Curriculum · Current curriculum For students admitted from 2024

Bachelor of Science Program in Data Science (2567)

Bachelor of Science (Data Science) · B.S. (Data Science)

  • 137credits in total
  • 4years8 semesters
  • 3elective tracks
  • 77courses in the curriculum

Admission Study plan

Admitted earlier? See Bachelor of Science Program in Data Science (2562)

Overview

The program prepares graduates to manage, analyze and model data with mathematics, statistics and computing.

In the first years, students take foundations such as calculus, probability and statistics, and programming for data science, followed by major courses such as database management, data manipulation, statistical learning and machine learning. They then choose one of three elective tracks and spend a semester of the fourth year in cooperative education.

Elective tracks

  • Data analytics using mathematical modeling
  • Statistical data analytics
  • Data analytics using computational modeling

Curriculum structure

At least 137 credits in total

  • General Education 30
  • Core Courses 27
  • Major 59
  • Minor (if any) 15
  • Free Electives 6

General Education

30 credits

  • Required Courses 21
  • GE Electives 9

Core Courses

27 credits

  • Basic Courses for Data Science 21
  • Basic Science Courses 6

Major

59 credits

  • Compulsory Courses 35
  • Major Elective Courses 24

Minor (if any)

15 credits

Free Electives

6 credits

Courses

Open a category to see its courses · credits (lecture-practice-self-study hours)

General Education30 credits

Required Courses 21 credits

Learner Person 15 credits

  • 001101Fundamental English 13(3-0-6)
  • 001102Fundamental English 23(3-0-6)
  • 001201Critical Reading and Effective Writing3(3-0-6)
  • 001225English in Science and Technology Context3(3-0-6)
  • 204100Information Technology and Modern Life3(3-0-6)

Innovative Co-creator 3 credits

  • 201190Critical Thinking, Problem Solving and Science Communication3(3-0-6)

Active Citizen 3 credits

  • 140104Citizenship3(3-0-6)

GE Electives 9 credits

A student also chooses at least 9 credits from these 3 groups of GE courses.

Learner Person

  • 057137Sports for Health3(3-0-6)
  • 701181Basic Accounting for Entrepreneurs3(3-0-6)
  • 702101Finance for Daily Life3(3-0-6)
  • 851100Introduction to Communication3(3-0-6)

Innovative Co-creator

  • 176100Law and Modern World3(3-0-6)
  • 201114Environmental Science in Today’s World3(3-0-6)
  • 703103Introduction to Entrepreneurship and Business3(3-0-6)
  • 851103Life and Society through Media3(3-0-6)

Active Citizen

  • 201111The World of Science3(3-0-6)
  • 951100Modern Life and Animation3(3-0-6)
Core Courses27 credits

Basic Courses for Data Science 21 credits

  • 204252Data Structures and Analysis3(3-0-6)
  • 206111Calculus 13(3-0-6)
  • 206112Calculus 23(3-0-6)
  • 206281Discrete Mathematics3(3-0-6)
  • 208150Probability and Statistics3(3-0-6)
  • 229123Fundamental Concept of Data Science3(3-0-6)
  • 229223Programming for Data Science3(2-2-5)

Basic Science Courses 6 credits

Select from the following courses:

  • 202101Basic Biology 13(3-0-6)
  • 203103General Chemistry 13(3-0-6)
  • 207187Physics 13(3-0-6)
Major59 credits

Among the credits earned from major courses taken, a minimum of 36 credits must be from the advanced level courses (300-400), and of which at least 18 credits must be from the 400 level courses.

Compulsory Courses 35 credits

  • 204217Computer Programming Languages3(2-2-5)
  • 204306Ethics for Computer Professionals1(1-0-2)
  • 204320Database Management3(2-2-5)
  • 204371Feature Engineering3(2-2-5)
  • 204456Machine Learning3(3-0-6)
  • 206324Applied Linear Algebra3(3-0-6)
  • or206325Linear Algebra3(3-0-6)
  • 208250Statistical Methods for Data Science3(2-2-5)
  • 229323Data Manipulation for Data Science3(2-2-5)
  • 229351Statistical Learning for Data Science 13(2-2-5)
  • 229352Statistical Learning for Data Science 23(2-2-5)
  • 229490Seminar1(1-0-2)
  • 229496Cooperative Education6

Major Elective Courses 24 credits

Register courses from one of the following groups with 18 credits:

Group: Data analytics using mathematical modeling

  • 204426Data Engineering3(2-2-5)
  • 204471Artificial Intelligence3(3-0-6)
  • 206300Mathematics of Finance and Insurance3(3-0-6)
  • 206341Differential Equations3(3-0-6)
  • 206358Mathematics for Data Science3(3-0-6)
  • 206465Principles of Mathematical Modeling3(3-0-6)

Group: Statistical data analytics

  • 204453Pattern Recognition3(2-2-5)
  • 208350Applied Multivariate Statistics for Data Science3(3-0-6)
  • 208354Time Series Analysis for Data Science3(2-2-5)
  • 208424Optimization for Statistical Learning3(3-0-6)
  • 208450Analytics for Observational Data3(3-0-6)

Select courses from the following with 3 credits:

  • 204422Data Warehousing3(2-2-5)
  • 204471Artificial Intelligence3(3-0-6)

