USM商业分析课程简介
USM 商业分析课程简介
Synopsis of Courses
课程概览
ABW501/4 Analytics Edge
分析学的边缘
这门课程解释了将数据转换为分析驱动业务决策洞察力的科学过程。它涵盖了与分析业务数据相关的方法论、问题和挑战。课程准备学生理解商业分析，并在这些领域成为领导者。学生将学习应用分析工具、算法和方法解决商业问题。学生还将深入研究高级调查和计算方法，以发展他们的分析技能和视角。根据模拟商业示例，将在适用的情况下使用RapidMiner或其他潜在分析工具。
This course explains the scientific process of transforming data into insights for analytics-driven business decision making. It covers the methodologies, issues, and challenges related to analyzing business data. It prepares students to understand business analytics and become leaders in these areas. Students will learn to apply analytical tools, algorithms, and methodologies to solve business problems. Students will also go deeper into advanced investigative and computational methods for developing their analytical skills and perspectives. RapidMiner or other potential analytical tools will be used whenever applicable based on simulated business examples.
ABW503/4 Management Insights
管理洞见
这门课程旨在向学生提供管理研究背景下重要的管理理论、概念和技术。它将使学生接触到分析数据的每个层面的基础知识。学生还将了解到实际工作情境中最新的环境变化和管理技术。
This course aims to provide students with important management theories, concepts, and techniques in the context of management research. It will expose students to the basics of each level of analytical data. Students will also be exposed to the latest environmental changes and management techniques in the context of real work situations.
ABW504/4 Statistics for Analytics
分析统计学
这门课程旨在让学生接触到在商业和管理中使用的统计基础概念。学生将被介绍到描述性统计、基本概率、概率分布、估计和置信区间、假设检验以及相关和回归分析。这门课程将增强学生的分析决策能力，并在解决商业和管理问题中使用这些技能。统计数据还用于展示商业和管理可持续性的重要性，以及衡量可持续或绿色经济的发展。
This course is designed to give students exposure to the basic concepts of statistics used in business and management. Students will be introduced to descriptive statistics, basic probability, probability distributions, estimation and confidence intervals, hypothesis testing, and correlation and regression analysis. This course will enhance the student's capability to make analysis decisions and use them in solving business and management problems. Statistics are also used to show the importance of business and management sustainability, and to measure the development of a sustainable or green economy.
ABW505/4 Data Programming and Predictive Analytics for Business
商业数据编程与预测分析
这门课程旨在为学生提供通用编程概念以及Python或R在商业和管理应用中的实际知识的动手课程。它将使学生具备设计和编写算法的技能，以及使用Python或R包进行决策以解决商业和管理问题的能力。课程还解释了预测建模技术及其核心原则，学生将学习预测分析的坚实基础，即使用商业数据集构建统计或机器学习模型的工具和技术。讨论的技术应用于商业组织的所有功能领域，包括人才管理、财务、国际业务、会计、市场营销和运营管理。学生将能够确定他们可以做出什么样的预测，以创建未来战略，并准备充分利用分析，做出有效的数据驱动商业决策。
This course aims at providing the students with both the general programming concepts as well as hands-on sessions on practical knowledge in Python or R for business and management applications. It equips the students with skills to design and write algorithms, as well as to use the available Python or R packages, for decision making to solve business and management problems. The course also explains the predictive modeling techniques and their core principles, whereby students will learn a solid foundation of predictive analytics, which refers to tools and techniques for building statistical or machine learning models to make predictions based on the business datasets. The techniques discussed are applied in all functional areas within business organizations including talent management, finance, international business, accounting, marketing, and operations management. Students will be able to determine what kinds of predictions they can make to create future strategies and be prepared to take full advantage of analytics to create effective data-driven business decisions.
ABW506/4 Data Storytelling and Visualization
数据讲故事和可视化
这门课程向学生讲解数据讲故事的关键——在全球商业环境中的数据、视觉和叙述。学生将学习在分析商业问题和使用各种可视化工具向听众传达重要见解时的有效讲故事策略。课程结束时，学生将能够提高理解数据背景的能力，选择有效的视觉设计，有效地用数据进行沟通，并做出更好的数据驱动商业决策。
This course provides students with an understanding of the keys to data storytelling – data, visuals, and narrative in the global business environment. Students will learn the strategies for effective storytelling in analyzing business problems and communicate important insights to the audience using a variety of visualization tools. At the end of this course, students will be able to enhance their ability to understand the context of the data, choose an effective visual design, communicate effectively with the data and make better data-driven business decisions.
