本项目通过研究网络犯罪有关的法律问题，学习刑法、证据法等相关基础知识，掌握法条、文献及案例检索和分析的研究方法。学生通过研习网络犯罪问题的有关法条及司法解释、案例，讨论网络犯罪的有关罪名的含义、网络犯罪行为的事实认定与定罪量刑等具体的问题，研究如何通过阅读相关法条、文献和案例回答前述问题。学生通过项目最终可以获得发现法学争议、提出有价值的法学研究问题、运用法条、文献和案例检索及分析的研究方法等方面的经验，掌握具体的与研究问题有关的刑法、证据法等相关的知识。

本项目将通过六次课，介绍矩阵的相关知识，以及一个矩阵背景的纯数学的公开问题，及其最新进展和困难所在。本项目目标是教给学生基本的初级研究能力和前沿科学思维，并且锻炼学生的逻辑思维和创新力。本项目可能会用到的软件包括MATHEMATICA等。

本项目将带领同学们从生命科学和基因学的角度对AD阿尔兹海默症的影响机理进行探索。通过项目学生能够更加了解生命科学与生物医学学科的本质。同时项目将为有志于今后从事相关学科的学生提供实践经验，也希望学生们通过该项目能够了解目前探索生命科学领域最新前沿技术。

本项目围绕数据洞察世界的核心智能技术方法涵盖：1）世界的数据、知识表示方法；2）视觉/语言数据的机器理解；3）从数据中推理新发现的逻辑演算计算；3）从数据中学习归纳知识的机器学习技术。研究了适用于不用应用的神经网络的构成。学生通过项目最终可以获得视觉、语言数据处理的一般方法和基于深度学习的神经网络计算的基本原理。

本项目从碳中和内涵、实现碳中和的重要意义出发，主要介绍大气环境遥感、植被遥感、地表覆被信息遥感等不同卫星平台以及生态过程模型对大气碳库、植被碳库以及大气与土壤/植被之间的碳通量交互的监测、估算和模拟方法，评估我国土地利用变化对陆地生态系统系统碳库的影响，预测不同气候情景下我国陆地生态系统碳汇能力及其对碳排放的中和能力。通过本项目的学习研究，学生将了解当前碳中和研究的前言技术和方法，能理解并亲自实践区域尺度大气碳库和植被碳库的探索，激发学生从事全球变化等相关领域研究的兴趣与热情。

课程将带领学生进一步探索我们的肠道，了解关于肠道的更多前沿的知识，同时通过实战经验传授，让学生能够掌握保持肠道健康的方法，掌握胃肠道疾病的调理方法等等，更多干货都将在课程中一一呈现。胃肠道的健康是人体健康的基石！通过本次学习我们不仅能为自己打造健康，还能为他人健康保驾护航。在本项目中，导师将带领学生跟踪营养学与医学最新科学研究成果，介绍营养学科发展的趋势，为肠道健康问题提供营养解决思路；应用营养学的理论知识剖析和解决现实中健康或疾病的相关问题，增强精准的解决问题的能力。

本项目将带领同学们从生命科学和基因学的角度对AD阿尔兹海默症的影响机理进行探索。通过项目学生能够更加了解生命科学与生物医学学科的本质。同时项目将为有志于今后从事相关学科的学生提供实践经验，也希望学生们通过该项目能够了解目前探索生命科学领域最新前沿技术。

本课程将首先从介绍虚拟现实技术的起源和发展过程开始，通过讲述虚拟现实技术在各个行业应用中的应用情况和典型虚拟仿真系统开发流程，逐步分析虚拟现实在发展过程中所面临的需求与挑战，以及背后所蕴含的技术问题，着重结合各种具体应用来讲授背后的共性技术原理和算法。在此基础上，重点讲授常用虚拟现实人机交互设备及其基本原理、虚拟场景几何建模与表示技术、动态现象/场景的物理建模仿真技术、虚拟场景的实时逼真绘制技术、增强现实技术，及其在人工智能中的应用等。由于本门课程是一门实践性很强的课程，因此，将在课内结合具体知识点设置课后作业，并结合虚拟现实技术在医疗、教育、培训等领域的应用情况。合理设置难度适中的作业，使得学生能够结合虚拟现实技术应用场景来学习以及加深对相关技术的理解、掌握以及应用，并借此培养学生的创新意识与专业技能。

