View count: 15822

Course Information

邏輯組課程介紹-英文20260714

 
Course Introduction
Foundation Computational Thinking and Programming Using information technologies to solve problems is an important skill in today's workplace. High-level workers often need to design a series of instructions to use information tools or make information equipment operate automatically according to needs. To have this ability, you need to have a good "computational thinking". Through group unplugged activities, this course will learn how to apply computational thinking to solve problems (without the use of information equipment), and then learn basic program/command design skills through visual programming tools. Finally, let group make multimedia project, to make sure they can apply "computational thinking skill". Those who complete this course will have the foundation to develop information application software (such as APP application software) and information application system (such as the Internet of Things).
Information Technology and Contemporary Issues Technology is woven into everything we do today, both at work and in our daily lives. To help our students thrive in this digital era, boost their productivity, and stay ahead in the job market, this course is designed to elevate their digital literacy and tech-savviness.

Through six core themes, students won't just pick up the latest, most practical tech skills—they'll also sharpen high-level abilities like teamwork, logical analysis, and critical thinking. Ultimately, they’ll learn how to leverage technology to solve real-world problems and drive social progress, perfectly aligning with our university's vision of fostering well-rounded, master-level talent.
Information
Technology		 Data Science and Computer Programming Through a series of data analytics real life applications, the course aims to equip students with the ability to collect, cleanse, analyze, and present data in an effective manner, which is important as the Big Data Era has come to be. The course covers control flow, common data structures, string processing, file processing, functional programing, data visualization, web scraping, and data analysis.
Game Programming and AI-Assisted Development We’ve designed this course for students looking to break into programming. It's a hands-on deep dive into computational thinking and game development. By leveraging an interpreted Java environment with real-time visualization, we’re removing the usual coding barriers. Students can see their results instantly, making it far easier to master core programming skills under expert guidance. The ultimate payoff? Every student will leave this course with the skills to independently drive and deliver a complete game project.
Mobile App Development This course aims to teach students to develop mobile applications through MIT App Inventor, a visual programming language. Students who intend to enroll in this course are suggested to have basic programming skills and know basic programming concepts such as variables, selection, and loops. (Those who need to learn basic programming skills are encouraged to enroll in another general education course - "Computational Thinking and Programming".)
Advanced Applications of Spreadsheets and Program This course teaches how to use EXCEL functions and VBA programming to solve practical problems in life.
Algorithms in Daily Lives In this course, we introduce the algorithms that one may encounter in daily lives. We will get an insight of each algorithm through implementation. 
Big Data Programming Python is an easy-to-learn, powerful programming language. It has a high-performance data structure and a simple and effective way to implement object-oriented programming.
Python is widely used for big data analysis. This course covers the basics of Python, including basic data types (numbers, strings), input and output, procedural control, function definitions, and data structures such as lists, tuples, dictionaries, collections, modules, classes and objects, inheritance, the Python standard library, and error and exception handling.
Finally, we will cover how to use Python for big data processing, including data extraction and analysis, data normalization, data visualization, and data storage and reading. Theoretical courses are combined with hands-on programming to develop students' programming logic and problem-solving skills.
Learning Analytics Tools Implementation Applications This course is a preparatory course to meet the practical course requirements, which enables students to understand how to use cloud technology, digital tools, and programming languages to develop application software, familiarize themselves with the tools and cloud platforms needed in the before during, and after stages of application software development, and use Microsoft Azure cloud big data technology to implement educational extensive data analysis. The learning results of data analysis will be used to conduct feasibility product development training.
Introduction to Web Programming This course starts with an introduction to web design and website operation, and primarily focuses on learning JavaScript programming language. The course aims to train students to acquire the fundamental programming skills required for front-end web development.
Structured Query Language (SQL) and Database Design In today's information-driven society, the processing and utilization of big data have become essential components of the workforce. Therefore, developing data processing skills and proficiency in information tool applications will be vital skills for the future. This course is an extension of "Advanced Applications of Spreadsheets and Programming" and "Advanced Spreadsheet Tools for Business Analysis" allowing students who are interested in learning about big data analysis to delve into database applications.
This course will use the Microsoft Office suite, specifically MS Access, as the primary focus of instruction and learning. In addition to mastering data processing and application techniques, students will also gain a conceptual understanding of relational databases. They will learn Structured Query Language (SQL) for database structure and querying. This knowledge will enable them to efficiently manage large volumes of data in the future, using structured database tools for data operations. This data can then be accessed for value-added applications on other information platforms or big data analysis tools.
Introduction to Python Programming with AI In this course, we will use the Python programming language to learn fundamental programming concepts. Unlike traditional programming courses, this course is supported by AI Vibe Coding, which allows students to learn programming logic more effectively while also quickly enjoying the sense of achievement that comes from seeing their programming results.
Interdisciplinary Applications Scientific Computing Scientific computing is a multidisciplinary field that solves problems with computers. The problems usually arise from mathematics, biology, physics, chemistry and so on. This course provides an introduction to basic python programming concepts and the techniques that can be used to solve scientific problems by modeling. 
Textual Data Analysis This course uses Python3 programming language to serve the purpose of Chinese Text Processing. It is designed for students with basic programming ability and interests in learning linguistic and text processing.
Toolkits such as Jieba, CKIPTagger, Articut NLP system and NLTK will be introduced in this course. Besides, all assignments are given with reference of real-world problems instead of toy questions.
Sports Data Analytics and Artificial Intelligence In the era of big data, the ability to use computer software, programming, and artificial intelligence technologies to collect and analyze data—and to further describe, interpret, and effectively present the knowledge embedded within it—has become an essential competency in the 21st century. The field of sports has accumulated a vast and diverse range of data over time, which awaits systematic exploration and application through scientific methods.

