Programme Structure 课程体系

The course looks at (i) how artificial intelligence (AI) (e.g., Generative AI, Agentic AI), and data science are impacting business strategies and operations, and (ii) how AI and data science can be used to transform businesses and organizational processes to gain competitive advantages and enhance innovation in an increasingly digital economy. The course will cover both the theoretical/conceptual foundations of AI and data science and their practical applications in areas such as marketing, finance, supply chain, and customer relationship management. The course also discusses ethical and privacy considerations, governance issues, and responsible use of AI technologies in business contexts. Through case studies and industry examples, course participants will develop the ability to translate course content into actionable and impactful business strategies and plans. Upon completion, participants will have the knowledge and skills to understand and comprehend advanced IT technologies, develop AI- and data-driven innovation strategies, and manage digital transformation initiatives in their businesses and organizations. 

本课程将探讨：(i) 人工智能（如生成式人工智能、代理式人工智能）与数据科学如何影响商业战略与运营；(ii) 在日益数字化的经济环境中，如何运用人工智能与数据科学重塑企业与组织流程，从而获取竞争优势并提升创新能力。课程将涵盖人工智能与数据科学的理论/概念基础，并探讨其在市场营销、金融、供应链及客户关系管理等领域的实践应用。课程还将探讨商业场景中的人工智能科技伦理与隐私考量、治理问题及负责任使用。通过案例研究与行业实例，学员将掌握将课程内容转化为可执行且具影响力的商业战略与计划的能力。完成课程后，学员将具备理解先进信息科技、制定人工智能与数据驱动的创新战略、管理企业及组织数字化转型项目的知识与技能。 

Senior managers very often need to make important decisions to ensure business competitiveness. These are usually difficult to justify without a good model and thorough data analysis. This course focuses on using Excel spreadsheets and Tableau as effective tools in business and financial modeling and data analysis. Through practices in class, students will be able to develop on their own models, covering representative topics from corporate finance to investments planning and analysis, to analyze trade-offs and sensitivities, and understand implications of uncertainties and risks. Using Tableau, powerful visualizations can be built to identify business challenges and opportunities. The key emphasis of this course is on acquiring the necessary model construction and data analytics skills to support critical decision making. 

高级管理人员常常需要做出重要决策以确保企业竞争力。若缺乏完善的模型和深入的数据分析，这些决策往往难以获得合理依据。本课程聚焦于运用Excel电子表格和Tableau作为商业与财务建模及数据分析的有效工具。通过课堂实践，学员将掌握独立构建模型的方法，涵盖从公司财务到投资规划与分析等典型主题，从而分析权衡关系与敏感性，理解不确定性与风险的影响。借助Tableau可创建强大的可视化工具，精准识别商业挑战与机遇。本课程的核心在于培养必要的模型构建与数据分析技能，为关键决策提供有力支撑。

As data and AI increasingly drive innovation across industries, realizing their full potential remains a profound challenge. This course introduces the fundamental principles and the core techniques for data and AI markets. The course is guided by a vision for data and AI markets—an emerging paradigm that reimagines how we share, value, and collaborate around data and AI models. Moving beyond fragmented exchanges, these markets aim to create trusted, privacy-preserving, and incentivized ecosystems where cooperation becomes scalable and sustainable. The course will illustrate practical examples from domains such as healthcare. The course will highlight how data ecosystems can evolve from isolated assets into dynamic, service-oriented platforms. It sketches key ideas behind fair valuation, privacy-aware collaboration, and trustworthy infrastructure, showing how technical and economic design can reinforce one another. Rather than a deep technical dive, this course offers a conceptual roadmap and forward-looking vision: how co-designing algorithms, infrastructure, and market mechanisms can transform data and AI into shared engines of equitable and impactful innovation. 

随着数据与人工智能日益驱动各行业的创新，如何充分发挥其潜力仍是一项重大挑战。本课程将介绍数据与人工智能市场的基本原理和核心技术。课程以数据与人工智能市场的愿景为指引——这一新兴范式重新构想了我们如何围绕数据与人工智能模型进行共享、评估和协作。超越零散的交易模式，这些市场旨在构建可信赖、保护隐私且具有激励机制的生态系统，使合作得以实现规模化与可持续性。课程将通过医疗健康等领域的实践案例进行阐释。课程将重点阐释数据生态系统如何从孤立资产演进为动态的服务导向型平台，勾勒公平估值、隐私感知协作及可信赖基础设施背后的核心理念，展示技术设计与经济设计如何形成良性循环。本课程不追求技术深度钻研，而是提供概念性路线图与前瞻性愿景：通过协同设计算法、基础设施与市场机制，将数据与人工智能转化为推动公平且具有深远影响的创新共享引擎。

This course examines how digital technologies are reshaping leadership theory, organizational behavior, and governance structures. Students critically analyze how artificial intelligence, big data, platform infrastructures, and algorithmic management challenge classical frameworks of motivation, decision-making, and organizational design. The course explores how digital transformation alters authority, coordination, and culture in remote, hybrid, and digital-native organizations, while addressing ethical issues such as data surveillance and algorithmic bias. Through engagement with contemporary research and advanced case analysis, students develop an evidence-based digital leadership framework applicable to their own organizations, integrating theory with executive practice. 

