Credit Program of Scientific Computation
With the rise of AI and big data in many industries, the world now needs more people who are good at math and statistics than ever before. From social media to finance, companies are looking for top math talent. To follow this trend, National Taiwan Normal University (NTNU) has started the Scientific Computing Program, led by the Department of Mathematics.
Scientific computing is a method that combines science and technology. It uses both math and computers to solve real-world problems. The goal of this program is to train people who can use scientific computing in different fields, and to support learning across different areas. Based on knowledge in both math and computers, this program helps students build two main skills: using math ideas in computer programs, and writing programs to solve math problems.
Students can take courses in scientific computing and related subjects, such as scientific computing, symbolic computation, image science, and algorithms. After finishing the program, students will have the skills, knowledge, and experience needed to work in jobs related to scientific computing.
Planning and Vision
By observing future trends and drawing on the strengths of current faculty and industry experts, we designed courses that offer the most value to the younger generation.
Discussion and Trial
We developed courses in the four main areas of scientific computing, held discussions with industry professionals, and trialed selected courses to gather valuable insights from teaching practices and student feedback.
Adjustment and Development
We reached a consensus among teachers, students, and industry partners, and adjusted the courses to better meet everyone’s needs. We also built supportive learning measures within the university.
Operation and Innovation
We aim to train students to become professionals needed by tech companies. The program continues to improve and innovate, staying connected to the future.
Industry proposes talent needs and collaborates with universities by offering practical experience and professional consultation. Industry experts are invited to give talks on campus, broadening students’ horizons.
Faculty members integrate theory with industry practices, cultivating students’ mathematical competence and enabling them to approach real-world challenges from a high-level mathematical perspective and solve problems using the knowledge acquired in class.
After completing the courses, students are capable of taking on responsibilities in the industry. They can analyze and organize practical problems with mathematical thinking, becoming mathematics professionals who meet industry demands amid future technological trends.
Guidelines for the Scientific Computing Credit Program at National Taiwan Normal University
Approved at the 1st Academic Affairs Meeting of the 2019 Academic Year on October 30, 2019
Approved at the 1st Academic Affairs Meeting of the 2023 Academic Year on November 1, 2023
Symbolic Computations
Combining number theory, algebra, and program design, focusing on solving practical problems using mathematical and algebraic algorithms, and exploring modern cryptographic issues.
Scientific Computation
Combining traditional linear algebra and numerical analysis with programming, this course cultivates the ability to perform large-scale matrix computations.
Imaging Science
Starting from perspectives such as linear algebra and differential geometry, this course interprets the construction and computation of computer graphics and image animation using modern theoretical tools.
Algorithm
Introducing classic mathematical puzzles and logic problems from history and literature. With educational resources in our department, we explore algorithm design and introduce AI topics.
Data Science
Integrating scientific computation, numerical optimization, and statistical methods to develop the ability for data analysis and modeling.
★ It is recommended that students complete “Linear Algebra (I)” and “Linear Algebra (II)” offered by this department before enrolling in this program.
Scientific Computing Credit Program, Course Requirements, National Taiwan Normal University
Approved by the 1st University Curriculum Committee of Academic Year 2019, October 30, 2019
Approved by the 1st University Curriculum Committee of Academic Year 2022, November 2, 2022
Approved by the 1st University Curriculum Committee of Academic Year 2023, November 1, 2023
I. Required Courses: 6 credits total
|
Course Code |
Course Name |
Credits |
Offering Department |
Remarks |
|
MAU0032 |
Computer Programming |
3 |
Department of Mathematics |
Department of Electrical Engineering AEU0013 Computer Programming Department of Mechatronic Engineering MTU0012 Computer Programming Department of Industrial Education IEU0119 Computer Programming Undergraduate Program of Vehicle and Energy Engineering VEU0017 Computer Programming Department of Computer Science and Information Engineering CSU0001 Computer Programming (I) Undergraduate Program of Learning Sciences LSU0001 Programming (I) Department of Technology Application and Human Resource Development ITU0127 Programming Language The above courses may be recognized as equivalent to this course. For other programming-related courses, please contact the Department of Mathematics office directly. |
|
MAC9029 |
Introduction to Scientific Computation |
3 |
Department of Mathematics |
Numerical Analysis may be recognized as equivalent to this course. |
2. Elective Courses: Minimum 6 credits required
|
Field |
Course Code |
Course Name |
Credits |
Offering Department |
Remarks |
|
Symbolic Computations |
MAC9016 |
Cryptography |
3 |
Department of Mathematics |
Combined Undergraduate and Graduate Course |
|
MAC9017 |
Cryptography |
3 |
Department of Mathematics |
Combined Undergraduate and Graduate Course |
|
|
MAC9018 |
Computational Number Theory and Algebra |
3 |
Department of Mathematics |
Combined Undergraduate and Graduate Course |
|
|
High-Performance Computing |
MAC9030 |
Special Topics on Scientific Computation |
3 |
Department of Mathematics |
Combined Undergraduate and Graduate Course |
|
MAC9035 |
Matrix Computation (I) |
3 |
Department of Mathematics |
Combined Undergraduate and Graduate Course |
|
|
MAC9044 |
Quantum Computation and Quantum Information (I) |
3 |
Department of Mathematics |
Combined Undergraduate and Graduate Course |
|
|
Imaging Science |
MAC9020 |
Computational Conformal Geometry (I) |
3 |
Department of Mathematics |
Combined Undergraduate and Graduate Course |
|
MAC9021 |
Computational Conformal Geometry (II) |
3 |
Department of Mathematics |
Combined Undergraduate and Graduate Course |
|
|
MAC9022 |
Image Processing and Analysis (I) |
3 |
Department of Mathematics |
Combined Undergraduate and Graduate Course |
|
|
MAC9023 |
Image Processing and Analysis (II) |
3 |
Department of Mathematics |
Combined Undergraduate and Graduate Course |
|
|
MAC9024 |
Mathematics of Motion and Deformation in Computer Graphics |
3 |
Department of Mathematics |
Combined Undergraduate and Graduate Course |
|
|
Algorithm |
MAC9019 |
Mathematical Games and Algorithms |
3 |
Department of Mathematics |
Combined Undergraduate and Graduate Course |
|
MAC9031 |
Combinatorial Designs |
3 |
Department of Mathematics |
Combined Undergraduate and Graduate Course |
|
|
Data Science |
MAC9048 |
Scientific Computing in Data Science |
3 |
Department of Mathematics |
Combined Undergraduate and Graduate Course |
|
MAC9049 |
Numerical Optimization in Data Science |
3 |
Department of Mathematics |
Combined Undergraduate and Graduate Course |
|
|
MAC0117 |
Statistical Computing (I) |
3 |
Department of Mathematics |
Combined Undergraduate and Graduate Course |
|
|
MAC8021 |
Cluster Analysis (I) |
3 |
Department of Mathematics |
Combined Master’s and Doctoral Course |