商业分析作为留学热门项目之一,不仅就业前景广阔,就业薪资高,也是一个快速发展的行业,每年都吸引了大量的学子前往深造,竞争尤为激烈!所以今天,小编特意为同学们带来2024年QS商业硕士学科排名中,位列全球Top1的加州大学洛杉矶分校商业分析硕士项目(Master of Business Analytics ),一起来看看吧!
三、课程结构: 该学生需要完成30个学分的核心课程、必修课程和选修课程。 通用核心课程: ACCT 5210 Managerial Accounting Foundations ECON 5200 Global Macroeconomics FINA 5120 Corporate Finance ISOM 5510 Data Analysis ISOM 5700 Operations Management MARK 5120 Marketing Strategy and Policy MGMT 5110 Managerial Communication 必修课程: ISOM 5730 Global Supply Chain Management ISOM 5810 Business Modeling and Optimization 选修课程: ISOM 5270 Big Data Analytics ISOM 5320 Digital Business and Web Analytics ISOM 5630 Business Analytics in R ISOM 5720 ERP and Enterprise Systems Management ISOM 5740 Managing Financial Services Operations ISOM 5770 Business Project Management ISOM 5820 OM Best Practices ISOM 5830 Simulation for Risk and Operations Analysis ISOM 5840 Logistics Management ISOM 6790M Sustainability for Business ISOM 6880 Project Study MARK 5430 Digital Marketing MGMT 5550 Effective Negotiations
案例展示 L同学 北理珠-金融数学 GPA80+ 录取结果: Hong Kong Baptist University--数学金融硕士&金融、投资与风险硕士双学位
下面,我们一起来简单了解该项目的一些信息~=
一、项目简介: 香港浸会大学数学系和肯特商学院(Kent Business School)的数学金融和金融、投资与风险硕士课程,反映出香港和伦敦两座城市焕发了新的活力,对金融机构、市场和教育的兴趣也有所增加。该课程提供了数学金融,金融原理和实践的坚实背景,并培养了未来商业和金融专业人士所需的技能。该项目提供了一个全面的框架的知识,洞察力和远见的关键问题在金融,财务职能的组织和业务和职能的金融机构和市场。学生将发展适当范围的认知、批判和智力技能、研究技能以及相关的个人和人际交往技能,以便在真实的商业和组织世界中进行互动。该理学硕士课程也为学生在该领域的研究或进一步学习做好准备。
二、课程结构: 这个跨学科的课程是为那些职业目标是成为金融市场专业人士、风险管理人员、衍生品分析师或交易员的学生设计的。该项目要求非常严格,需要完成13门课程。该课程将数学中的金融知识和量化技能与金融中的风险管理和动态估值技能相结合,以解决衍生证券估值、投资组合构建、风险管理和情景模拟等问题。 Semester 1 (Location: University of Kent): MFFM7020 Derivatives MFFM7070 Quantitative Methods MFFM7100 Financial Risk Management MFFM7150 Investment Analysis
Semester 2 (Location: University of Kent): MFFM7120 Advanced Investment Management MFFM7160 Credit Risk MFFM7170 Corporate Governance and Sustainability 1 Elective course*
Semester 3 (Location: Hong Kong Baptist University): MFFM7010 Topics in Probability Theory & Stochastic Processes MFFM7060 Derivatives II MFFM7030 Computational Finance MFFM7040 Time Series Analysis MFFM7050 Mathematical Finance
Elective Courses*: MFFM7110 Financial Econometrics MFFM7080 Fixed Income Markets MFFM7180 Programming for Finance in Python MFFM7190 Algorithmic Trading
学生背景: C同学 港中深-应用经济学 GPA3.7+,IELTS7.5,GRE320+ 录取结果: Columbia University--商业分析硕士 Imperial College London--商业分析硕士 The University of Hong Kong--商业分析硕士 National University of Singapore--商业分析硕士 The University of Edinburgh--商业分析硕士
二、课程结构: 该项目的学生需要完成至少31学分课程,其中包含16学分核心课程和15学分选修课程。此外,全日制学生预计在1年内完成该计划(两个常规学期:秋季和春季),非全日制学生为2年。 核心课程: MSDM 5001 Introduction to Computational and Modeling Tools MSDM 5002 Scientific Programming and Visualization MSDM 5003 Stochastic Processes and Applications MSDM 5004 Numerical Methods and Modeling in Science MSDM 5005 Innovation in Practice MSDM 6771 Data-Driven Modeling Seminars and Tutorials
选修课程: MSDM 5051 Algorithm and Object-Oriented Programming for Modeling MSDM 5053 Quantitative Analysis of Time Series MSDM 5054 Statistical Machine Learning MSDM 5055 Deep Learning for Modeling: Concepts, tools, and techniques MSDM 5056 Network Modelings MSDM 5058 Information Science MSDM 5059 Operations Research and Optimization MSDM 6980 Computational Modeling and Simulation Project PHYS 5120 Computational Energy Materials and Electronic Structure Simulations
二、课程结构: 核心课程: International Organizational Behaviour International Entrepreneurship & Intrapreneurship Cross-Cultural Negotiation Managing International Business Financial Statement Analysis in Global Context Global Human Resources Management Global Ethics & Corporate Social Responsibilities International Finance 核心选修课(2选1): Overseas Business Discovery Doing Business in Asia 选修课(至少选1门): Leadership: Managing in Adverse Situations Strategic Management and Business Policy Blockchain Technology and Business Applications
二、课程结构: 核心课程: SD6101 Data Science Thinking AI6102 Machine Learning Methodologies and Applications SD6103 Data Systems SD6104 Data Preparation SD6105 Data Visualisatio SD6106 Capstone Project AI6120 Python Programming 选修课程: AI6104 Mathematics for Artificial Intelligence SD6124 Probability and Statistics for Data Science SD6128 Introduction to Economics SD6129 Introduction to Psychology AI6122 Text Data Management SD6123 Data Privacy in Data Science AI6123 Time Series And Prediction AI6103 Deep Learning and Applications SD6125 Data Mining SD6126 Scalable Data Systems SD6127 Network Science
二、课程内容: MRED项目为期11个月的全日制教学,包括一个可选的为期一周的训练营,使学生能快速掌握项目规划、空间分析和视觉传达使用的高需求技术平台。MRED课程为城市发展政策和机构流程提供了坚实的基础,并呼吁学生对城市的未来进行批判性思考。 核心课程将在以下方面打下坚实的基础: Economics and finance Market analysis Land development laws and regulation Development and design New building technologies Negotiation and consensus-building Community participation 选修课的轮换将涉及以下主题但不限于: Climate adaptation Housing affordability Zoning and equity Age-friendly building Innovative financing Globalization Big data and smart cities
二、课程内容: 普通法学硕士方向的学生学习一门必修模块,即法律研究概论( Introduction to Legal Research),并从所有法学硕士途径的可用模块中选择五个模块,例如: Assessment and Financing of Energy Projects Banking Law Commercial Conflict of Laws Company Law Criminal Law Reform Now Elements of Cyberlaw Environmental Energy Law European Human Rights Law Financing of International Trade Issues in International Criminal Law and Justice Global Crime Problems Human Rights and Criminal Justice Human Rights and Health Care Law Intellectual Property Law International and European Legal Responses to Terrorism International Corporate Governance International Criminal Law and Justice International Human Rights International Trade Law Law and Language Law of International Organisations Law, Society and Governance Public International Law Renewable Energy and Climate Change Law Socio-Legal Theory Transnational Criminal Law