ABW507/4 Research Method
研究方法
这门课程为学生提供了进行研究的基本概念和过程，包括各种研究方法和设计。学生将获得进行原创研究的知识和技能，同时遵循良好的伦理研究实践。
This course provides students with basic concepts and the process of conducting research, including various research methods and designs. Students will acquire the knowledge and skillsets to undertake original research with good ethical research practices.
ABF502/4 Accounting and Finance Analytics
会计与财务分析
第四次工业革命要求跨学科知识的整合。这门课程满足企业分析会计和财务数据的需求。未来的公司需要从会计和财务数据中生成重要信息，并将这些信息与公司的外部信息（如社交媒体、人口统计和宏观经济）相联系。为此，除了扎实的会计和财务知识外，还需要使用复杂工具和软件处理数据的实践知识，以确保学生能够理解涌入组织的前所未有的数据量中的关系。
The fourth industrial revolution requires the integration of interdisciplinary knowledge. This course fulfills the needs of businesses to analyze ready data from accounting and finance. A future company needs to generate essential information from accounting and financial data and link up this information with the company’s external information like those from social media, demographic, and macro-economy. For this purpose, besides solid knowledge in accounting and finance, practical knowledge to handle data with sophisticated tools and software is also needed to ensure that students can understand the relationships in the unprecedented amount of data flowing into the organizations.
ABF503/4 Financial Technology and Digital Innovation
金融技术与数字创新
这门课程从金融及其工具的基础知识开始，为学生提供金融技术方面的知识。它向学生介绍具有颠覆传统金融方法、生态系统、全球和地方发展潜力的金融科技（Fintech）领域。课程还涵盖了人工智能、机器学习、机器人流程自动化等先进技术，并讨论技术如何帮助行业和社会走向更包容、更有竞争力和可持续的金融。
This course provides knowledge on financial technology starting with the basics of finance and its instruments. It introduces students to the Fintech landscape that has the potential to disrupt traditional financial methods, ecosystems, global and local evolution. It also exposes advanced technologies such as artificial intelligence, machine learning, robot process automation, and more, and discusses how technology can help industry and society towards a more inclusive, competitive, and sustainable financial.
ABF507/4 Economics Insights
经济学洞见
这门课程旨在让学生了解如何根据整体、国家及国际经济状况，做出分配稀缺资源的选择。它结合了微观经济理论和宏观经济理论与管理实践，并应用最新技术进行大数据分析。因此，课程包括了诸如了解企业运营的市场、价格和非价格策略、微观经济环境下的生产函数等广泛主题，并补充了货币政策、财政政策和开放经济的相关宏观政策等几个经济条件，以及关于环境保护和社会利益的双赢商业结果。课程提供了经济理论和概念的实例，展示了经济分析如何协助决策过程，这对于管理组织的商业领袖来说至关重要，以实现可持续性和平等。
This course is designed to expose the students to how choices are made to allocate scarce resources with competing uses, depending on overall, national as well as international, economic conditions. It is a discipline that combines microeconomic theories and macroeconomic theories with management practice by applying the latest techniques to big data analysis. This course, therefore, incorporates wide-ranging relevant topics such as knowing the markets in which the businesses are operating, price and non-price strategies, production function in the microeconomic environment, and later be complemented with several economic conditions such as monetary policies, fiscal policies, and relevant macro policies for open economies, as well as win-win business outcomes with regards to environmental preservation and social interest. It provides an illustration of economic theory and concepts on how economic analysis can assist in the decision-making process which is essential for business leaders for managing an organization for sustainability and equality.
