The advent and advancement of information technology bring the current world into big data era such that data are high in their variety, volume, and velocity. Such rapid changes intensify the need to pre-process, process, and analyze big data into information and intelligence and then ultimately convert information and intelligence into competitive advantage and actionable plans which eventually contribute social, economic, and national development in a long-run.
Especially, Thailand has confronted middle income trap that hinder our national development. Hence, we strongly need to transform data into information and intelligence as a part of value creation process to build up competitive advantage such that we can create knowledge-based economy and leave away from the labour-intensive or capital intensive economy.
This curriculum aims at developing Ph.D. graduate with 21st century skills with strong research and statistical methodology and skills, information technology skills, and inquiry skills so that they can apply, analyze, solve, and provide better solutions for business, finance, insurance, logistics, industry, society, economic, and national problems to achieve sustainable development.
Integration between multidiscliplinary and technology fusion in the current world leads to social and economic innovation. Such changes make it harder for graduates who acquire solely acquire knowledge in any single discipline to compete and succeed. This curriculum has been improved by harmonizing and integrating between several disciplines to align with frontier of knowledge and state-of-the art practices.
From the impact of external situations above, the objectives of program development is to produce researchers, scholars, professors, specialists and consultants with capability to synthesize theories for building new knowledge, to transfer knowledge, to analyze complicated problems. These products must have potential in self-development in their job both in the aspects of academic and professional with morality and ethics. These characteristics are reflected in various courses of the program.
Moreover, the integration and convergence among discipline are the key factors in the current world of work as well as the advent of big data and data sciences. Hence, the curriculum and major have been revised tremendously to reflect those trends and situations.
Business analytics and data science major has been opened to reflect the integration between business and data analysis as well as to align with current practice in the field of business analytics and intelligence and data sciences.
(1) Remedial Courses
Students in Plan 1(1.1) and 2(2.1) are subjected to take remedial course in English as non credit in following courses,
LC 4003 Advanced Integrated English Language Skills Development 3 Credits*
LC 6000 Advanced Reading and Writing in English for Graduate Studies 3 Credits*
* Non credit
(2) Core Course
Students in Plan 2(2.1) of each major must enroll in the core course for 12 credits as follows,
(1) BADS 6050 Epistemiology and Research Methodology 3 Credits
(2) BADS 6051 Theories and Research in Big Data Engineering 3 Credits
(3) BADS 6052 Theories and Research in Machine Learning 3 Credits
(4) BADS 6053 Advanced Statistical Analysis 3 Credits
(3) Major Courses
Students of Plan 2(2.1) in each major must enroll in major courses for 12 credits as follows,
(1) BADS 7150 Advanced Marketing Models 3 Credits
(2) BADS 7151 Predictive Modeling in Finance 3 Credits
(3) BADS 7250 Advanced Image Analytics 3 Credits
(4) BADS 7152 Business Information Visualization and Descriptive Analytics 3 Credits
(4) Elective Courses
Students of Plan 2(2.1) in each major must enroll in elective course for at least 12 credits as follows,
(1) BADS 7160 Advanced Big Data Management 3 Credits
(2) BADS 7161 Modeling Techniques in Marketing Decision 3 Credits
(3) BADS 7163 Advanced Customer Relationship Management Analytics 3 Credits
(4) BADS 7164 Prescriptive Analytics in Business Analytics and Data Sciences 3 Credits
(5) BADS 7165 Theories and Practices in Social Network and Media Analysis 3 Credits
(6) BADS 7166 Theories and Practices in Spatial Data Analysis 3 Credits
(7) BADS 7167 Thoeries and Models for Project/Program Evaluation 3 Credits
(8) BADS 7168 Advanced Poll and Public Opinion Survey Methodology 3 Credits
(9) BADS 7251 Advanced Text Analytics and Natural Language Processing 3 Credits
(10) BADS 7153 Advanced Human Resource Analytics 3 Credits
(11) BADS 7252 Advanced Distributed, Paralell, and Cloud Computing 3 Credits
(12) BADS 7253 Advance Real Time Analytics and Automation 3 Credits
(13) BADS 7261 Advanced Speech Recognition 3 Credits
(14) BADS 7262 Advanced Cognitive Analytics 3 Credits
(15) BADS 7263 Advanced Machine Learning 3 Credits
(16) BADS 7264 Advanced Artificial Intelligence 3 Credits
(17) BADS 7265 Advanced Bioinformatics 3 Credits
(18) BADS 7266 Advanced Medical Image Analytics 3 Credits
Selected Topics in Business Analytics and Data Science
(1) BADS 8001-8010 Readings in Business Analytics and Data Sceince 3 Credits
(2) BADS 8011-8020 Practicum in Business Analytics and Data Sceince 3 Credits
(3) BADS 8021 Seminar in Business Analytics and Data Sceince 3 Credits
(4) BADS 8801-8820 Selected Topics in Business Analytics and Data Sceince 3 Credits
(1) The Elective courses also include other graduate courses offered by the school or others in NIDA (To register for these courses, students must receive approvals from his/her advisor) (2) Courses opened in each semester will be selected by the school and the institute.
(1) BADS 9000 Independent study 3
(1) BADS 9900 Dissertation 36/48 Credits
- N/A -
- N/A -