Core Courses

Introduction to Management (3 credits)

Introduction to management is a required course for all the undergraduate students of School of Business. Basically, management is a science and art, and dynamic as well. This course is expected to enable students to have a full understanding of the importance of management in today’s increasingly competitive global business environment. It provides students with basic managerial theories, concepts and principles. Emphases are given to the four functions of management, i.e., planning, organizing, leading and controlling. By the end of this course, students are expected to understand basic theories about management, and be able to apply what they have learnt from this course into practices. This course aims to assist students to build up a scientific framework of analyzing business and management. It will prepare students to better cope with disciplines that related to advance management in the coming semesters, enabling them to develop managerial skills in the future.

Microeconomics (3 credits)

Economics is the study of how society allocates its scarce resources. The field of economics is traditionally divided into two broad subfields of microeconomics and macroeconomics. Microeconomics is the study of how households and firms make decisions and how they interact in specific markets. The main purpose of this course is to motivate students to learn basic microeconomic principles and tools of analysis in order to apply them to a variety of economic topics and issues. Topics and issues include market structure, including competition and monopoly, costs of production, wage determination, resource markets, market failure, government policies, including taxation and regulation, income inequality, poverty, pollution, health care and international trade.

Macroeconomics (3 credits)

This course provides students with a comprehensive foundation in macroeconomics, covering essential theories, models, and real-world policy applications. Students will analyze key concepts such as national income, consumption, investment, money and inflation, interest rates, and unemployment, while exploring the interplay between short-run fluctuations and long-run growth. A central focus is placed on Keynesian economics, including the role of monetary and fiscal policy in stabilizing business cycles. Through this course, students will develop the analytical tools needed to assess economic policies and their impacts on global and domestic economies.

Fundamentals of Finance (3 credits)

The course is designed to cover the topics in fundamental finance. Students can learn the basic concepts of financial management, financial report, valuation of cash flow and stock market. This course introduces the fundamental theories of finance and basic quantitative tools used in the major decisions of corporate financial management. It covers financial statement analysis, time value of money, bond valuation, stock valuation, risk and return, cost of capital, capital budgeting, and financing decision. Upon successful completion of this course, students are able to perform basic financial ratio analysis based on financial statements, to apply the model of time value of money to solve money problems, such as financial asset pricing, future value, present value, the return on an investment, payment value and payment periods. Students will know how to calculate expected returns of stock, the security market line and the risk-return trade-off based on Capital Asset Pricing Model (CAPM).

Introduction to Accounting (3 credits)

In modern business environments, accurately recording and reporting economic events is essential. Accounting serves the critical function of converting business activity into valuable information, which stakeholders use to assess performance and to support financial analysis and decision-making in business activities. This course introduces financial accounting from a user’s and business-analytics perspective with a strong focus on analyzing the process of business transactions. Students learn core accounting principles and trace how transactions flow through the accounting system from economic events to journal entries and financial statements.

Operations Management (3 credits)

This course is designed to give the students the concepts and applications of operations management. To accomplish this, lecture material includes detailed examples, solved questions, and cases studies in forecasting, capacity planning, process selection, location analysis, inventory management, quality management, supply chain management, and project management.

Business Ethics and Corporate Social Responsibility (3 credits)

Business Ethics and Corporate Social Responsibility is a required course for all the undergraduate students in School of Business. This introductory course aims to explore the ethical obligations and responsibilities of a manager, and his / her moral relationship with shareholders and other stakeholders. Important theories of managerial obligation, including the stockholder theory, the stakeholder theory and so on, will be introduced to provide foundation for students’ awareness of the ethical issues in general business management. Various aspects related to business ethics will be discussed, including marketing, use of technology, discrimination, employee conduct, environment and questionable business practices. After taking this course, students are expected to reflect critically on the ethical issues in business management, to develop their own views on these issues, and to resolve ethical dilemma in the workplace as employee and manager.

Probability and Statistics (3 credits)

This course offers a comprehensive introduction of statistical and probability principles utilized in business data analysis. This course aims at equipping students’ expertise to carry out descriptive, analytical, and predictive data analysis to tackle contemporary real-world business issues and provide practical insights for managerial solutions. This course lays the foundation. For quantitative skills that can be utilized in advanced data analysis courses.

Linear Algebra (3 credits)

This course aims at providing students with basic theories, calculation methods and application in Linear Algebra. The course mainly introduces the essential topics in linear algebra, such as linear systems, matrix, determinant, vector space, eigenvalue and eigenvectors. Students will learn how to analyze and solve math problems and will build a strong foundation for further studies and their professional careers.

Introduction to Python Programming (3 credits)

This course trains students to use programming to solve real-world business analytics problems. It covers Python syntax, data structures, functions, modules, file handling, and commonly used libraries such as NumPy and pandas. Through case studies, students learn data cleaning, processing, and basic analysis, and develop computational thinking applied to business data. Emphasizing theory and practice, the course builds a foundation for further study in data analysis, data mining, and related fields.

Introduction to Business Analytics (3 credits)

Introduction to Business Analytics is a foundational course designed to equip students with the core concepts, methods, and tools of business analytics. The course covers the fundamentals of data collection, data analysis, business decision-making models, and data visualization. Students will learn how to apply data-driven approaches to solve business problems while developing critical thinking and analytical skills. This course is ideal for students interested in business data analytics and provides a foundation for advanced coursework.