本项目从光学成像原理出发，通过对彩色数字图像获取方法的梳理，引导学生理解彩色相机插值计算的内涵和意义，并逐步熟悉与掌握各类经典彩色Demosaicing算法，利用计算软件实现1-2种算法的数字仿真。通过本项目的学习研究，学生将了解到最先进的相关光学成像技术进展，理解并亲自实践探索，扩展学生的科学前沿视野，激发未来从事光学、视觉、算法等领域研究的兴趣与热情。

在本课程中，学生们将会学习人工智能在医学领域的应用场景以及目前医学人工智能的最新发展。同时，学生们将会学习BP神经网络，CNN卷积神经网络以及LSTM长短时记忆神经如何在医学中应用。课程中将会涉及医学图像处理的案例分析与探讨，由此引出创新性方案的思考。希望对人工智能或者生物医学工程感兴趣的学生能够通过本项目的学习为未来学业和工作打下基础。

项目内容包括计算天体物理、宇宙学、星系物理、星系形成模拟方法等理论知识与案例实战。学生将通过项目了解前沿星系形成理论、星系模拟理论和编码，完成星系形成模拟。学生将在课程结束时提交项目报告，进行成果展示。 个性化研究课题参考： 高纯锗探测器在粒子物理与天体物理中的应用 星系恒星形成历史及特性演化研究 原初和主序星系在不同尺度下的恒星形成 The students learn about the basics of cosmology, astrophysics and how galaxies form. They use analytical and numerical methods to study the evolution of our universe. They will submit a project report at the end of this project and display their results. Suggested Research Fields： Application of High Purity Germanium Detector in Particle Physics and Astrophysics Research on the Formation History and Characteristic Evolution of Galaxy Stars Star formation in primordial and main sequence galaxies at different scales

项目内容包括拓扑性质和复杂网络的度量、网络模型、互联网和网络的结构和演化、网络可视化。学生将自选课题，对选定真实网络，例如社交网络、世界航空网络或者脑图，完成量化分析，在项目结束时提交项目个性化研究课题报告，进行成果展示。 个性化研究课题参考： 使用时间指数随机图形模型分析加权网络 共同进化的感染网络的结构研究 基于多层网络构建语义网络的知识图谱及其在社交网络上的应用 复杂网络中的自异性和自同性分析

项目从传统能源材料与新能源材料的异同切入，进而带领学生走进种类繁多的新能源材料世界。其中将会涉及到诸多纳米技术与电池材料基本原理，如物理化学、金属材料、固体物理和电化学中关于材料的结构组成、制备、性能、能量存储与转换等多学科交叉的知识。在整个项目中，我们将以特斯拉的电池材料为主线举例，让学生在接受理论的同时了解到其最新的工业应用。学生将在项目结束后，提交项目报告，进行成果展示。 个性化研究课题参考： 特定类型的电池及其整体结构对电池寿命的影响 不同类型的电解质–固体电解质及液体电解质 合理提高电池能量密度的监管问题 电动汽车车架和车厢使用的复合材料及其质量效应 This project starts with discussing the similarities and differences between traditional energy materials and new energy materials and leads students into the world of new energy materials. This project will involve many basic principles of nanotechnology and battery materials, such as physical chemistry, metal materials, solid-state physics and electrochemistry on the structure, preparation, performance, energy storage and conversion of materials, and other interdisciplinary knowledge. Tesla’s battery materials will act as an example throughout the project, students can understand the latest industrial applications. Students will submit a research report at the end of this project to show their results. Suggested Future Research Fields: The impact of specific types and overall structure of batteries on battery life Different types of electrolytes---solid electrolytes and liquid electrolytes Regulatory issues for rationally increasing battery energy density Composite materials used in electric vehicle frames and compartments and their mass effects

项目将带领学生学习金融市场效率和套利原则、多元投资组合和投资组合理论、目标导向型投资、公募基金、ETF基金、因子投资等知识。学生将在项目结束时提交报告，进行成果展示。

项目将带领学生学习金融市场效率和套利原则、多元投资组合和投资组合理论、目标导向型投资、公募基金、ETF基金、因子投资等知识。学生将在项目结束时提交报告，进行成果展示。