ABM502/4 Marketing Analytics
营销分析
这门课程将向学生介绍系统化和分析性的营销决策背后的工具和技术。学生将了解营销中的分析挑战，并被引入四个基本的营销策略原则，这些原则可以帮助应对挑战。学生将通过学习如何测量顾客偏好、建立市场细分的不同方式、识别潜在或有吸引力的目标顾客、确定品牌的最佳定位以及通过共同分析、群集分析、定位图、逻辑回归、响应和选择模型等技术开发增值的新产品，从而发展与这四个原则相关的分析能力。数据分析将通过Marketing Engineering (MeXL)分析工具进行，该工具是Excel的一个附加组件。
This course will introduce students to the tools and techniques behind a systematic and analytical approach to marketing decision-making. Students will be exposed to the analytic challenges faced in marketing and introduced to four fundamental marketing strategy principles that can help address the challenges. Students will develop analytic competencies pertaining to the four principles by learning how to measure customer preferences, establish different ways for market segmentation, identify potential or attractive customers to target, determine the best positioning for a brand, and develop new products that add value through techniques like conjoint analysis, cluster analysis, positioning maps, logistic regression, response and choice models. Data analysis will be carried out via Marketing Engineering (MeXL) analytic tool, which is an add-on to Excel.
ABM503/4 Web and Social Media Analytics
网页与社交媒体分析
数字技术，特别是网页和社交媒体应用，在过去十年里根本性地重塑了营销理论和实践，并导致了我们能够捕获、存储和分析的信息的质量和数量的巨大转变。随着数据的大量增长，许多企业越来越需要更好地理解并对各种客户特征做出反应。这门课程旨在为学生提供识别数字营销领域中网页和社交媒体分析角色所需的技能和工具。
The digital technologies of web and social media applications have fundamentally reshaped marketing theory and practice over the last decade and have led to a drastic shift in the quality and quantity of information we are able to capture, store, and analyze. With this proliferation of data has come an increasing need for many businesses to better understand and react to various customer characteristics. This course is designed to provide the skills and tools needed for students to recognize the role of web and social media analytics within the digital marketing landscape.
ABO502/4 Human Resource Analytics
人力资源分析
人力资源分析提供了一个清晰易懂的人力资源管理流程。这是一门课程，为学生提供了关于高级人力资源管理的见解，考虑到使用虚拟数据分析创建有效的人力资源管理系统。课程还根据行业适宜性和管理方向提供人才管理方面的知识。学生将了解到有效的工作流程，使用SPSS统计软件包的数据分析技术，并进一步解释结果，帮助传达人力资源分析的潜力，以充分利用现有人力资源。案例研究方法也被用来展示这些人力资源管理实践。
Human Resource Analytics provides a clear and easy-to-understand human resource management process. This is a course that provides insights into advanced human resource management, taking into account the use of virtual data analysis to create an efficient human resource management system. This course also provides exposure to talent management according to industry suitability and management direction. The subject will expose students to effective work processes, data analysis techniques using the SPSS statistics package, and further interpret the results, helping to convey the potential of human resource analysis to make the most of existing human resources. Case study methods are also used to provide exposure to each of these human resource management practices.
ABO503/4 Collaborative Foresight
协作预见
未来的复杂性可能是压倒性的，适应变化是不可避免的。因此，组织为了在当今迅速变化的商业环境中保持竞争力，为未来做好准备至关重要。协作预见对于承认多种可能的未来以加速组织发展至关重要。它通过改善创意、问题定义和长期战略中的共识，增强组织的韧性。学生将被引导拓宽视野，了解当今推动组织变革的因素，增加在情景创造中的多样性视角，并做出适当的决策，以利用未来新可能性的潜力。学生将学习各种战略工具和统计技术，以预测各种情景，从而改善战略选择。如'TOWS Matrix'、'Competitors Analysis'、'Business Portfolio Matrices'、'SPACE Matrix'等战略工具将与人工智能、RapidMiner等统计工具结合使用，用于制定情景规划和解决方案。在这种情况下，学生将学习生成未来情景、评估这些未来的影响，并制定适应不同未来结果的适当策略的技术和分析。
The complexity of the future can be overwhelming, and adapting to change is inevitable. It is therefore important for organizations to prepare for the future to remain competitive in today’s rapidly changing business environment. Collaborative foresight is critical to acknowledge the possibility of multiple futures to accelerate organizational development. It enhances organizational resilience by improving ideation, problem definition, and consensus in long-term strategies. Students will be exposed to a wider perspective on today’s drivers of change for organizations to increase the variety of perspectives in scenario creation and make appropriate decisions, to harness the potential of new possibilities of the future. Students will learn various strategic tools and statistical techniques to make predictions on various scenarios which will result in improved strategic options. The strategic tools such as ‘TOWS Matrix’, ‘Competitors Analysis’, ‘Business Portfolio Matrices’, ‘SPACE Matrix’ will be aligned with the statistical tools such as Artificial Intelligence, RapidMiner, and other related tools that will be applied to produce Scenario Planning and solution ideas. In this case, students will learn the techniques and analytics to generate future scenarios, assess the impacts of those futures, and craft suitable strategies that are resilient to different future outcomes.
