人工智慧概論與計算機程式
臺北科技大學 115-1 學期課程,課號 362882。
- 學期:115-1
- 授課教師:李旻璁
- 學分:2
- 必修
- 上課時段:週一 5、6、7 節
課程大綱
This course focuses on understanding the algorithms behind programming solutions rather than the syntax of any specific programming language. Students will learn how to conceptualize, develop, and implement algorithms to solve engineering problems using a dual-language approach. Fortran will be used to introduce algorithmic fundamentals, while Python—generated and explored through ChatGPT—will demonstrate how logical structures can be adapted across languages. A key emphasis of this course is cultivating literacy in using Generative AI tools, especially ChatGPT, for programming. Students will learn how to prompt ChatGPT effectively, interpret and critique AI-generated code, and use it as a tool to accelerate their understanding of computational thinking. The course aims to empower students to confidently build adaptable, reliable solutions for engineering applications, especially those involving data analysis, simulation, and visualization.
課程進度
Part I: Foundations and Tools (Weeks 1–3) Introduction to programming and ChatGPT as a GenAI assistant Basic Linux operations, shell usage, and the vim editor Setting up compilers and interpreters; visualization with gnuplot Role of spreadsheets (Excel) in conceptual planning Part II: Programming Concepts with Fortran (Weeks 4–10) Input/Output (I/O) fundamentals Variable declaration and data types Mathematical operations and built-in functions Control structures: loops (do), conditionals (if) File operations and array handling Subroutines and modules Introduction to random number generation * During these sessions, Python equivalents will be generated using ChatGPT to reinforce the portability of algorithmic thinking. Part III: Applied Algorithms and Visualization (Weeks 11–16) Sorting algorithms and data organization Statistical analysis and data interpretation Probability functions and histogram plotting Regression modeling and trend analysis Generating random walk trajectories and visualizing with VMD Simulating self-assembly and analyzing aggregate structures
評量方式
Class Participation (Zuvio attendance and Q&A) 40% In-Class Exercises (hands-on programming tasks) 40% Final Project Report (individual or group-based) 20% There are no midterm or final exams. Attendance is mandatory, and students are expected to actively participate in in-class discussions and exercises.
教材
【遵守智慧財產權觀念,請使用正版教科書,不得使用非法影印教科書】 使用外文原文書:否 Instructor-prepared materials will be used throughout the course.