项目将首先回顾包含分类与回归的传统机器学习算法及初步神经网络，而后教授将会介绍用于优化神经网络的数学原理及代码技术。在确保学生具备扎实的理论及编程基础后，项目将进入到关于卷积神经网络原理、架构、优化及应用的核心阶段，学生将根据自身兴趣选择个性化研究课题进行深入研究，在项目结束时提交项目报告，进行成果展示。 In this course, you will be taken from basic topics of artificial neural networks to advanced topics such as convolutions. We will review important introductory concepts such as feedforward networks, gradient descent etc and then dive into convolutional neural networks. 个性化研究课题参考 Suggested Research Fields： 算法优化：图卷积神经网络 Graph Neural Networks 计算机视觉应用：DGD卷积神经网络行人重识别 Person re-identification on DGD convolutional neural networks 自然语言处理应用：基于自联想记忆与卷积神经网络的跨语言情感分类 Auto-associative convolutional neural network based multi-language sentiment classification 推荐系统应用：基于标签卷积神经网络的推荐算法 Personalised recommender system with tagged convolutional neural network

项目内容包括拓扑性质和复杂网络的度量、网络模型、互联网和网络的结构和演化、网络可视化。学生将自选课题，对选定真实网络，例如社交网络、世界航空网络或者脑图，完成量化分析，在项目结束时提交项目个性化研究课题报告，进行成果展示。 个性化研究课题参考： 使用时间指数随机图形模型分析加权网络 共同进化的感染网络的结构研究 基于多层网络构建语义网络的知识图谱及其在社交网络上的应用 复杂网络中的自异性和自同性分析

项目中，导师将向学生介绍机器学习和现代人工神经网络的关键理论，然后探索机器学习在涉及图像、声音和运动数据分类的实际问题上的实际应用。该项目将使用Edge Impulse在线平台，让学生在无需编写完整复杂代码的情况下，将复杂的神经网络学习方法应用到所收集的数据集上。学生将自选真实世界的分类任务，使用上述算法及平台开发解决方案，在项目结束时提交项目报告，进行成果展示。 This course will introduce students to machine learning and modern neural networks. It will introduce the key theory of this approach and then explore the practical use of machine learning on real problems involving the classification of images, sounds and motion data. The course will use the online Edge Impulse platform to allow students to apply sophisticated neural network learning approaches, without having to write code, to datasets that they have collected (from the internet or their smartphones). During the project, students will choose their own real-world classification task, develop a solution using the skills that they learned, write up their results, and present their work back to the group.

项目内容包括可穿戴设备、心电图ECG、前沿心电放大器设计理念等理论知识与实战。学生将掌握仪表放大器的基本知识，运用LTSpice软件设计一款可以植入新一代智能手表或可穿戴设备中的仪表放大器，帮助医生清晰监测心电信号，在课程结束时提交报告，进行成果展示。 个性化研究课题参考： 新型电化学传感器的构建及其在环境检测中的应用 乳腺癌标记物的太赫兹生物传感研究 面向智能服装的无线传感器研究 This project includes theoretical knowledge of wearable devices, ECG, and ECG amplifier design concepts. In this project, students can grasp the basic knowledge of instrumentation amplifiers, use LTSpice to design an instrumentation amplifier which can be implanted in smart watches or wearable devices to help doctors monitor the ECG signal. Students should submit their research report at the end of the course and show their results. Suggested Future Research Fields: Construction of electrochemical sensors and their applications in environmental detection Terahertz biosensing study of breast cancer markers Research on wireless sensors for smart clothing

项目内容包括机器学习与数据科学概论、商业分析中市场数据处理的机器学习技术与算法、Python与Jupiter notebooks交互式学习、机器学习库、股市预测等。学生将在项目中学习如何使用机器学习完成商业市场数据分析，进行股市预测，在项目结束时，提交项目报告，进行成果展示。

