 – 6) |
| MADT 6004 | Applied Data Analytics for Business | 3(3 – 0 – 6) |
| MADT 6005 | Modern Data Management | 3(3 – 0 – 6) |
(3) Elective courses Plan A requires at least 9 credits while Plan B requires at least 18 credits. Students may enroll in the courses of their interest subject to approval from a supervisor.
Data analysis courses
| MADT 7101 | Advanced Business Reporting | 3(3 – 0 – 6) |
| MADT 7102 | Data Modeling, Transformation, and Quality Management | 3(3 – 0 – 6) |
| MADT 7103 | Use Cases and Case Studies in Business Analytics | 3(3 – 0 – 6) |
| MADT 7104 | Digital Transformation with Data Analytics | 3(3 – 0 – 6) |
Technology data courses
| MADT 7201 | Cloud Infrastructure: Design, Development, and Management | 3(3 – 0 – 6) |
| MADT 7202 | Web and Social Network Analytics Management | 3(3 – 0 – 6) |
| MADT 7203 | Data Security in the 21st Century | 3(3 – 0 – 6) |
| MADT 7204 | Big Data Applications - Practical Applications | 3(3 – 0 – 6) |
Seminars and selected topics on data and technology data analysis management
| MADT 8000 | Seminar in Management of Analytics and Data Technologies | 3(3 – 0 – 6) |
| MADT 8101-8109 | Selected Topics in Management of Analytics and Data Technologies | 3(3 – 0 – 6) |
Note 1. Other than the elective courses above, students may also choose an elective course from other programs should it be appropriate, subject to the discretion of a supervisor.
- Elective course management shall be in accordance with the requirements of the School and the Institute.
(5) Independent study
| MADT 9000 | Independent Study | 3(0 – 0 – 12) |
(6) Thesis
| MADT 9004 | Thesis | 12 credits |
| ELOs | Levels of Educational Learning Outcomes in Bloom’s Taxonomy | |
| ELO 1 | ELO 1: Follows the official Academic Code of Ethics and makes decisions to adhere to professional principles and policies. | knowledge |
| ELO 2 | ELO 2: Understand principles, theories, and necessary knowledge in data management, data analysis, and information technology for lifelong self-learning. | Comprehend |
| ELO 3 | ELO 3: Analyze and evaluate business problems systematically. | Application |
| ELO 4 | ELO 4: Solve problems with analytical thinking. and develop appropriate solutions to the problem. | Analysis |
| ELO 5 | ELO 5: Have communication skills Leadership and can work together smoothly with others | Synthesis |
| ELO 6 | ELO 6: Apply information technology effectively and efficiently. | Evaluation |
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