本课程系统探讨数字技术如何重塑领导理论、组织行为与治理结构。学员将批判性分析人工智能、大数据、平台基础设施与算法管理如何挑战经典激励理论、决策理论与组织设计框架。课程聚焦数字化转型如何改变组织权力结构、协调机制与文化形态，并深入讨论数据监控与算法偏见等伦理问题。通过前沿研究文献研读与高级案例分析，学员将构建基于理论与证据的数字领导力框架，实现理论与高层管理实践的融合。​

Emerging Tech Ecosystem Seminars I & II expose DBA(Tech) students to the frontier technologies reshaping industries and creating new entrepreneurial opportunities. Spanning two modules, the seminars cover a broad spectrum — from quantum computing, AI, and blockchain to healthcare innovation, smart nation initiatives, and space technology. Through curated talks by leading researchers, practitioners, and entrepreneurs, students will gain first-hand insight into cutting-edge technological developments, real-world applications, and the venture-building opportunities they enable. The goal is to broaden students' technological fluency beyond their core domain, helping them identify cross-disciplinary innovation opportunities and develop an informed perspective on the emerging tech landscape that will define the next decade of business transformation.

新兴技术生态系统研讨会 I & II 旨在帮助DBA(Tech)学生深入了解正在重塑行业格局并催生全新创业机遇的前沿技术。研讨会分为两个模块，涵盖广泛的技术领域——从量子计算、人工智能、区块链，到医疗健康创新、智慧国度建设以及航天科技。通过精心策划的系列讲座，学生将与顶尖学者、行业实践者及创业者直接对话，获得对前沿技术发展、实际应用场景及其所带来的创业机会的第一手洞察。研讨会的核心目标是拓展学生在自身专业领域之外的技术视野，帮助他们识别跨学科创新机遇，并建立对未来十年驱动商业变革的新兴技术生态的深刻认知。

This course analyzes how digital technologies transform entrepreneurial finance, valuation, and capital allocation. Students examine platform economies, SaaS models, fintech innovation, and data-driven business architectures through the lens of corporate finance theories, including agency theory, real options, and information economics. The course emphasizes valuation of intangible and data assets, network effects, unit economics (e.g., LTV/CAC), venture contracting, and exit strategies in high-uncertainty environments. Through rigorous case analysis and research-based discussion, students develop theoretically grounded financial strategies applicable to scalable digital ventures and innovation initiatives. 

本课程系统分析数字技术如何重塑创业金融、企业估值与资本配置机制。学员将基于代理理论、实物期权理论与信息经济学等公司金融理论框架，深入探讨平台经济、SaaS模式、金融科技创新与数据驱动商业模式。课程重点涵盖数字无形资产与数据资产估值、网络效应、单体经济模型（如LTV/CAC）、风险投资契约设计与退出策略，特别关注高不确定性环境下的资本决策。通过严谨案例分析与研究型讨论，学员将构建具有理论基础的数字企业融资与创新资本战略。

This course examines the strategic role of financial derivatives in the modern fintech ecosystem. Building on core mechanics of forwards, futures, options, and swaps, the course focuses on how smart contracts and automated market makers (AMMs) are transforming derivative execution, clearing, and settlement. Students explore innovations in structured products, synthetic assets, and real-time risk management powered by big data and AI. The course bridges traditional valuation models with the practices of the Programmable Finance era, preparing leaders to design and govern sophisticated financial instruments in an increasingly automated global economy.

本课程系统剖析金融衍生品在现代金融科技生态中的战略地位。课程在夯实远期、期货、期权、互换核心机理的基础上，重点聚焦智能合约与自动化做市商（AMM）如何重构衍生品的执行、清算与结算。学员将探究大数据与人工智能驱动的结构化产品创新、合成资产与实时风险管理工具。课程打通传统估值模型与 “可编程金融” 时代实践，培养学员在高度自动化的全球经济中设计与治理复杂金融工具的领导力。

This course explores the evolution of global financial markets through the lens of technological disruption. Students analyze how algorithmic trading, high-frequency data, and AI-driven analytics reshape market liquidity, price discovery, and regulatory oversight. Beyond traditional equity and bond markets, the course examines the infrastructure of digital asset exchanges, decentralized finance (DeFi) protocols, and the geopolitical implications of cross-border digital currencies. By the end of the course, students will master analytical frameworks to assess risks and opportunities in global capital flows, where financial logic and technological capability are deeply and inextricably integrated.