项目主要涵盖材料物理学的基础理论及相关概念，重点讲授分子动力学、蒙特卡洛法在材料科学中的应用，引导学生进行原子尺度的材料基础建模。学生将了解到材料模拟中的多个时空尺度及其背后的理论联系，掌握每种技术有关的基本算法实现。最终以小组为单位，对特殊材料进行综合性建模并出具细节性研究报告。通过项目，学生将掌握基本的计算模拟理念和方法，充分了解材料计算与模拟这一现代材料学不可或缺的新型研究方法。 个性化研究课题参考： 计算化学方法在基于受体结构的药物分子设计中的应用 金属—有机骨架材料的吸附分离机理及功能化的计算化学研究 计算化学在确定天然产物绝对构型中的应用 This project is talking about basic theories of materials physics, application of molecular dynamics and Monte Carlo method in materials science. Students will understand the multiple temporal and spatial scales in material simulation and the theoretical connections behind them, master the basic algorithm implementation related to each technology. Finally, the students will model some special materials. Through this project, students will master the basic calculation and simulation methods, understand how to calculate and simulate materials. Suggested Future Research Fields: Application of Computational Chemistry Methods in the Design of Drug Molecules Based on Receptor Structure Computational Chemistry Study on the Mechanism of Adsorption and Separation of Metal-Organic Frameworks and Functionalization Application of Computational Chemistry in Determining the Absolute Configuration of Natural Products

项目主要涵盖材料物理学的基础理论及相关概念，重点讲授分子动力学、蒙特卡洛法在材料科学中的应用，引导学生进行原子尺度的材料基础建模。学生将了解到材料模拟中的多个时空尺度及其背后的理论联系，掌握每种技术有关的基本算法实现。最终以小组为单位，对特殊材料进行综合性建模并出具细节性研究报告。通过项目，学生将掌握基本的计算模拟理念和方法，充分了解材料计算与模拟这一现代材料学不可或缺的新型研究方法。 个性化研究课题参考： 计算化学方法在基于受体结构的药物分子设计中的应用 金属—有机骨架材料的吸附分离机理及功能化的计算化学研究 计算化学在确定天然产物绝对构型中的应用 This project is talking about basic theories of materials physics, application of molecular dynamics and Monte Carlo method in materials science. Students will understand the multiple temporal and spatial scales in material simulation and the theoretical connections behind them, master the basic algorithm implementation related to each technology. Finally, the students will model some special materials. Through this project, students will master the basic calculation and simulation methods, understand how to calculate and simulate materials. Suggested Future Research Fields: Application of Computational Chemistry Methods in the Design of Drug Molecules Based on Receptor Structure Computational Chemistry Study on the Mechanism of Adsorption and Separation of Metal-Organic Frameworks and Functionalization Application of Computational Chemistry in Determining the Absolute Configuration of Natural Products

项目内容包括生物传感理论、蛋白质折叠过程、单分子检测技术、荧光光谱应用、非标记检测技术等。学生将通过项目了解生物传感器的类型和运作机制，掌握单分子生物传感器等前沿生物传感技术，在项目结束时提交项目报告，进行成果展示。 个性化研究课题参考： 光学传感方法的构建及其在环境检测中的应用 纳米复合材料光电化学传感应用研究 纸基折叠电池的制备与化学传感应用 新型光化学传感分子的设计合成与分子识别研究 This project includes the knowledge of biosensing theory, protein folding process, single-molecule detection technology, fluorescence spectroscopy application, non-label detection technology, etc. Students will learn about the types and operating mechanisms of biosensors, cutting-edge biosensing technologies such as single-molecule biosensors, and submit a reasearch report at the end of the project to show their results. Suggested Future Research Fields: The construction of optical sensing method and its application in environmental detection Research on application of nanocomposite photoelectrochemical sensing Preparation and chemical sensing application of paper-based folding battery Design, synthesis and molecular recognition of new type photochemical sensor molecules

项目将首先回顾包含分类与回归的传统机器学习算法及初步神经网络，而后教授将会介绍用于优化神经网络的数学原理及代码技术。在确保学生具备扎实的理论及编程基础后，项目将进入到关于卷积神经网络原理、架构、优化及应用的核心阶段，学生将根据自身兴趣选择个性化研究课题进行深入研究，在项目结束时提交项目报告，进行成果展示。 In this course, you will be taken from basic topics of artificial neural networks to advanced topics such as convolutions. We will review important introductory concepts such as feedforward networks, gradient descent etc and then dive into convolutional neural networks. 个性化研究课题参考 Suggested Research Fields： 算法优化：图卷积神经网络 Graph Neural Networks 计算机视觉应用：DGD卷积神经网络行人重识别 Person re-identification on DGD convolutional neural networks 自然语言处理应用：基于自联想记忆与卷积神经网络的跨语言情感分类 Auto-associative convolutional neural network based multi-language sentiment classification 推荐系统应用：基于标签卷积神经网络的推荐算法 Personalised recommender system with tagged convolutional neural network