Data Structures and Algorithms (3 credits)

The objective of this course is to provide students with foundational knowledge of data structures and algorithms, focusing on efficiently organizing data and designing problem-solving procedures. The course will introduce core data structures, including arrays, linked lists, stacks, queues, trees, and graphs, along with their corresponding algorithms such as sorting, searching, traversal, and dynamic programming. It will also explore methods for analyzing time and space complexity. Through theoretical explanations and practice, students will learn how to select appropriate structures and algorithms to optimize program performance and cultivate the ability to solve practical problems.

Business Forecasting (3 credits)

As business operations grow more complex and uncertain, the ability to scientifically forecast and analyze future environments has become a vital skill in corporate decision-making. This course equips students with key forecasting methods, such as time series analysis, smoothing techniques, decomposition models, regression analysis, and the Box-Jenkins (ARIMA) model, and trains them to apply these tools using software like Minitab and SPSS. Emphasizing both theory and practice, the course combines case studies and hands-on projects to help students effectively use forecasting in real-world business contexts.

Data Management and Visualization (3 credits)

In the era of big data, data management and visualization have become essential core skills for modern managers. This course aims to cultivate students’ systematic abilities in data processing, analysis, and visualization. The course content covers database design and management, data cleaning and preprocessing, statistical analysis methods, and the application of various data visualization tools. Through a combination of theoretical learning and practical operations, students will be able to use modern data management tools, design effective data visualization solutions, and provide strong data support for business decision-making.

Business and Artificial Intelligence (3 credits)

In today’s rapidly evolving information technology, this course aims to help students understand the fundamental concepts of information systems and cultivate their ability to understand and apply information technology to support organizational business objectives. The course will cover the application of information systems / information technology (IS / IT) at various levels. The course will focus on how IS / IT can help organizations make more informed business decisions, with a particular emphasis on how to analyze data to enhance business intelligence. It will also provide practical application of artificial intelligence in business and management.

Data Mining (3 credits)

This course aims to enable students to understand the principles of classical machine learning algorithms and be able to construct models of classical algorithms through programming languages. The course will cover various machine learning algorithms, including regression trees, classification trees, random forests, ensemble learning, neural networks, regularization, and principal component analysis. Specifically, this course focuses on encouraging students to appropriately apply relevant theories and methods, solve practical problems in the business field, and interpret the commercial implications of the analysis results to assist in business decision making.

Deep Learning and Big Data (3 credits)

This course aims to enable students to systematically learn and master the core theories, frameworks, and common applications related to deep learning and big data. The course covers the fundamental knowledge of deep learning, including the basic principles of neural networks, backpropagation, and common activation and loss functions. In addition, we will also focus on mainstream deep learning models such as, Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Long Short-Term Memory Networks (LSTM), and Transformer. Consequently, students are able to build models through mainstream frameworks, master model training and tuning, and thus achieve typical applications in business scenarios.

Modeling and Simulation (3 credits)

In today’s globalized and complex supply chain networks, the ability to apply modeling and simulation to analyze real management problems is essential for future managers and decision-makers. This course aims to equip students with fundamental theories and methods of modeling and simulation, using a 3D simulation platform and common software to transform abstract management problems into operational models for analysis. Topics include modeling of core supply chain processes, simulation of system operations, dynamic decision-making, and strategy evaluation under uncertainty. Simulation games are also designed to let students experience challenges in supply chain coordination, resource allocation, and risk control. Students are expected to master basic modeling and simulation tools, abstract and analyze practical supply chain problems, understand applications and comparisons of different simulation methods and gain awareness of recent developments in the field.

Business Decision Methods (3 credits)

This course provides an introduction to the application of management science techniques within spreadsheet environments to support decision analysis. Instructional content, comprising detailed examples, problem-solving exercises, and case studies, covers the following areas: linear, integer, goal, and nonlinear programming; sensitivity analysis; network modeling; regression analysis; simulation; queuing theory; and decision analysis.

Electronic Commerce (3 credits)

This course is designed to facilitate students’ understanding of the basic concepts of electronic commerce and equip students with the capabilities to understand and apply electronic commerce knowledge to support the organization’s objectives. This course emphasizes technologies, business principles, and issues related to electronic commerce. Different facets of electronic commerce will be covered, including technological support of electronic commerce, electronic commerce presence design, online payments, security threats, technology solutions, business models and concepts, management practices, internet marketing, emerging applications, issues in electronic commerce, customer relationship management, etc. Many electronic commerce cases will be discussed in this course. Students will gain insights into electronic commerce operations, and business concepts, and an understanding of the potential challenges. They will be empowered to propose feasible solutions for companies operating in the electronic commerce space.

Social Media Analytics (3 credits)

In the era of today’s digital transformation and the booming development of social platforms, possessing social media analytics capabilities to gain insights into business and communication dynamics is crucial for students who aspire to pursue careers in marketing, brand strategy, or business management in the future. This course aims to guide students in acquiring the core operational principles of social media, enabling them to transform real-world business scenarios into appropriate analytical models for exploration. Students must solidly understand user behavior analysis, content dissemination principles, data extraction techniques, and platform algorithm mechanisms; gain an initial grasp of social network architecture, digital marketing tactics, social media big data analytics, and privacy and ethical issues; and pay attention to the latest developments in social media analysis within the business domain.

Game Theory in Business (3 credits)

This course is designed for senior students in the program. Using game theory as the core analytical tool and integrating business intelligence tools, the course systematically cultivates students’ strategic problem analysis and scientific decision-making abilities. The course primarily covers static games of complete information, dynamic games of complete information, static games of incomplete information and dynamic games of incomplete information. Through case studies, the students can apply the methods they learn to the reality.

Graduation Project (3 credits)

The Graduation Project in Business Intelligence and Data Analytics is a crucial course designed to equip students with the ability to apply foundational theories, core knowledge, and professional skills in business analytics to address real-world challenges.