本课程从技术变革视角解析全球金融市场的演进。学生将分析算法交易、高频数据与人工智能分析如何重塑市场流动性、价格发现机制及监管框架。课程超越传统股债市场，深入探讨数字资产交易所架构、去中心化金融（DeFi）协议，以及跨境数字货币的地缘政治影响。课程结束后，学员将掌握分析全球资本流动的系统框架，精准识别风险与机遇，深刻理解金融逻辑与技术能力的深度融合。.

This comprehensive course provides a deep dive into Large Language Models (LLMs) and the principles of Generative AI, covering the foundational Transformer architecture, pre-training methods, and practical prompt engineering techniques essential for steering modern AI like ChatGPT. You will learn to move beyond basic interaction, exploring advanced customization frameworks such as Retrieval-Augmented Generation (RAG) for proprietary data and specialized models for generating text, code, and images. 

The course emphasizes real-world applications across major industries. Key use cases include boosting software developer productivity through code generation, revolutionizing customer service with advanced virtual assistants, and enhancing marketing personalization by generating large volumes of customized content. This course is ideal for data scientists and business professionals seeking to master the implementation of Generative AI to drive innovation and efficiency in their respective fields. 

本课程深入探讨大语言模型（LLMs）与生成式人工智能原理，涵盖基础Transformer架构、预训练方法及实用提示工程技术——这些正是操控ChatGPT等现代AI的核心要素。您将学习突破基础交互，探索高级定制框架：如专为私有数据设计的检索增强生成（RAG），以及生成文本、代码和图像的专用模型。 

课程着重强调跨行业实际应用场景。核心应用包括：通过代码生成提升软件开发者效率、运用先进虚拟助手革新客户服务模式、借助海量定制化内容生成技术增强营销个性化。本课程特别适合数据科学家及商业人士，助您掌握生成式人工智能的落地应用，在各自领域推动创新与效率提升。 

This course examines the evolving role of leadership in driving organizational change within the digital era. Students will study leadership theories and practices, with particular focus on digital transformation, organizational culture, and change management. Topics include leading virtual teams, fostering innovation, managing resistance, and aligning digital initiatives with corporate strategy. Emphasis will be placed on the leadership skills needed to inspire, influence, and empower employees in technology-enabled organizations. Real-world case studies and interactive exercises will enable students to critically analyze digital transformation journeys and apply leadership frameworks to complex organizational challenges. 

本课程探讨领导力在推动数字时代组织变革中的演变作用。学员将系统学习领导力理论与实践，重点关注数字化转型、组织文化及变革管理领域。课程涵盖虚拟团队领导、创新培育、阻力管理以及数字化举措与企业战略的协同等议题。课程特别强调科技驱动型组织中激励员工、影响决策及赋能团队的核心领导力技能。通过真实案例分析与互动实践，学员将掌握批判性审视数字化转型路径的能力，并学会运用领导力框架应对复杂的组织挑战。

This course equips students with the essential tools and methodologies for conducting rigorous academic and applied research in business and management. Students will gain a solid understanding of qualitative and quantitative approaches, including research design, data collection, and statistical analysis. Emphasis will be placed on formulating research questions, developing hypotheses, and applying appropriate methods to generate valid and reliable insights. The course also introduces ethical considerations in research and prepares students to design their own projects that address complex issues in management and economics. By the end of the course, students will be able to critically evaluate existing studies and develop independent, methodologically sound research proposals. 

本课程旨在为学生提供开展严谨的商业与管理学术及应用研究所需的核心工具与方法论。学生将系统掌握定性与定量研究方法，包括研究设计、数据收集及统计分析等核心技能。课程重点在于培养学生提出研究问题、构建假设并运用恰当方法获取有效可靠的洞见的能力。同时引入研究伦理考量，引导学生设计解决管理与经济领域复杂课题的独立研究项目。完成课程后，学生将具备批判性评估现有研究成果的能力，并能制定方法论严谨的独立研究方案。

This course provides a strategic framework for managing the complex and interconnected risks of security and safety in technology-driven businesses. In today's landscape, these domains are not siloed technical concerns but are fundamental to business continuity, brand reputation, legal compliance, and ethical responsibility. The curriculum is designed to equip future leaders with the mindset and tools to pre-emptively manage security risk rather than react to failures.The course will cover fundamental security and privacy technologies such as encryption, digital signature, access control, intrusion detection, and blockchain.  Moving beyond technologies, the course examines how to integrate security and safety as core business functions, essential for risk management, and sustained competitive advantage. The course will explore the modern threat landscape, security-by-design principles, and the governance structures needed to build resilient organizations. A strong emphasis is placed on real-world case studies, from catastrophic software failures and massive data breaches to algorithmic bias and supply chain attacks, to ground theoretical concepts in practical business outcomes. 