项目内容包括生物传感理论、蛋白质折叠过程、单分子检测技术、荧光光谱应用、非标记检测技术等。学生将通过项目了解生物传感器的类型和运作机制，掌握单分子生物传感器等前沿生物传感技术，在项目结束时提交项目报告，进行成果展示。 个性化研究课题参考： 光学传感方法的构建及其在环境检测中的应用 纳米复合材料光电化学传感应用研究 纸基折叠电池的制备与化学传感应用 新型光化学传感分子的设计合成与分子识别研究 This project includes the knowledge of biosensing theory, protein folding process, single-molecule detection technology, fluorescence spectroscopy application, non-label detection technology, etc. Students will learn about the types and operating mechanisms of biosensors, cutting-edge biosensing technologies such as single-molecule biosensors, and submit a reasearch report at the end of the project to show their results. Suggested Future Research Fields: The construction of optical sensing method and its application in environmental detection Research on application of nanocomposite photoelectrochemical sensing Preparation and chemical sensing application of paper-based folding battery Design, synthesis and molecular recognition of new type photochemical sensor molecules

项目内容包括生物传感理论、蛋白质折叠过程、单分子检测技术、荧光光谱应用、非标记检测技术等。学生将通过项目了解生物传感器的类型和运作机制，掌握单分子生物传感器等前沿生物传感技术，在项目结束时提交项目报告，进行成果展示。 个性化研究课题参考： 光学传感方法的构建及其在环境检测中的应用 纳米复合材料光电化学传感应用研究 纸基折叠电池的制备与化学传感应用 新型光化学传感分子的设计合成与分子识别研究 This project includes the knowledge of biosensing theory, protein folding process, single-molecule detection technology, fluorescence spectroscopy application, non-label detection technology, etc. Students will learn about the types and operating mechanisms of biosensors, cutting-edge biosensing technologies such as single-molecule biosensors, and submit a reasearch report at the end of the project to show their results. Suggested Future Research Fields: The construction of optical sensing method and its application in environmental detection Research on application of nanocomposite photoelectrochemical sensing Preparation and chemical sensing application of paper-based folding battery Design, synthesis and molecular recognition of new type photochemical sensor molecules

项目主要涵盖材料物理学的基础理论及相关概念，重点讲授分子动力学、蒙特卡洛法在材料科学中的应用，引导学生进行原子尺度的材料基础建模。学生将了解到材料模拟中的多个时空尺度及其背后的理论联系，掌握每种技术有关的基本算法实现。最终以小组为单位，对特殊材料进行综合性建模并出具细节性研究报告。通过项目，学生将掌握基本的计算模拟理念和方法，充分了解材料计算与模拟这一现代材料学不可或缺的新型研究方法。 个性化研究课题参考： 计算化学方法在基于受体结构的药物分子设计中的应用 金属—有机骨架材料的吸附分离机理及功能化的计算化学研究 计算化学在确定天然产物绝对构型中的应用 This project is talking about basic theories of materials physics, application of molecular dynamics and Monte Carlo method in materials science. Students will understand the multiple temporal and spatial scales in material simulation and the theoretical connections behind them, master the basic algorithm implementation related to each technology. Finally, the students will model some special materials. Through this project, students will master the basic calculation and simulation methods, understand how to calculate and simulate materials. Suggested Future Research Fields: Application of Computational Chemistry Methods in the Design of Drug Molecules Based on Receptor Structure Computational Chemistry Study on the Mechanism of Adsorption and Separation of Metal-Organic Frameworks and Functionalization Application of Computational Chemistry in Determining the Absolute Configuration of Natural Products

