Data Science
Data Science with R/Python
An introduction to data management, manipulation, and analysis, with an emphasis on information
science problems. Class consists of short introductions to new concepts followed by hands on
computing exercises using R and SQLite, but the concepts apply to programming languages and
databases more generally. No background in computing is required.
R Programming, Data Visualization, SQLite
Note: A similar course will be implemented using Python language
IT/IS/CS
Information Systems Using Shell & SQL
Undergraduate
Spring 2018 ~ present
This course sits at the intersection of IT (information technology) and IT services/management,
introduces students across stages in their programs to topics that connect their information
systems skills and the management of information technology services. Half of the course discusses
about IT project management and the role technology has played in modern organizations. Specific
topics are selected from information system framework, quality management, project management (PMI
PMP, specifically), agile project management, information technology service management (ITSM) (the
ITIL framework, specifically), and data management. The other half of the course reviews and
integrates the common essential technologies used (file system, scripting, and databases), and
connect technology design and adoption with computing skills. Specific technology include Linux
operating system, bash scripting, and MySQL database.
Linux/UNIX-like OS, Bash, MySQL, PM (SDLC, agile), ITSM (ITIL)
Note: Ideally, this course could be made into two separate courses, one integrated IS and one
PM/ITSM.
Computer Science I with Python
This course introduces the essential ideas of computation through hands-on practice of programming to
cultivate skills and habit of computational thinking and problem-solving as a computer scientist. This
course is geared to flip learning: live coding activities in class and reading at home to ensure a focus
on problem-based and project-based learning. A laptop computer is recommended in the lectures so that
the learner can follow along to gain experience and practice. While practice time is limited in lecture
sessions, the weekly laboratory sessions are devoted to help the learners with the homework assignment
of the week. The analytical and coding elements are blended with a survey of the big ideas in computer
science, which covers the theoretical foundations, the organization of computer systems, and
applications and effect of computers on the society. (The use of the Python turtle module makes the
coding practice in this course visual and enjoyable!)
CS1, Python Standard Library, Classes & OOP, visual learning
Data Structure & Algorithm
The goals of this course is for the learners to achieve an understanding of fundamental data structures
and algorithms, which means solving computational problems that involve collections of data and is
critical for developing efficient computer code. We will introduce a set of data abstractions, data
structures, and algorithms (including lists, stacks, queues, heaps, dictionaries, maps, hashing, trees
and balanced trees, sets, graphs, and searching and sorting algorithms) along with the tradeoffs between
different implementations of these abstractions. At the successful completion of this course, learners
will be able to describe and manipulate and implement the types of data structure a variety of
algorithms for searching and sorting (including linear search, binary search, insertion sort, selection
sort, merge sort, quicksort, and heap sort) and write recursive algorithms. For theoretical analysis,
learners will be able to analyze the time and space efficiency of data structures and algorithms for
selecting efficient tools for solving computational problems.
Python Collections Module, Complexity (O-notation), Data
Structures, Sorting and Searching
MIS
Management Information Systems
Undergraduate/Graduate
This course provides a broad socio-technical overview of information systems in organizations by showing
how various technology infrastructure and information systems/applications function together to support
the operation, management, and strategic decision-making of enterprises. Major topics include:
information systems and the competitive advantage of enterprises, the structure and components of
information technology infrastructure, the features of major enterprise application systems, and the
planning, implementation, and management of information systems projects. The learners will also learn
about the design, development, and operation major enterprise system applications such as enterprise
resource planning, customer relationship management, supply chain management, knowledge management, and
business intelligence.
e-Business, IT Infrastructure, ERP, CRM, SCM, KM, BI, PM
Enterprise Information System Practice
This course aims to provide learners the hands-on experience needed in the successful operation of
enterprise systems. After taking this course, the learners will possess fundamental understanding of
the infrastructure and information system technology and applications in enterprises. The concepts
and skills obtained from this course will ensure that the learners become capable of describing,
operating, designing, and implementing information systems at enterprise level. Recommended
prerequisites include operating systems, databases, programming, and enterprise information
communications. Additional learning resources are suggested for learners without the prerequisites.
Linux OS, networking, network security, file services, Web server, business flow/process
Note: This course is the technical implementation of the MIS sibling course
Global Information Systems Strategies
Graduate
This course aims to provide a lens for students to analyze the ever changing world of business
strategy from the perspective of information technology (IT) and information systems (IS). The
course focuses on how the use of information systems could increase the competitive advantage of a
firm in a globalized and networked business world.
Students will learn about the foundations of IS, the strategic and technical perspectives of
corporate information systems, and how the development of ICT could impact the global business
environment in the future. In order to achieve such learning, students need to possess the basic
concepts and knowledge about organization, the global economy, and information systems to enable
them to think strategically about how to leverage IS and IT infrastructure for business value.
Through analysis of IS cases, the students will: 1) examine key IS development trends, 2)
familiarize themselves with the issues of IS in the global business context, 3) be able to analyze
the IS issues from management viewpoints.
Competitive Advantage, Business Process Reengineering, Knowledge
Management, Decision Support, Business Intelligence, Competitive Intelligence,
Cultural Dimensions
Professional/Business Ethics
Graduate/Undergraduate
In addition to covering the ethical issues essential to the information systems professionals, this
course provides learners the opportunity to explore ethical issues in depth to cultivate students as
modern citizens with sufficient knowledge about ethical regulations. In addition, this course will
provide opportunities for students to engage in the thinking and argument of moral issues.
After successful completion of this course, the students will be able to demonstrate the following
competences in the areas knowledge, affection, and skills: 1) Become familiar with the logical
reasoning process of the ethical judgment system of the university's Professional Ethics Curriculum
and is able to apply it to the ethical choice scenarios (Skill); 2) Through obtaining of
professional ethics knowledge and concepts and case studies in the discipline of information
management, form the habit of critical thinking in general ethics and become willing to actively
conduct professional ethical thinking and judgment (Affection); 3)Understand the professional ethics
issues in the discipline of information management (Knowledge) and 4) willing to collaboratively
communicate, explore, and share with peers (Affection) and express dialectical statement (Skill).
Ethics, moral dilemma, ethical decision-making, irrationality (behavioral economics)
Social Science Research Method
Graduate
This course offers a comprehensive introduction to research as practiced by contemporary social
scientists along with tools to apply the learned research concepts practically. Students learn about the
design and construction of research projects and various research methods and the analysis of both
qualitative and quantitative data.