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MS Computer Science: Data Analytics and Science
MS
12-18 Months
Ongoing
Full-time/Part-time
Online
฿39,000
฿54,000
All education backgrounds are welcome, including individuals without an undergraduate degree.
Advance your expertise in one of the fastest-growing fields with our Master of Science in Computer Science: Data Analytics and Science. This internationally accredited program provides an in-depth understanding of data-driven decision-making, equipping you with the skills to analyze, interpret, and visualize complex datasets. The program’s flexible online format allows you to study at your own pace while balancing professional and personal commitments.
This degree is built on the European Credit Transfer and Accumulation System (ECTS), the most widely recognized credit system globally. As an ECTS-accredited program, your degree is accepted internationally, enhancing your career opportunities across industries and regions.
What you will learn
Our specialized curriculum focuses on the essential skills needed for success in data analytics and science, including:
- Developing expertise in data analysis and visualization using tools like Python, R, and Tableau;
- Building and deploying machine learning models for predictive analytics;
- Mastering big data frameworks and tools for processing large datasets;
- Applying advanced techniques in data cleaning, integration, and interpretation for actionable insights.
Graduates of this program are well-prepared for roles such as data scientist, business intelligence analyst, or machine learning engineer. With the global recognition of an ECTS-accredited degree, you’ll have the credentials and skills to succeed in the data-driven world.
Join us to turn data into impactful solutions and advance your career in this high-demand field.
Job Guarantee - Get a Job in 7 Months or Get a Refund
We're dedicated to turning learning into careers. That’s why we introduced our Job Guarantee—making your learning journey risk-free. It’s simple: secure a job within 7 months of graduation, or we’ll refund your tuition.
Teaching and Assessments
Study With Your Personal Teaching Team
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Faculty Advisor
Schedule unlimited 1-on-1 lessons with industry and research experts in their field.
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Career Advisor
Get matched with an experienced career counseling expert who will help you achieve your goals.
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Student Success Manager
Your success manager keeps you on track and supports every aspect of your learning.
Learning
Contents
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40% Machine learning and Artificial Intelligence
40% Data Analytics and Visualization
20% Specialized Topics
Learning Method
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20% 1-on-1 Sessions
15% Office Hours
30% Video Lectures
30% Projects
Learning Timeline
Part-time
Estimated Time of Completion: 12-17 Months
Study load: 35-45 Hours/Week
Career Coaching Starts: Month 6
Full-Time
Estimated Time of Completion: 9-12 Months
Study load: 35-45 Hours/Week
Career Coaching Starts: Month 3
STRUCTURE
Learn more about the structure of your program below.
Core Modules
Spreadsheets for Data Understanding
Designed for all skill levels, this course covers Excel basics to advanced techniques, including data analysis, dynamic charts, and automation with macros. Students will gain practical skills to confidently manage data, create complex formulas, and enhance professional productivity through hands-on exercises.
Data Visualisation Tools
Master Power BI and Tableau to create interactive dashboards and reports. Learn key features, connect data sources, and present insights effectively to support business decisions.
Relational Databases
Develop expertise in database design and SQL for efficient data management. Learn relational modeling, normalization, complex queries, transaction handling, indexing, and advanced SQL features through real-world projects and practical applications
Introduction to Problem-Solving Techniques: Part 1
Master Git and GitHub for version control alongside Python programming from basics to Object-Oriented Programming (OOP). Learn collaboration, data structures, file handling, and OOP concepts like inheritance and encapsulation to build efficient applications.
Numerical Programming in Python
Learn to analyze data efficiently with Python's Pandas library. This course covers data manipulation, cleaning, analysis, and visualization through hands-on exercises and real-world case studies.
Introduction to Machine Learning
Learn the basics of Machine Learning, including key algorithms, supervised and unsupervised learning techniques, and practical applications using frameworks like TensorFlow and scikit-learn. Gain hands-on experience through real-world projects.
Introduction to Deep Learning
Learn the basics of deep learning using PyTorch. This course covers building, training, and deploying neural networks for real-world applications like image classification and natural language processing. Gain hands-on experience to effectively create and deploy deep learning models.
Practical Software Engineering
Learn to develop high-quality software with a focus on testing and reliability. Gain skills in software design, project lifecycle management, unit testing, integration testing, and automated testing tools to ensure efficient and maintainable systems.
Specialization
Data Engineering
This course provides foundational skills in managing and processing large-scale data systems, including Linux and Bash, data warehousing, and building pipelines. Students will design scalable data architectures, automate workflows, and ensure data quality through hands-on projects.
Foundations of Cloud Computing
หลักสูตรนี้แนะนำพื้นฐานการประมวลผลแบบคลาวด์สำหรับนักเรียนและมืออาชีพในสายงาน IT ธุรกิจ และสาขาที่เกี่ยวข้อง ครอบคลุมองค์ประกอบสำคัญ โมเดลการใช้งาน (IaaS, PaaS, SaaS) ประเภทการใช้งาน (Public, Private, Hybrid) ความปลอดภัยของคลาวด์ การจัดเก็บข้อมูล เครือข่าย และกลยุทธ์การย้ายระบบ ผู้เรียนจะได้พัฒนาทักษะในการออกแบบโซลูชันคลาวด์ที่ปรับขนาดได้ มีความน่าเชื่อถือ และคุ้มค่าต่อการใช้งาน
Product Analytics
Learn to improve product performance with data-driven insights. Topics include data analysis, customer behavior, key metrics, A/B testing, predictive models, and ethical considerations. Perfect for business and product professionals.