This course provides an introduction to a modern web development in Java. Creating web applications requires various approaches and involves the integration of numerous technologies. The course is designed for beginners and explains the specifics of Java web development. The topics covered include object-oriented paradigm for programming (in Java); building modern web pages with HTML, CSS, servlets, JSP, JavaScript and XML; using professional tools on team project. Students are expected to participate in a group final class project to apply the learned concepts. 本项目将介绍现代的基于Java的网站开发。创建web应用程序需要多种方法，并涉及到多种技术的集成。本项目旨在让学生了解Java web开发的细节,所涵盖的主题包括面向对象的编程范式(Java);用HTML、CSS、servlet、JSP、JavaScript和XML构建现代网页;在团队项目中使用专业工具。学生将随着项目的进行,整理用户需求,完成原型设计，并最使用上述工具编写代码、开发网站。学生将在项目结束时，进行demo展示。 个性化研究课题参考 Suggested Research Fields 类亚马逊购物网站开发 Building the front end of a shopping website 优化现有学校官方网站界面 Beautify your school’s current official website

This program provides an overview and introduction to storytelling using virtual environments and/or 360 degree video. Students will learn about the history of Virtual Reality (VR) and its relation to other media arts as a basis for creating their own immersive narrative or documentary experiences using easily accessible hardware and software. We will ask and answer questions such as: • What are the special challenges and opportunities when working with immersive media? • What experiences can be achieved with immersive media that are not available in any other medium? • What kinds of stories or experiences work best for immersive media? • What are the most effective platforms for delivery? • How can immersive audio be used most effectively? • What are the limitations of immersive media? • What is the future of virtual reality for storytelling? Students will need access to a consumer grade 360 video camera or prior skills using a 3D game engine such as Unreal or Unity to complete assignments. No prior technical experience is required. Access to a home VR display system is helpful but not required. 本项目将提供了一个概述和介绍使用虚拟环境和/或360度全景视频讲故事。学生将学习虚拟现实(VR)的历史及其与其他媒体艺术的关系，以此为基础，使用易于获取的硬件和软件，创造自己的沉浸式场景体验。项目将就沉浸式体验的独特性、交付平台及未来发展应用深入讨论及实践，学生将在项目结束时，搭建自己的虚拟场景

项目内容包括机器学习与数据科学概论、商业分析中市场数据处理的机器学习技术与算法、Python与Jupiter notebooks交互式学习、机器学习库、股市预测等。学生将在项目中学习如何使用机器学习完成商业市场数据分析，进行股市预测，在项目结束时，提交项目报告，进行成果展示。

项目主要涵盖材料物理学的基础理论及相关概念，重点讲授分子动力学、蒙特卡洛法在材料科学中的应用，引导学生进行原子尺度的材料基础建模。学生将了解到材料模拟中的多个时空尺度及其背后的理论联系，掌握每种技术有关的基本算法实现。最终以小组为单位，对特殊材料进行综合性建模并出具细节性研究报告。通过项目，学生将掌握基本的计算模拟理念和方法，充分了解材料计算与模拟这一现代材料学不可或缺的新型研究方法。 个性化研究课题参考： 计算化学方法在基于受体结构的药物分子设计中的应用 金属—有机骨架材料的吸附分离机理及功能化的计算化学研究 计算化学在确定天然产物绝对构型中的应用 This project is talking about basic theories of materials physics, application of molecular dynamics and Monte Carlo method in materials science. Students will understand the multiple temporal and spatial scales in material simulation and the theoretical connections behind them, master the basic algorithm implementation related to each technology. Finally, the students will model some special materials. Through this project, students will master the basic calculation and simulation methods, understand how to calculate and simulate materials. Suggested Future Research Fields: Application of Computational Chemistry Methods in the Design of Drug Molecules Based on Receptor Structure Computational Chemistry Study on the Mechanism of Adsorption and Separation of Metal-Organic Frameworks and Functionalization Application of Computational Chemistry in Determining the Absolute Configuration of Natural Products

项目内容包括机器学习与数据科学概论、商业分析中市场数据处理的机器学习技术与算法、Python与Jupiter notebooks交互式学习、机器学习库、股市预测等。学生将在项目中学习如何使用机器学习完成商业市场数据分析，进行股市预测，在项目结束时，提交项目报告，进行成果展示。

