Global Technology and Innovation Management (GTIM)

The ecosystem of innovation and technology in Asian and global context underscore the importance of data analysis for decision making. Data sciences connects the web of knowledge across disciplines that construe a real-time portrait of the world containing diversities and individualities. The track curriculum of GTIM thus serves as the gateway to advanced data analysis courses, complementing the foundational knowledge of other track courses for application and trainings. Our goal is to cultivate professionals using Data Analytics & Artificial Intelligence on social analysis and organizational management for innovative developments in the industry.

GTIM Capstone Projects/ Specialized Research

Business Data Analytics

This course is an introduction and practice for data analysis for social analysis. In recent years, the application of Big Data has become an important trend in almost every field. This course employs a project-driven strategy that students are able to follow the instructors’ steps about how a data project is developed and how to use R programming to finish a project.

There are three sections in this course. The first is the statistics section which focuses on the basic statistical knowledge for data analysis. The second section is to use Kaohsiung city pollution data project to teach R programming’s basic coding skills in 5 weeks. The third section will introduce an advanced data project every week. You are required to develop a research project with your teammates by end of the course. Lastly, this course is designed to provide you with the basic ability to become a member of a professional data analysis team.

Computer Programming (I)

This course is an introductory level of Python programming language. We start this course by introducing Google Colaboratory, a platform which runs on the cloud and offers free computing resources, will be introduced as your code playground in this course. Then, basic Python syntaxes will be introduced. To provide a better understanding, some examples or assignments will be given. Students need to find an issue to address and solve it using Python as your term-project. A final report about this issue and how you solve it should be submitted at the end of the semester.

Big Data for Social Analysis

This course is an introduction and practice for data analysis for social analysis. In recent years, the application of Big Data has become an important trend in almost every field. This course employs a project-driven strategy that students are able to follow the instructors’ steps about how a data project is developed and how to use R programming to finish a project.

There are three sections in this course. The first is the statistics section which focuses on the basic statistical knowledge for data analysis. The second section is to use Kaohsiung city pollution data project to teach R programming’s basic coding skills in 5 weeks. The third section will introduce an advanced data project every week. You are required to develop a research project with your teammates by end of the course. Lastly, this course is designed to provide you with the basic ability to become a member of a professional data analysis team.

AI & Ethics

Artificial intelligence (AI) is developing at an rapid pace. We should expect to see significant changes in our daily lives. This course will cover legal and philosophical issues raised by AI systems. Questions we consider include:

  1. Who is responsible when AI causes suffering?
  2. Do we have to give up privacy to get technological innovation?
  3. How can bias in algorithms be prevented?
  4. What can we do to make AI more ethical?
  5. How will society respond as versatile robots and machine-learning systems displace an ever-expanding spectrum of blue- and white-collar workers?
  6. Will the benefits of this technological revolution be broadly distributed or accrue to a lucky few?
  7. How can we ensure that these systems respect our ethical principles when they make decisions at speeds and for rationales that exceed our ability to comprehend?
  8. What, if any, legal rights and responsibilities should we grant them?

Should we regard them merely as sophisticated tools or as a newly emerging form of life?

AI & Governance

Recent advances in computing may place us at the threshold of a unique turning point in human history. Soon we are likely to entrust management of our environment, economy, security, infrastructure, food production, healthcare, and to a large degree even our personal activities, to artificially intelligent computer systems.

The prospect of “turning over the keys” to increasingly autonomous systems raises many complex and troubling questions. How will society respond as versatile robots and machine-learning systems displace an ever-expanding spectrum of blue- and white-collar workers? Will the benefits of this technological revolution be broadly distributed or accrue to a lucky few? How can we ensure that these systems respect our ethical principles when they make decisions at speeds and for rationales that exceed our ability to comprehend? What, if any, legal rights and responsibilities should we grant them? And should we regard them merely as sophisticated tools or as a newly emerging form of life?

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