Introduction to Computer Programming: Part 1
Learn programming fundamentals with JavaScript, including syntax, debugging, variables, control structures, and functions. Build a strong foundation to create interactive web applications, manage data structures, and confidently solve programming challenges.
Introduction to Computer Programming: Part 2
Learn the essentials of JavaScript to build basic web applications. This course covers syntax, loops, functions, objects, and arrays, helping you develop interactive applications and gain confidence in programming.
Front End UI/UX Development
Explore the fundamentals of UX and UI design in this beginner-friendly course. Learn user-centered principles, UX processes, user research, prototyping, and testing. Gain practical experience through real-world projects to create intuitive and engaging digital products.
JavaScript
Elevate your skills with advanced JavaScript concepts and in-depth React development. Master ES6+ features, asynchronous programming, closures, React hooks, Context API, state management with Redux, and API integration to build dynamic, high-performance web applications.
Applied Computer Science Project
Applied Computer Science Project
In this final course, learners will combine the skills they've mastered throughout the program to create a comprehensive, portfolio-worthy project. Designed to be open-ended, this capstone encourages students to explore their unique interests while demonstrating their expertise in real-world applications. Whether it's a groundbreaking app, a stunning website, or an innovative data analysis project, the capstone empowers learners to showcase their creativity and technical prowess.
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Class Schedule
หลักสูตรส่วนใหญ่ของเรา (40 ECTS credits) เรียนแบบ Blocks ซึ่งคุณจะมุ่งเน้นเรียนวิชาเดียวในระยะเวลา 5 สัปดาห์ต่อครั้ง โดยตารางเรียนจะจัดไว้หลัง 19.00 น. ในวันธรรมดา และในช่วงวันหยุดสุดสัปดาห์ พร้อมคลาสสด 2-3 ครั้งต่อสัปดาห์ในแต่ละ Block
เพื่อเพิ่มความยืดหยุ่น วิชาพื้นฐานด้านเทคโนโลยีสองวิชา ได้แก่ Python for Business Analytics และ Data Analytics and Modelling จะจัดการเรียนแบบ asynchronous ที่ให้คุณสามารถเรียนตามจังหวะของตนเองได้
สำหรับหลักสูตร Digital Action Programme for Business Administration (30 ECTS) จะใช้เวลาเรียน 9 เดือน โดยคุณและทีมจะพบกับคณาจารย์แบบออนไลน์ทุกสองสัปดาห์
เราจะเริ่มต้นโปรแกรมด้วยงาน ต้อนรับอย่างเป็นทางการ และปิดท้ายด้วยงาน พิธีสำเร็จการศึกษา ทั้งนี้ในระหว่างโปรแกรมจะมีการจัด กิจกรรมสร้างเครือข่ายแบบพบปะด้วยตนเอง ทุกๆ 1-2 เดือน
Find more details about the teaching and learning format of your program here
ปรึกษาด้านอาชีพ
Accreditation
WeStride Institute of Technology's degrees are currently recognized in both Europe, United States, Canada and more than 60 countries globally. WeStride is a full member college of Woolf, offering accredited programs that adhere to European Standards and Guidelines (ESG) (Brussels 2015). Woolf is an accredited degree-granting higher education institution based in Malta with license number 2019-015.
Our degrees are accepted in Thailand through equivalency of qualifications for foreign higher education graduates Ministry of Higher Education, Science, Research and Innovation. Likewise, the degree is also accepted by the Office of the Civil Service Commission.
Learning Hubs
Learning goes beyond online—our 7 learning hubs across Thailand offer learners the opportunity to connect, explore, and grow in inspiring spaces.
South East Asia University
Phone: 02-8074500 – 27 ext. 190,192
Siam Square Branch
Phone: 090-970-4587
Icon Siam Branch
Phone: 090-971-4415
Salaya Branch
Phone: 090-971-5283
Rangsit Branch
Phone: 090-971-5764
Asok Branch
Phone: 090-969-8084
Ubon Ratchathani Branch
Phone: 090-971-6325
Tuition
Tuition
ผ่อนชำระด้วยบัตรเครดิต ดอกเบี้ย 0%
Additional Costs
Installment Payments
Please consult with your admissions advisor to learn more about the available credit card installment plans and how they can best suit your needs.
Payment Options
Why is the tuition for this degree significantly lower compared to similar programs?