2017年，摩根大通发布了一份题为《大数据与人工智能战略：机器学习和其它投资数据分析方法》的报告，对机器学习对金融领域的影响进行了全面的阐述，昭示着机器学习已经敲开金融领域和商业数据分析的大门。机器学习是什么？如何与商业分析相结合？项目将通过介绍两种非常实用的商业分析工具，即Python编程语言和机器学习工具包，帮助学生厘清上述问题的答案。学生将着重了解机器学习在商业分析股市预测中的应用，利用机器学习分析市场数据解决商业问题。该项目内容包括机器学习与数据科学概论、商业分析中市场数据处理的机器学习技术与算法、Python与Jupiter notebooks交互式学习、机器学习库、股市预测等。学生将在项目中学习如何使用机器学习完成商业市场数据分析，进行股市预测，在项目结束时，提交项目报告，进行成果展示。 In 2017, JPMorgan Chase released a report entitled "Big Data and AI Strategies: Machine Learning and Alternative Data Approach to Investing, which comprehensively elaborated the impact of machine learning on the financial sector, showing that machine learning has been introduced into the financial sector and business data analysis. What is machine learning? How to integrate it with business analysis? The program will help students clarify the answers to the above questions by introducing two useful business analysis tools, the Python programming language, and the machine learning toolkit. Students will focus on the application of machine learning in business analysis and stock market forecast, and use machine learning to analyze market data to solve business problems. The program covers an introduction to machine learning and data science, machine learning techniques and algorithms on market data processing in business analysis, interactive learning with Python and Jupiter notebooks, libraries for machine learning, and predicting the stock market. During the program, students will learn how to use machine learning to complete market data analysis, predict the stock market, and at the end of the program, submit a project report and present the results.

In this program we will study the pricing and hedging of financial derivatives in the benchmark models used in financial engineering, the binomial tree model and the Black-Scholes-Merton model. We will also discuss popular extensions to those models, such as stochastic volatility models, and suggest more recent models for projects or further research, such as rough volatility models. Suggested Research Fields: Recent popular option pricing models, such as rough volatility models or recent models with jumps. 在本项目中，我们将研究金融工程中使用的基准模型、二叉树模型以及布莱克-舒尔斯模型中金融衍生品的定价和对冲。我们还将讨论这些模型最近比较流行的扩展方向，例如随机波动率模型，并介绍一些新型模型，为后续的项目或深度研究做准备，例如粗略波动率模型。

项目将首先回顾包含分类与回归的传统机器学习算法及初步神经网络，而后教授将会介绍用于优化神经网络的数学原理及代码技术。在确保学生具备扎实的理论及编程基础后，项目将进入到关于卷积神经网络原理、架构、优化及应用的核心阶段，学生将根据自身兴趣选择个性化研究课题进行深入研究，在项目结束时提交项目报告，进行成果展示。 In this course, you will be taken from basic topics of artificial neural networks to advanced topics such as convolutions. We will review important introductory concepts such as feedforward networks, gradient descent etc and then dive into convolutional neural networks. 个性化研究课题参考 Suggested Research Fields： 算法优化：图卷积神经网络 Graph Neural Networks 计算机视觉应用：DGD卷积神经网络行人重识别 Person re-identification on DGD convolutional neural networks 自然语言处理应用：基于自联想记忆与卷积神经网络的跨语言情感分类 Auto-associative convolutional neural network based multi-language sentiment classification 推荐系统应用：基于标签卷积神经网络的推荐算法 Personalised recommender system with tagged convolutional neural network

本项目专注于区块链系统的技术细节和应用。导师将首先介绍以太坊区块链的系统架构专注于以太坊虚拟机和智能合约。随后，教授将从语法、类型和架构设计来分析Solidity 编程语言。教授还将介绍以太坊分散应用程序(dApps)当前的标准和框架，以及如何在主流大云上实现和部署区块链解决方案。最后导师将提出一个区块链生态系统的当前状态概述，说明该技术的风险、挑战和局限性。在项目中，学生将在导师指导下理解、设计、应用区块链技术。项目结束时，学生将提交项目报告，进行成果展示。This lecture provides an overview of Blockchain systems and related systems engineering, focusing on technical details and applications of blockchain systems. The course first demonstrates the system architecture of the Ethereum blockchain with a focus on the Ethereum Virtual Machine and smart contracts. Subsequently, the Solidity language is explained in terms of syntax, types, and design. Ethereum decentralized applications(dApps) are illustrated with current standards and frameworks, and specifics of dApps development are introduced. The course then demonstrates how to implement and deploy blockchain solutions on the mainstream big clouds. The course inspects the risks, challenges, and limitations of the technology and presents an overview of the current state of the blockchain ecosystem. 个性化研究课题参考 Suggested Research Fields 比特币区块链的数据结构与工作原理Data Structure and the Working Principles of the Bitcoin Blockchain 智能金融交易机器人 Smart Fintech Trading Robots 加密哈希函数Cryptographic Hash Functions 加密数字身份证与疫苗护照管理Secure Digital Identity and Vaccine Passport Management