This course aims to equip students with the ability to apply data analytics and artificial intelligence techniques to solve problems in the field of sports. The curriculum covers sports data collection, data processing, statistical analysis, machine learning, and the application of generative AI tools. Through these topics, students will gain an understanding of modern sports science, performance analytics, sports industry management, and the development trends of smart sports technologies.

The course is specifically designed for students with no prior programming experience. It welcomes those who are interested in sports, engaged in sports-related fields, and are curious about data analysis and the patterns behind it (with particular encouragement for students from the College of Sports and Leisure).
Advanced Applications of AI-Generated Spreadsheets and Programming With the rapid rise of AI technologies, office professionals are increasingly expected to leverage AI-generated formulas and programming solutions to enhance data processing and workflow automation efficiency. This course covers advanced applications of AI-generated Excel functions, AI-assisted VBA custom function development, and report creation. Through practical, real-world examples, students will learn how to effectively apply AI tools to spreadsheet analysis, automation, and reporting tasks.
Advanced Spreadsheet Tools for Business Analysis In the future, Information Technology ability will be the competitiveness of students in the workplace. Mastering various data processing methods and approaches such as data collection, data cleaning, analysis and application is the key to the road to Big Data. Business Intelligence is also a competitive advantage for businesses.
Therefore, this course starts from the application of data analysis in academic research to the application of data analysis in business. It will provide students with the mastery of various data collection and processing methods from data extraction to data visualization. Also, learn excel advanced applications, PowerPivot, PowerMap, and even PowerBI analysis tools. Let everyone become a data analysis expert.
Introduction to Music AI Programming This course is an introductory programming course designed for students without prior hands-on experience in programming languages. The course centers on music-oriented programming, integrating core concepts and practical applications of commonly used programming languages. Through hands-on activities in music creation and algorithmic thinking, students will develop interdisciplinary computational and creative programming skills.

For the midterm and final projects, students will be guided to engage in music-related programming projects using AI-assisted development workflows and Vibe Coding practices. By collaborating with large language models to design, plan, and debug programs, students will gain an understanding of the role and limitations of artificial intelligence in the programming process. They will also learn how to effectively leverage AI tools in the AI era, completing music programming projects that integrate both creativity and technical implementation.
Music AI Algorithm Design and Sound Synthesis Driven by the growth of the music AI industry and the interdisciplinary development of science, technology, and arts, programming skills related to digital music and sound synthesis have become increasingly important in professional practice. However, the knowledge required in this field spans music, electrical engineering, and computer science, making it challenging for beginners. This course adopts a step-by-step approach to guide students in understanding the programming logic and system design methods required for digital music creation.