ABP502/4 Data-Driven Insights and Actions
数据驱动的洞察和行动
这门课程描述了数据分析和行动研究的概念和技术。学生将学习数据的重要性和发展。学生将学习使用分析工具和技术设计模型。学生将学习创建基于混合技术和工具（如模拟和优化）的模型，以识别数据分析中的行动。他们还将学习开发所需的批判性思维技能，并在管理背景下进行预测。此外，学生将学习选择和应用此类分析数据过程和方法。根据管理案例，将使用RapidMiner或其他潜在的分析工具。
This course describes the concepts and techniques of data analysis and action research. Students will learn the importance and development of data. Students will learn to design models using analytical tools and techniques. Students will learn to create models based on blending techniques and tools such as simulation and optimization to identify actions in data analysis. They will also learn to develop the critical thinking skills needed and make predictions in the context of management. In addition, students will learn to select and apply such analytical data processes and methods. RapidMiner or other potential analytical tools will be used based on management cases.
ABP503/4 Advances in Digital Technology
数字技术的进步
数字技术的迅速发展不仅为我们的社会创造了新机遇，也带来了挑战，各种机构都在努力通过调整策略和活动来应对。企业和政府正在重组以提高生产力、改善质量和控制成本。整个行业已经重构，以更好地适应数字时代的现实。毫不夸张地说，信息技术正在根本改变人与知识之间的关系。因此，这门课程将使学生了解数字技术进步的概念、应用和实践。
The rapid evolution of digital technologies is creating not only new opportunities for our society but challenges to it as well, and institutions of every stripe are grappling to respond by adapting their strategies and activities. Corporations and governments are reorganizing to enhance productivity, improve quality, and control costs. Entire industries have been restructured to better align themselves with the realities of the digital age. It is no great exaggeration to say that information technology is fundamentally changing the relationship between people and knowledge. Thus, this course will expose the students to the concept, application, and practice of the advancement of digital technology.
ABW508/6 Analytics Lab
分析实验室
这门课程旨在让学生在全球商业环境中应用分析技能解决商业问题。课程为学生提供利用数据分析来分析商业问题并推荐可行的商业解决方案的机会。在这门课程中，学生可以选择以下选项之一：首先，使用行业的真实数据集或网站的模拟数据集；其次，与组织中的分析团队合作获取小型分析项目，并解决实际案例。课程结束时，学生将能够根据自己的兴趣领域进行分析实验室项目，并做出更好的商业决策。
This course is designed for students to apply analytical skills in business problems in the global business environment. The course provides an opportunity for students to leverage data analytics in analyzing business problems and recommend a feasible business solution. In this course, students can choose one of the options; first, use the real dataset from industry or simulated dataset from the website and second, collaborate with analytics teams in organizations to obtain small analytics projects and solve real-life cases. At the end of this course, students will be able to conduct analytics lab projects based on their area of interest and make better business decisions.
Core Courses (Compulsory)必修课程：
ABW501/4 Analytics Edge
ABW503/4 Management Insights
ABW504/4 Statistics for Analytics
ABW505/4 Data Programming and Predictive Analytics for Business
ABW506/4 Data Storytelling and Visualization
ABW507/4 Research Method
Electives (Choose any three (3) courses)选修课程(选3个)
ABF502/4 Accounting and Finance Analytics
ABF503/4 Financial Technology and Digital Innovation
ABF507/4 Economic Insights
ABM502/4 Marketing Analytics
ABM503/4 Web and Social Media Analytics
ABO502/4 Human Resource Analytics
ABO503/4 Collaborative Foresight
ABP502/4 Data-Driven Insights and Actions
ABP503/4 Advances in Digital Technology
Project (Compulsory) 毕业设计（必选）
ABW508/6 Analytics Lab
