Courses
Database Management (ISM 4212)
Modern organizations rely on data-driven decision-making to stay competitive.
Database systems therefore have become central to organizations’ decision-making at
operational, managerial, and strategic levels. The main objective of this course is
hence to equip students the capability and skills in understanding and utilizing
database systems to be able to access, retrieve, analyze, and utilize data and
information effectively to support decision-making in organizations. Students will
begin with learning about database systems followed by conceptualizing, designing,
and implementing databases in a real-world context for tasks from information
processing to managerial decision-making.
This course introduces the theory and practice of database design, management, and application. Topics covered
include basic database concepts, relational algebra, data modeling with entities and relationships,
normalization, SQL queries, and writing code to interface with databases. To ensure the learners' capability to
design and implement an information systems with a relational database server backend, a 3-tier client-server
interactive web database application term project integrates the knowledge and skills learned throughout the
semester.
DBMS, Relational DBMS, SQL, MySQL, SQLite, Database Modeling, Database Design, SQL Queries
Business Intelligence (ISM 4117)
Business intelligence (BI), by nature, is the study of an integrated set of
applied computational and business techniques used to obtain business insights
from data. Simply put, BI is computerized support for managerial
decision-making. The purpose of using BI is to help organizations stay
competitive by managing data as a strategic resource for supporting decisions
and enabling innovation.
To achieve better decision-making, organizations need the capacity to collect contextual business data; to
employ analytics techniques to discover possible business insights; and to communicate and collaborate the
results of analysis internally and externally. This course provides a balanced introduction to BI, including
both the organizational (managerial and strategic) and technical issues associated with the development and
deployment of BI applications to serve as such capacity. Major topics covered include business needs,
decision support, IT & decision infrastructure, data management, the analytical processes, methodologies,
and current BI practices. Students will also learn commercial tools and techniques such as visualization,
statistical analysis, and management dashboard to transform business data into useful information for
effective decision support.
Business Intelligence (BI), Decision Support, Dashboard, Excel, SQL, Databases,
Python, Visualization, Descriptive Analytics
Information Systems & Services (LIS 3706)
This course introduces students topics that connect their learning in information systems and IT management in
organizations. It includes an introduction to information system hardware components, operating systems,
scripting languages, with practical applications in databases and networked servers. In addition, this course
provides practice in managing the people, processes and events (planned or otherwise) involved in information
system and information service management. Information management topics include system management, maintenance,
quality assurance, reporting services, and management of physical and human resources as services.
OS, Linux, scripting, Bash, DBMS, Relational DBMS, SQL, MySQL, SQL Queries
Computational Problem Solving with Python
This course introduces the essential ideas of computation through hands-on practice of Python
programming to cultivate the skills and concepts of computational thinking and problem-solving of a
computer science. This course is designed to use the principles of flip learning (FL): live coding
homework assignments and lab activities in class with textbook and pre-recorded lecture viewing at
home. FL ensures the class time is used for 1) problem-based, 2) project-based, and 3) collaborative
problem-solving. Access to a computer is required during class meeting hours so that students can
follow along the demonstrations and engage in exercises to implement the computational concepts
through preparing small code blocks. The weekly laboratory sessions, on the other hand, give
students the opportunity to work over longer periods of time on problems and projects to integrate
skills and concepts covered. The analytical and coding elements are connected to a structured
concepts in computer science.
CS1, Programming Basics, Python Standard Library, Data Structure, Classes & OOP
Data Analysis and Visualization with R (Python)
Adapted from a Data Carpentry course, this class is a general introduction to data science.
Beginning with a review of R/Python programming, this course leads the learner through the topics
of data types, data workflows, data visualization using packages, and managing SQL databases using
Python. The class meetings consist of short introductions to data science concepts followed by
demonstrations and hands-on coding exercises. No background in computer programming is assumed.
R/Python Programming, Data Visualization, SQL
Note: This course was originally prepared in the form of data science weekend
workshops at the School of Information at Florida State University. This course can
be implemented using either Python or R language .
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
Management Information Systems (MIS)
2006~2016
Chung Yuan U.
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
Chung Yuan U.
Undergraduate
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, Database Server, Business
Flow/Process
Note: This course is the technical implementation of the MIS sibling course
Global Information Systems Strategies
International MBA Program
Chung Yuan U.
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
Business Ethics
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. In addition, this course provide opportunities for students to engage in the
thinking and debating of moral issues and arguments.
After successful completion of this course, the students will be able to demonstrate the following
competences in the areas knowledge, affection, and skills:
- Become familiar with the logical reasoning process of the ethical judgment in ethical choice scenarios;
- Through obtaining of professional ethics knowledge and concepts and case studies in the discipline of information management, form the habit of critical thinking in ethical decision-making;
- Become willing to actively conduct professional ethical thinking and judgment;
- Understand the professional ethics issues in the discipline of information management; and
- Become willing to collaboratively communicate, explore, and share with peers.
Ethics, Moral Dilemma, Ethical Decision-making, Irrationality (Behavioral Economics)
Social Science Research Method
This course offers a comprehensive introduction to research as practiced by contemporary social
scientists along with tools to practically apply the learned research concepts. Students learn about the
design process and implementation of research projects, data collection methods, and the analysis of
both qualitative and quantitative data.