本课程为科技驱动型企业管理复杂且相互关联的安全与保障风险提供战略框架。在当今环境中，这些领域已非孤立的科技问题，而是关乎业务连续性、品牌声誉、法律合规与道德责任的根本要素。课程旨在培养未来领导者具备前瞻性思维与工具，实现安全风险的预先管控而非被动应对。课程将涵盖加密科技、数字签名、访问控制、入侵检测及区块链等核心安全与隐私科技。 超越科技层面，课程将探讨如何将安全与防护融入核心业务职能，将其作为风险管理与持续竞争优势的基石。课程将剖析现代威胁态势、安全设计原则，以及构建韧性组织所需的治理架构。课程特别强调现实案例研究——从灾难性软件故障、大规模数据泄露，到算法偏见与供应链攻击——使理论概念落地于实际商业成果。

This course explores how digital technologies, innovation, and disruption are reshaping competitive landscapes across industries. Students will analyze key strategic frameworks and apply them to real-world cases where artificial intelligence, big data, and platform-based ecosystems redefine value creation and capture. The course emphasizes how firms can adapt their business models, leverage emerging technologies, and sustain competitive advantage in dynamic environments. Through case studies and simulations, students will learn to anticipate technological shifts, assess strategic options, and make informed decisions in fast-changing markets. The course is particularly relevant for leaders seeking to navigate uncertainty and create strategic agility in technology-intensive contexts. 

本课程探讨数字科技、创新与颠覆如何重塑各行业的竞争格局。学生将分析关键战略框架，并将其应用于现实案例——其中人工智能、大数据及平台化生态系统正重新定义价值创造与获取方式。课程重点阐释企业在动态环境中如何调整商业模式、运用新兴科技并保持竞争优势。通过案例研究与模拟演练，学员将掌握预判科技变革、评估战略选项及在快速变化市场中做出明智决策的能力。本课程尤其适合需要在科技密集型环境中应对不确定性、打造战略敏捷性的领导者。 

This course introduces students to the foundations of corporate governance and capital market regulation, drawing on classic theories in corporate governance and corporate finance. Students will first explore the core principles of governance, investor protection, and regulatory design in traditional business and financial contexts. Building on this foundation, the course examines applications to cutting-edge areas, including blockchain governance, cryptocurrency and digital asset regulation, and the evolving regulatory landscape for artificial intelligence. By connecting classical concepts of governance and finance with the novel issues raised by technological innovation, the course equips students with the analytical tools to understand, evaluate, and shape the interaction between business, regulation, and technology in a rapidly changing world. 

本课程基于公司治理与公司金融的经典理论，向学生介绍公司治理与资本市场监管的基础知识。学生将首先在传统商业与金融背景下探索治理核心原则、投资者保护及监管设计。在此基础上，课程将深入探讨前沿领域的应用，包括区块链治理、加密货币与数字资产监管，以及人工智能不断演变的监管格局。通过将治理与金融的经典概念与科技创新引发的新问题相衔接，本课程旨在为学生提供分析工具，使其能够在瞬息万变的世界中理解、评估并塑造商业、监管与科技之间的互动关系。

This course provides an in-depth exploration of the emerging paradigm of Web3 and the tokenized economy, examining how collaborative intelligence and decentralized technologies are reshaping business, finance, and governance. Students will gain a solid understanding of blockchain foundations, collaborative intelligence core technologies, digital assets, decentralized finance (DeFi), and tokenomics, as well as the design of trust frameworks in decentralized systems. Through case studies and applied projects, the course highlights how tokenization enables new business models in areas such as asset-backed tokens, stablecoins, decentralized identity, and real-world asset (RWA) digitization. In addition to technical and economic principles, the course addresses regulatory, ethical, and governance considerations in Web3 adoption, with particular focus on the frontiers at digital economy landscape. By the end of the course, students will be equipped to critically assess opportunities and risks of tokenization, design strategic approaches for organizations, and contribute thought leadership on how tokenized economies can drive sustainable digital transformation. 

本课程深入探讨Web3新兴范式与代币经济，剖析协作智能与去中心化科技如何重塑商业、金融及治理模式。学员将系统掌握区块链基础理论、协同智能核心科技、数字资产、去中心化金融（DeFi）及代币经济学原理，并理解去中心化系统中的信任框架设计。通过案例分析与实践项目，课程重点阐释代币化如何在资产支持代币、稳定币、去中心化身份认证及现实世界资产（RWA）数字化等领域催生新型商业模式。除科技与经济原理外，课程还将探讨Web3应用中的监管、伦理及治理考量，尤其聚焦数字经济领域的创新前沿。完成课程后，学员将具备批判性评估通证化机遇与风险的能力，能够为组织设计战略方案，并就通证化经济如何推动可持续数字转型贡献思想领导力。