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Data Science, Analytics and Engineering Bootcamp
2 Certificates
3-6 Months
Ongoing
Full-time/Part-time
Online
฿38,000
฿41,500
No Minimum Qualifications. All Levels Welcome.
Dive into the dynamic field of data with our Data Analytics, Science, and Engineering Bootcamp. Designed for aspiring data professionals and those looking to enhance their analytical skills, this program offers a comprehensive, hands-on approach to understanding and leveraging data. From foundational concepts to advanced techniques, you’ll learn to analyze, interpret, and visualize data to make informed decisions and solve real-world problems.
Through project-based learning and expert guidance, you’ll master tools like Python, SQL, and Tableau while gaining a deep understanding of data engineering pipelines and machine learning models. By the end of the bootcamp, you’ll have a robust portfolio that showcases your ability to derive insights and drive impactful outcomes with data.
What you will learn
Our carefully crafted curriculum equips you with the skills needed to excel in data analytics, science, and engineering, including:
- Understanding and working with data pipelines and engineering processes;
- Analyzing large datasets using Python, SQL, and advanced data visualization tools;
- Building predictive models through machine learning techniques;
- Gaining expertise in data cleaning, transformation, and integration for decision-making.
Join us to develop the technical skills and problem-solving mindset needed to thrive in today’s data-driven world and make meaningful contributions in any industry.
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% Data Science
30% Data Analytics
30% Data Engineering
Learning Method
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20% การเรียนแบบตัวต่อตัว
15% Office Hours
30% Video Lectures
30% Projects
Learning Timeline
Part-time
Estimated Time of Completion: 6-7 Months
Study load: 15-25 Hours/Week
Career Coaching Starts: Month 5
Full-Time
Estimated Time of Completion: 3-4 Months
Study load: 35-45 Hours/Week
Career Coaching Starts: Month 2
STRUCTURE
Learn more about the structure of your program below.
Core Modules
B. Structured Thinking
Develop structured problem-solving skills through clear frameworks and organized analysis. Learn to model solutions, make effective decisions, and communicate results professionally for real-world applications.
D. Database Design [Optional]
Learn relational database design, including entities, keys, normalization, and dependencies. Gain hands-on experience creating efficient structures and managing relationships for IT, data analysis, and software development.
E. SQL
Master SQL for managing and querying relational databases. Learn to create, update, and retrieve data, use advanced features like JOINs and indexes, and optimize database performance through hands-on projects.
F. Portfolio Project 1
Analyze data using Excel with Open Government Data of Thailand. Learn data preprocessing, visualization, and presentation through platforms like Coda or Notion, building professional portfolio projects for real-world application.
G. Data Visualization with Tableau and Power BI
Learn to create compelling visualizations using Tableau and Power BI. Master importing data, advanced analytics with DAX and calculations, and building charts, maps, and KPIs for effective data presentation.
H. Portfolio Project 2
Enhance data analysis skills using Power BI or Tableau with NASA datasets. Learn DAX or Tableau calculations, data modeling, and professional presentation techniques through platforms like Coda or Notion.
I. Python
Learn Python fundamentals, from setup and basic operations to advanced topics like loops, data structures, and object-oriented programming. Gain hands-on experience to apply Python skills in IT, data analysis, and software development.
N. Final Portfolio Project
Apply Python and SQL skills to analyze United Nations data. Learn to prepare datasets, perform analysis with Pandas, create visualizations, and present findings in a professional portfolio for future opportunities.
Data Science
C. Exploratory Data Analysis (EDA)
Learn to inspect, clean, and visualize data to uncover insights and test hypotheses. Use Python and EDA libraries like YData Profiling, SweetViz, and Missingno for effective analysis, reinforced through real-world projects.
D. Machine Learning Fundamentals
เสริมสร้างพื้นฐานด้าน Machine Learning ตั้งแต่การเตรียมข้อมูลจนถึงการสร้างและประเมินโมเดลแบบมีผู้สอนและไม่มีผู้สอน ฝึกฝนผ่านไลบรารี Python และโปรเจกต์จริงเพื่อประยุกต์ใช้เทคนิค ML ได้อย่างมีประสิทธิภาพ
E. Sampling Strategy and Model Evaluation
Learn data sampling techniques like Stratified and Cluster sampling, and handle imbalanced datasets with methods like SMOTE. Master model evaluation metrics, including Confusion Matrix, Precision, Recall, F1-Score, ROC, and AUC, for effective data analysis.
F. Introduction to Classification and KNN Algorithm
Explore the basics of classification and the K-Nearest Neighbors (KNN) algorithm. Learn to implement KNN in Python, optimize parameters, and solve real-world data classification problems with confidence.
G. Decision Trees
Master Decision Trees for classification and regression through concepts like Entropy, Information Gain, and Pruning. Apply these techniques with real-world case studies and hands-on practice to build and evaluate effective models confidently.
