| Course Name |
(中) 生命科學家的程式設計入門(2231) |
| (Eng.) An Introduction to Programming for Life Scientists |
| Offering Dept |
Department of Life Sciences |
| Course Type |
Elective |
Credits |
2 |
Teacher |
HSIEH,LI-CHING |
| Department |
Department of Life Sciences/Undergraduate |
Language |
English |
Semester |
2025-FALL |
| Course Description |
(中) 這是針對生命科學領域學生開設的 Python 程式設計入門課程。本課程旨在培養學生跨領域解決問題的能力，透過計算機與程式語言的運用，使他們能夠更有效地應對日益數位化與資訊化的生命科學領域。課程涵蓋 Python 基礎語法、科學運算、資料處理、機器學習等，並導入相關套件與工具。學生將獲得實際應用經驗，建立以電腦解決問題的思維，並具備銜接統計、生物資訊等進階課程的能力。
(Eng.) This is an introductory Python programming course designed for students in the field of life sciences. The course aims to cultivate students' interdisciplinary problem-solving skills by utilizing computers and programming languages, enabling them to cope more effectively with the increasingly digitized and information-driven landscape of life sciences. The course covers Python fundamentals, scientific computing, data processing, machine learning, and introduces relevant packages and tools. Students will gain practical application experience, develop a mindset for problem-solving using computers, and acquire the ability to transition to advanced courses such as statistics and bioinformatics. |
| Prerequisites |
|
self-directed learning in the course |
Y |
| Relevance of Course Objectives and Core Learning Outcomes(%) |
Teaching and Assessment Methods for Course Objectives |
| Course Objectives |
Competency Indicators |
Ratio(%) |
Teaching Methods |
Assessment Methods |
(中) 培養學生跨領域解決問題的能力，透過計算機與程式語言的運用，使他們能夠更有效地應對日益數位化與資訊化的生命科學領域。
(Eng.) The goal of this course is to cultivate students' ability to solve problems across disciplines through the use of computers and programming languages, enabling them to more effectively navigate the increasingly digital and information-driven field of life sciences. |
| 1.The knowledge of basic science and basic life science |
| 3.The training of the ability of expression and the logics of thinking. |
|
|
| topic Discussion/Production |
| Discussion |
| Exercises |
| Lecturing |
|
| Study Outcome |
| Oral Presentation |
| Assignment |
|
| Course Content and Homework/Schedule/Tests Schedule |
| Week |
Course Content |
| Week 1 |
Course Introduction
課程簡介 |
| Week 2 |
Instruction to Python
Python 語言簡介 |
| Week 3 |
Python language essentials (Variables, expressions and statements)
Python 語言基礎（變數、表達式和語句） |
| Week 4 |
Python language essentials (Conditional Execution)
Python 語言基礎（條件執行） |
| Week 5 |
Python language essentials (Functions)
Python 語言基礎（函數） |
| Week 6 |
Python language essentials (Loops and Iterations)
Python 語言基礎（迴圈和迭代） |
| Week 7 |
Python language essentials (Strings)
Python 語言基礎（字串） |
| Week 8 |
Python language essentials (Files)
Python 語言基礎（檔案） |
| Week 9 |
Python language essentials (Tuples and Lists)
Python 語言基礎（元組和串列） |
| Week 10 |
Python language essentials (Dictionaries and Sets)
Python 語言基礎（字典和集合） |
| Week 11 |
Midterm report
期中報告 |
| Week 12 |
Data Processing and Analysis I
資料處理與分析 I |
| Week 13 |
Data Processing and Analysis II
資料處理與分析 II |
| Week 14 |
Machine Learning I
機器學習 I |
| Week 15 |
Machine Learning II
機器學習 II |
| Week 16 |
Final report
期末報告 |
self-directed
learning |
03.Preparing presentations or reports related to industry and academia.
|
|
| Evaluation |
作業: 50%，課中討論：10%，期末報告: 40%
Homework: 60%, Discussion: 10%, Final report: 30% |
| Textbook & other References |
| Python for Everybody by Charles Severance (2016) |
| Teaching Aids & Teacher's Website |
置於 iLearning
Put in iLearning |
| Office Hours |
(四) 789
(Thur.) 789 |
| Sustainable Development Goals, SDGs(Link URL) |
| include experience courses：N |
|