Program Overview
Master of Science Program in Data Analytics and Data Science (DADS)
The Master of Science Program in Data Analytics and Data Science (Revised Program B.E. 2564) has been revised from the Master of Science in Business Analysis and Data Science (Revised Program B.E. 2563). This has resulted from the rapid changes and difficult predications in politics, economy, society, disasters and illnesses in the era that information technology is widely used. This leads to a creation of massive data, which is crucial to learning, understanding, analyzing and managing of the data in the most systematic and useful manner. Additionally, this is to strengthen the field of data analysis and data science, which is the identity of the Institute to be better in line with the notion of King Rama IX who established the Institute and particularly the Graduate School of Applied Statistics. In his vision, national development would require data and scientific knowledge. Thus, the objective of this program is to produce personnel for the country in response to the royal initiative on establishing the National Institute of Development Administration.
Potential careers
- Business Analyst , Strategic Planner , Strategic Analyst , Business Planner , Business Developer
- Data Scientist
- Statistician, Statistics Officer
- Big Data Analyst
- Researcher, Marketing Researcher, Big Data Analytics Researcher
- Data Engineer
- Artificial Intelligence Engineer
- IT Manager, IT Project Manager
- Computer and IT Officer
- System Analyst
- Information System Auditor/Tester , Software Auditor/Tester
- University Professor/Academician
Program Structure
| Plan A2: Thesis | Plan B: Non-thesis | |
|---|---|---|
| Foundation courses | Non-credit | Non-credit |
| Core courses | 6 credits | 6 credits |
| Major courses | 15 credits | 15 credits |
| Elective courses | 3 credits | 12 credits |
| Independent study | – | 3 credits |
| Comprehensive exam | Exam | Exam |
| Oral exam | – | Exam |
| Thesis (Passed thesis) | 12 credits | – |
| Not less than | 36 credits | 36 credits |
Course Details
mean courses designed to provide knowledge at levels below graduate studies for students to be ready for the master’s degree level including
| ND 4000 | Foundation for Graduate Studies | 3(2–2-5) |
| LC 4001 | Reading Skills Development in English for Graduate Studies | 3(2–2-5) |
| LC 4002 | Integrated English Language Skills Development | 3(2–2-5) |
| LC 4011* | Remedial Reading Skills Development in English for Graduate Studies | 3(2–2-5) |
| LC 4012 | Remedial Integrated English Language Skills Development | 3(2–2-5) |
| DADS 4001 | Statistics and Mathematics Foundation | 3(3–0-6) |
| DADS 4002 | Basic Programming and Database Management | 3(3–0-6) |
| DADS 4003 | English for Data Analytics and Data Science | 3(2–2-5) |
หมายเหตุ
- 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.
mean 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)
| DADS 5001 | Data Analytics and Data Science Tools and Programming | 3(3–0-6) |
| DADS 5002 | Business Model Simulation and Design Thinking | 3(3–0-6) |
mean 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)
| DADS 6001 | Applied Modern Statistical Analysis | 3(3–0-6) |
| DADS 6002 | Big Data Analytics | 3(3–0-6) |
| DADS 6003 | Applied Machine Learning | 3(3–0-6) |
| DADS 6004 | Financial and Risk Analytics | 3(3–0-6) |
| DADS 6005 | Data Streaming and Real Time Analytics | 3(3–0-6) |
include the following courses. For Plan A2, at least 3 credits are required, and at least 12 credits for Plan B. Students can enroll in the courses according to their interest, subject to approval of their supervisor.
| DADS 7101 | Customer and Marketing Analytics | 3(3–0-6) |
| DADS 7102 DADS 7103 DADS 7104 | Applied Optimization and Prescriptive Analytics Supply Chain Analytics Presentational Strategies Competence Development for Business Success | 3(3–0-6) 3(3–0-6) 3(3–0-6) |
| DADS 7201 | Social Network and Media Analysis | 3(3–0-6) |
| DADS 7202 | Deep Learning | 3(3–0-6) |
| DADS 7203 | Text Analytics and Natural Language Processing | 3(3–0-6) |
| DADS 7204 | Reinforcement Learning and Advanced Machine Learning | 3(3–0-6) |
| DADS 7205 | Research Design and Inquiry Methods | 3(3–0-6) |
| DADS 7206 | Image and Video Analytics | 3(3–0-6) |
| DADS 8710-8720 | Selected Topics in Data Analytics and Data Science | 3(3–0-6) |
| DADS 8721 | Seminar in Data Analytics and Data Science | 3(0–3-6) |
หมายเหตุ – นอกเหนือจากกลุ่มวิชาเลือกดังกล่าวแล้ว นักศึกษาอาจเลือกเรียนวิชาเลือกเสรีจากหลักสูตรอื่น ๆ และ/หรือของสถาบันได้อีกตามความเหมาะสม ทั้งนี้ให้อยู่ในดุลพินิจของอาจารย์ที่ปรึกษาและ/หรือ อาจารย์ผู้รับผิดชอบหลักสูตร โดยการจัดการเรียนการสอนในหมวดวิชาเลือกให้เป็นไปตามที่คณะกำหนด
| DADS 9000 | Independent Study | 3(0–0-12) |
| DADS 9004 | Thesis | 12 credits |
Overall Expenses
Program Detail
| ELOs | Expected Learning Outcomes (ELO) | Levels of Educational Learning Outcomes in Bloom’s Taxonomy |
|---|---|---|
| ELO1 | Follow the code of ethics for professional practice. Work and make decisions in accordance with the Code of Professional Behavior and Ethics. | remember |
| ELO2 | Understand the principles, theories, and knowledge necessary for lifelong self-learning. | understand |
| ELO3 | Apply knowledge to practical problems. | apply |
| ELO4 | Solve problems with analytical thinking and creativity. | analyze and evaluate |
| ELO5 | Effectively present and communicate knowledge and information to the target audience. | create |
| ELO6 | Use information technology effectively to solve actual practical problems. | apply |
Contact Us
GRADUATE SCHOOL OF APPLIED STATISTICS (GSAS)
National Institute of Development Administration (NIDA) Navamindradhiraj Building, 12th floor 148 Serithai Road, Klong-Chan, Bangkapi, Bangkok THAILAND 10240
Tel : 02-727-3035-40
Fax : 02-374-4061
Facebook : GSASNIDA
Line : GSAS NIDA
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