To support learning, the course uses ChucK as a tool for sound synthesis and real-time music programming, and Python for MIDI processing, data analysis, and music computation applications.

This course serves as an advanced extension of an introductory programming curriculum and is designed for students with prior hands-on experience in programming languages. The course focuses on music-oriented programming, integrating algorithm design, digital music applications, and creative programming to cultivate students’ ability to solve music-related problems through computational approaches.

The course incorporates concepts and practical applications of generative AI and AI-assisted programming (AI-assisted coding). For the midterm and final projects, students will engage in AI Vibe Coding practices, using large language models to assist in planning, writing, and testing programs to complete music-related projects. In addition to learning technical skills in music programming, students will also develop an understanding of the role, strengths, and limitations of AI tools in creative development workflows.
Biomedical and Health Data Analytics This course introduces the use of health data from wearable devices and patient data from electronic health records (EHR) to explore the potential of data driven personal health management and study the role of data in biomedical research and healthcare systems. The course also covers the very basics of database management, and the extract, transform, load (ETL) techniques. Students without programming concepts are advised to take Computational Thinking and Programming prior to enrolling.
Data Science in Education Research Thepurpose of this courseis to introduce the application of python modules and libraries in data science analysis. This course also introduce different types of educational big data databases to lead students in data exploration as well as to develop the ability in solving practical educational problems.
When Artificial Intelligence Meets Generative Art This course is a Interdisciplinary curriculum ,aiming to guide students to experience art creation , computer programming and various AI through the integration of art , programming and various AI.

 The teacher will inspire students' creative inspiration through the introduction of art styles, and we will use programming and various AI as a medium to lead students to create a variety of works of artistic creation styles, analyze and display the works. During artistic creation, students will learn the basic concepts and skills of programming and various AI.

This course offers students opportunities to appreciate and analyze various artistic creation styles, and experience the process of using programming and various AI as a creative medium. Furthermore, it is designed to inspire students’ creative thinking in interdisciplinary context.
Digital storytelling and learning technologies The objective of this course is to develop students’ ability of digital storytelling so that they can think how to integrate learning technologies and digital storytelling as powerful and engaging products with humanities and cultures. In the future, they can further apply what they learned to educational or commercial creation areas.
Practical Applications of Generative AI In the rapidly evolving landscape of technology, Generative AI stands at the forefront, reshaping how knowledge work is conducted across various industries. This course is designed to equip students with an understanding of the fundamental concepts of Data Science, Machine Learning, Artificial Intelligence, Discriminative AI, and Generative AI, with a focus on language models in the first half, extending to image generation, and further to video and music generation in multimodal formats in the latter half. Through a blend of theoretical knowledge and practical applications, students will learn to navigate the potential of Generative AI in creative content creation, problem-solving, and innovation. The course includes hands-on projects where students will first draft a personalized proposal using related tools, showcasing their unique skills or interests, followed by a final project that involves creating a video utilizing at least two technologies learned during the course. This course aims to provide students with the skills to harness the power of Generative AI, opening up new avenues for future knowledge workers in an AI-driven world.
Data Visualization and Communication This course will focus on data visualization theory, and on this basis, further explore how to use currently popular AI/programming tools such as ChatGPT and Python to clearly interpret data for the audience and communicate effectively as a goal.
Generative AI and Humanities Applications With the widespread adoption of generative AI tools such as ChatGPT and Gemini, the humanities are facing unprecedented opportunities and challenges. Traditional approaches to textual analysis, historical research, and creative practice can all achieve breakthrough innovations through AI technology. However, how to effectively utilize these tools while preserving the core elements of the humanities and creating new possibilities is precisely the essential competency that contemporary liberal arts students must master. This course is not merely technical training, but rather a profound journey of intellectual transformation. The course will guide students to contemplate: How does AI change the way we understand texts? How can we leverage AI for large-scale literature analysis? How can we collaborate with AI in the creative process without losing the human touch that defines the humanities? The exploration of these questions will open new horizons for students in both academic research and career development. This course adopts a "learning by doing" pedagogical philosophy, where every theoretical concept will be verified and deepened through hands-on practice. Furthermore, this course will place special emphasis on cultivating critical thinking. In every AI application practice, students will be guided to consider the limitations of technology, ethical considerations, and the profound implications for the development of humanities disciplines.