tychen
 
Courses
Database Management (ISM 4212)
Spring 2022
Florida State University
Syllabus
Undergraduate

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)
Spring 2022
Florida State University
Syllabus
Undergraduate

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)
Spring 2018 ~
Undergraduate

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
EMBA Program, Chung Yuan U.
Textbook: Justice
Open Course Site
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. 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:
  1. Become familiar with the logical reasoning process of the ethical judgment in ethical choice scenarios;
  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 ethical decision-making;
  3. Become willing to actively conduct professional ethical thinking and judgment;
  4. Understand the professional ethics issues in the discipline of information management; and
  5. Become willing to collaboratively communicate, explore, and share with peers.
Ethics, Moral Dilemma, Ethical Decision-making, Irrationality (Behavioral Economics)
Social Science Research Method
Chung Yuan U.
Textbook: Earl R. Babbie
Graduate
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.