Group: Data analytics using computational modeling

  • 204383Image Processing3(3-0-6)
  • 204422Data Warehousing3(2-2-5)
  • 204426Data Engineering3(2-2-5)
  • 204471Artificial Intelligence3(3-0-6)
  • 204472Natural Language Processing3(3-0-6)

Select courses from the following with 3 credits:

  • 204423Data Mining3(3-0-6)
  • 204453Pattern Recognition3(2-2-5)

Select courses from the following with at least 6 credits:

  • 204381Numerical Computation and Software3(3-0-6)
  • 204383Image Processing3(3-0-6)
  • 204422Data Warehousing3(2-2-5)
  • 204423Data Mining3(3-0-6)
  • 204424Ontology Design and Development3(3-0-6)
  • 204426Data Engineering3(2-2-5)
  • 204453Pattern Recognition3(2-2-5)
  • 204471Artificial Intelligence3(3-0-6)
  • 204482Simulation and Modelling3(3-0-6)
  • 204483Computer Vision3(3-0-6)
  • 206300Mathematics of Finance and Insurance3(3-0-6)
  • 206341Differential Equations3(3-0-6)
  • 206355Numerical Method3(3-0-6)
  • 206357Scientific Computation3(2-3-4)
  • 206358Mathematics for Data Science3(3-0-6)
  • 206370Probability 13(3-0-6)
  • 206441Nonlinear Ordinary Differential Equations3(3-0-6)
  • 206457Mathematics of Financial Derivatives3(3-0-6)
  • 206465Principles of Mathematical Modeling3(3-0-6)
  • 206467Neural Networks3(3-0-6)
  • 206470Probability 23(3-0-6)
  • 206471Introduction to Actuarial Mathematics3(3-0-6)
  • 208251Regression Analysis and Non-parametric Statistics3(2-2-5)
  • 208350Applied Multivariate Statistics for Data Science3(3-0-6)
  • 208354Time Series Analysis for Data Science3(2-2-5)
  • 208424Optimization for Statistical Learning3(3-0-6)
  • 208450Analytics for Observational Data3(3-0-6)
  • 208451Analytics for Experimental and Simulated Data3(2-2-5)
  • 208453Statistics for Finance and Investment3(3-0-6)
  • 208454Actuarial Modeling3(2-2-5)
  • 229452Research in Data Science3(0-9-0)
  • 229471Data Analytics in Medicine3(2-2-5)
  • 261441Internet of Things and Big Data3(3-0-6)
  • 261461Visual and Interactive Programming3(3-0-6)
  • 954471Business Data Mining3(2-2-5)
  • 954472Business Data Visualization3(2-2-5)
Minor (if any)15 credits

2.3.1 Students who wish to have minor is required to register at least 15 credits and may take courses choosing from minor in general Business Administration, Economics, or any minor being offered by science faculty ( except minor in Data Science, Mathematics, Computer Science, and Statistics). Furthermore, student may choose any minor courses corresponding to minor listed in the Chiang Mai University announcement about minor offered for CMU students with approval of an academic advisor.

2.3.2 For those who do not wish to have a minor, it is required that a minimum of 15 credits from major elective courses at 300 or 400 level must be chosen.

Free Electives6 credits

The curriculum lists no particular courses here.

Study plan

The recommended courses for each semester. Items in italics are courses the student chooses.

First Year

First Semester

  • 001101Fundamental English 13
  • 206111Calculus 13
  • 208150Probability and Statistics3
  • 229123Fundamental Concept of Data Science3
  • 229223Programming for Data Science3
  • Basic Science3

Total18 credits

Second Semester

  • 001102Fundamental English 23
  • 140104Citizenship3
  • 206112Calculus 23
  • 204100Information Technology and Modern Life3
  • 204217Computer Programming Languages3
  • 208250Statistical Methods for Data Science3
  • Basic Science3

Total21 credits

Second Year

First Semester

  • 001225English for Science and Technology3
  • 201190Critical Thinking, Problem Solving and Science Communication3
  • 204320Database Management3
  • 206281Discrete Mathematics3
  • 229323Data Manipulation for Data Science3
  • 229351Statistical Learning for Data Science 13
  • General Education Electives3

Total21 credits

Second Semester

  • 001201Critical Reading and Effective Writing3
  • 204252Data Structures and Analysis3
  • 206324Applied Linear Algebra3
  • or206325Linear Algebra3
  • 229352Statistical Learning for Data Science 23
  • Major Electives3
  • Minor or Major Electives3

Total18 credits

Third Year

First Semester

  • 204371Feature Engineering3
  • Major Electives9
  • Minor or Major Electives3
  • Free Electives3

Total18 credits

Second Semester

  • 204306Ethics for Computer Professionals1
  • 204456Machine Learning3
  • Major Electives6
  • Minor or Major Electives6
  • Free Electives3

Total19 credits

Fourth Year

First Semester

  • 229496Cooperative Education6

Total6 credits

Second Semester

  • 229490Seminar1
  • General Education Electives6
  • Major Electives6
  • Minor or Major Electives3

Total16 credits

Admission

Admission is through Chiang Mai University's TCAS rounds. See the university's announcements for the rounds, requirements and dates.

Curriculum structure, courses and study plan from Chiang Mai University's TQF2 system (retrieved 11 October 2026)

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