H. Data Science Portfolio Project I
Enhance data handling expertise through EDA, sampling strategies, and applying KNN and Decision Tree algorithms. Learn to build predictive models and evaluate performance using Precision, Recall, and F1-score for professional-level projects.
I. Random Forests and SVM
Learn to apply Random Forests and Support Vector Machines (SVM) for data analysis. Master feature importance, parameter tuning, and performance evaluation through Python libraries, hands-on demos, and real-world projects.
J. Linear and Logistic Regression
Master Linear and Logistic Regression for predictive modeling and data analysis. Learn to build, interpret, and optimize models for real-world applications, including handling imbalanced data and feature selection.
K. Naive Bayes
Learn the principles and applications of Naive Bayes Classifier, including Multinomial Naive Bayes and Bayesian Networks. Master feature selection, parameter tuning, and handling imbalanced data for efficient real-world classification tasks.
L. Computer Vision
Gain foundational skills in digital image processing and analysis with tools like OpenCV and TensorFlow. Learn techniques like edge detection, object detection, and CNN-based deep learning through hands-on projects and real-world applications.
Data Engineering
A. Introduction to Azure Cloud Computing
Learn the basics of Microsoft Azure, including resource management, SQL database setup, and cost optimization. Gain hands-on experience in Azure Portal and apply real-world cloud solutions with expert guidance.
D. Azure Data Lake
Master data management with Azure Data Lake, focusing on architecture, access control, and Active Directory integration. Learn setup, data analysis tools, and security best practices through comprehensive demos and real-world examples.
E. Azure NoSQL & Cosmos & Databricks
Learn the fundamentals of cloud computing with Microsoft Azure, including resource management, access control, and SQL database configuration. Gain hands-on experience in data storage, geographic replication, and cost optimization with expert guidance.
F. Introduction to Google Certified Professional Data Engineer
Understand the role of a Data Engineer and prepare for the Google Certified Professional Data Engineer exam. Learn to manage batch and streaming data, use GCP services, and build efficient, secure data systems with hands-on practice.
G. GCP Storage Product
Master GCP storage fundamentals, including storage classes, data transfer, and database concepts like scalability, availability, and durability. Learn efficient data management, OLTP vs. OLAP, and storage access setup for effective cloud solutions.
I. AWS Data Engineering Fundamentals
Learn data engineering essentials on AWS, covering Data Warehouses, Data Lakes, ETL pipelines, and database optimization. Gain expertise in Amazon S3 security, versioning, replication, and lifecycle management for efficient big data handling.
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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
Graduates of our bootcamp programs do not receive an accredited degree. We recommend learners interested in pursuing a globally accredited degree to consider enrolling in our Master's Degree program.
WeStride Institute of Technology's graduate 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 graduate and undergraduate 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
Difference Between 10 and 12 Months
There is no difference in the program itself; the variation simply accommodates individual preferences. Some students choose the 12-month option to allow more time for studying, often due to work commitments, planned holidays, or personal schedules.
Tax Benefits
Frequently Asked Questions
What Career Can I Pursue After the Data Science, Analytics, and Engineering Bootcamp?
Completing a Data Science, Analytics, and Engineering Bootcamp prepares you for a variety of high-demand roles in the data-driven tech industry. Here are some career paths you can pursue:
- Data Scientist: Analyze complex datasets to extract insights, build predictive models, and solve business problems using statistical and machine learning techniques.
- Data Analyst: Interpret data and provide actionable insights to support decision-making through visualization and reporting.
- Machine Learning Engineer: Design, build, and deploy machine learning models and systems for real-world applications.
- Data Engineer: Develop and optimize data pipelines, databases, and infrastructure to handle large-scale data processing.
- Business Intelligence (BI) Analyst: Use data tools and techniques to help organizations make strategic business decisions.
- AI Specialist: Focus on creating intelligent systems using advanced AI methodologies and algorithms.
- Quantitative Analyst: Apply mathematical and statistical techniques to solve financial or operational problems.
- Big Data Engineer: Handle massive datasets using technologies like Hadoop and Spark to enable efficient analysis and processing.
- Research Scientist: Work on advanced research projects in AI, machine learning, and data science to push the boundaries of innovation.
- Data Product Manager: Oversee data-centric products and ensure their development aligns with business goals and user needs.
With these skills, you’ll have the opportunity to make a significant impact in industries such as finance, healthcare, e-commerce, technology, and beyond. Your bootcamp training will position you as a competitive candidate in the fast-growing field of data science and engineering.
What Language Is the Program Taught In?
This program is offered in two options: it can be taught in either Thai or English, depending on your preference.
Who Will Be My Personal Mentor?
Your personal mentor will be an experienced industry practitioner carefully selected to support your learning journey. We pair you with a mentor based on their expertise, your specific learning goals, and practical factors such as time zone compatibility. This ensures personalized guidance that aligns with your career aspirations and schedule. Our mentors bring real-world knowledge to help you succeed in your chosen field.
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.
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.