The tuition for this degree is significantly lower due to our thoughtful approach to education and cost management. Here are the key reasons:
- Online Delivery:
By operating primarily online, we eliminate many overhead costs associated with traditional campus-based programs, such as physical facilities and maintenance. This enables us to focus resources directly on delivering high-quality education. - Teaching-Focused University:
As a teaching-focused institution, our resources are dedicated solely to instruction and student success, rather than subsidizing non-revenue-generating activities like large-scale research projects. - Accredited in the EU:
Since we are accredited in the EU, we do not need to adhere to the Thai Ministry of Higher Education’s requirement for students to complete an Independent Study, which is a costly component for most Thai universities. Instead, our learners work on practical projects that provide valuable, hands-on experience while reducing unnecessary expenses. - Accessibility and Affordability:
We are committed to making higher education accessible to as many learners as possible. To achieve this, we avoid adding unnecessary costs, ensuring that our tuition remains fair and affordable without compromising quality. - Focus on Essential Services:
We concentrate on providing what students truly need to succeed—high-quality teaching, accessible support, and practical outcomes—without incurring costs for non-essential campus amenities like sports facilities or luxury housing. - Streamlined Administration:
By operating as a modern, online-first institution, we maintain leaner administrative structures, which further reduces costs. - Efficient Use of Technology:
Advanced learning technologies and platforms streamline course delivery, communication, and assessments, reducing administrative overhead and operational costs.
This combination of factors enables us to provide a world-class degree that is both cost-effective and accessible, without sacrificing the quality of education.
Tax Benefits
Frequently Asked Questions
What Career Can I Pursue After Graduating with an MS in Computer Science: Data Analytics and Science?
Earning an MS in Computer Science with a specialization in Data Analytics and Science opens the door to advanced roles in the tech industry and beyond. Here are some career paths you can pursue:
- Data Scientist
Utilize advanced analytics, statistical methods, and machine learning to interpret data and solve complex problems. - Data Analyst
Analyze and interpret data to provide actionable business insights through visualization and reporting tools. - Machine Learning Engineer
Design, build, and deploy machine learning algorithms to develop intelligent systems. - Business Intelligence (BI) Developer
Create and manage BI solutions to help organizations make data-driven decisions. - Big Data Engineer
Build, maintain, and optimize big data pipelines and architectures for large-scale data processing. - Data Architect
Design and manage the data infrastructure and ensure its efficiency, scalability, and security. - AI Researcher
Conduct advanced research in artificial intelligence, developing new algorithms and applications. - Quantitative Analyst
Apply statistical and mathematical models to solve problems in finance, operations, and marketing. - Product Manager (Data)
Oversee the development and delivery of data-driven products, aligning them with organizational goals. - Chief Data Officer (CDO)
Lead an organization’s data strategy, ensuring data-driven decision-making aligns with business objectives. - Data Consultant
Provide expert advice to organizations on how to leverage data for growth and efficiency.
Industries such as finance, healthcare, technology, retail, and entertainment are in constant demand for professionals with skills in data analytics and science. Your advanced degree will position you as a highly competitive candidate for leadership roles in these fields.
What Are the Minimum Requirements to Enroll in the Master’s Program?
What is PBA?
PBA allows candidates to demonstrate their ability to succeed in the program by completing specific coursework during their first term. This ensures that students are evaluated based on their current skills and dedication rather than solely on past academic performance.
Why Use PBA?
PBA is widely used by many top universities, including Northwestern University, to provide opportunities for students from diverse educational and professional backgrounds. It ensures fairness and accessibility, giving everyone a chance to prove their capabilities.
For more information, read here
In Which Countries Are The Degree Recognized?
The degree is recognized in 65+ countries worldwide because we grant ECTS credits, the most widely recognized credit system globally. Learn more about degree mobility and international recognition on our dedicated page.
What is ECTS? What is the meaning of the MS degree being ECTS backed?
ECTS is a highly sophisticated and globally recognized accreditation system. It serves as the universal standard for accreditation within the European Higher Education Area, which now includes 49 countries. Its widespread recognition stems from its endorsement by a significant network of universities and nations, ensuring its credibility and acceptance worldwide.
Will My Master’s Degree Qualify Me for Entering a PhD Program?
Yes, nearly all PhD programs require a master’s degree, and your degree will be fully accredited and recognized across Europe, meeting the formal qualifications for admission. However, each PhD program has its own unique criteria, with the PhD advisor often playing a key role in the admissions process. When choosing a PhD program, it’s essential to ensure that the focus of your master’s degree aligns closely with the subject of your intended PhD.
How Often Is the Intake?
Bootcamps and Master’s in Computer Science: These programs offer flexible enrollment, allowing you to start at any time that suits you. There’s no fixed intake period, so you can begin your learning journey whenever you’re ready.
Master's in Business Administration Program: The intake for the MBA program is scheduled for mid-July 2025.
Undergraduate Program: The undergraduate program intake begins in August 2025.
Can I Enroll While Working a Full-Time Job?
Yes, our programs are designed with flexibility in mind. Our bootcamps and MS in Computer Science degree allow you to set your own schedule, making it easier to balance with your work commitments. Meanwhile, our undergraduate and MBA programs focus on live classes held during evenings and weekends to accommodate full-time professionals.