商业分析和数据建模是商业和工业中有效的管理决策的重要技能。 技术的进步(电脑、扫描仪、手机)使管理人员可以获得大量的数据用于商业决策。 此外，商业分析为企业规划未来提供了一种具象化的科学方式。 通过对企业的销售、利润和其他关键指标的趋势建模，可以对这些指标的未来进行有效的科学预测。通过数据分析和建模了解可能发生的季节性、年度或任何规模的变化，可以让企业经营有备无患。该项目内容为商业分析核心知识与技能，包括统计分析、概率分布、决策分析、抽样分布、置信区间、假设检验、回归模型等。其中，概率模型侧重不确定性和风险处理；统计分析侧重数据呈现以及如何通过数据获取有用信息和有效推论；优化模型和决策分析侧重运用数据进行决策。学生将在项目中运用Excel或Mintab进行商业数据分析，在项目结束时提交报告，进行成果展示。 Business Analytics and modeling are important skills for effective managerial decision-making in business and industry. Advances in technology (computers, scanners, cell phones) have made a significant amount of data available to managers. Furthermore, business analytics provides a way for businesses to plan for the future. By modeling the trends in a businesses' sales, profits, and other key metrics, these indicators can be projected into the future. Understanding the changes that are likely to occur seasonally, annually, or on any scale allows businesses to better prepare. The techniques learned in this program will help students infer data and as such make better-informed decisions. The program covers statistical analysis, probability distributions, sampling distributions, confidence intervals, hypothesis testing, and regression models. Probability models provide tools to handle uncertainty and risk. The statistical analysis focuses on the presentation of data and techniques to draw useful and valid inferences from data.

项目内容包括计算天体物理、宇宙学、星系物理、星系形成模拟方法等理论知识与案例实战。学生将通过项目了解前沿星系形成理论、星系模拟理论和编码，完成星系形成模拟。学生将在课程结束时提交项目报告，进行成果展示。 个性化研究课题参考： 高纯锗探测器在粒子物理与天体物理中的应用 星系恒星形成历史及特性演化研究 原初和主序星系在不同尺度下的恒星形成 The students learn about the basics of cosmology, astrophysics and how galaxies form. They use analytical and numerical methods to study the evolution of our universe. They will submit a project report at the end of this project and display their results. Suggested Research Fields： Application of High Purity Germanium Detector in Particle Physics and Astrophysics Research on the Formation History and Characteristic Evolution of Galaxy Stars Star formation in primordial and main sequence galaxies at different scales

Rapid advances in digital technologies and democratized access to the entrepreneurial stack presents individuals with a once-in-a-generation opportunity to build new products and services that change the world. Building Transformational Businesses is a high-intensity, experiential workshop that will help you become a world-class builder. Through a combination of instruction, action, and critique, participants work through a process of identifying, refining and de-risking new venture opportunities. Along the way, participants build a builder’s mindset — a collection of habits, behaviors, and leadership styles, that make you a more effective problem solver, a thoughtful entrepreneur and teach you to lead in high-uncertainty environments—skills that are key to contemporary careers in business, technology, and public-service. Rapid advances in digital technologies and democratized access to the entrepreneurial stack presents individuals with a once-in-a-generation opportunity to build new products and services that change the world. Building Transformational Businesses is a high-intensity, experiential workshop that will help you become a world-class builder. Through a combination of instruction, action, and critique, participants work through a process of identifying, refining and de-risking new venture opportunities. Along the way, participants build a builder’s mindset — a collection of habits, behaviors, and leadership styles, that make you a more effective problem solver, a thoughtful entrepreneur and teach you to lead in high-uncertainty environments — skills that are key to contemporary careers in business, technology, and public-service. 数字技术的快速发展和创业组合的大众化为现今个体提供了千载难逢的机会，来打造改变世界的新产品和服务。本项目是一个高密集度的体验式项目，项目将帮助学生成为一个具有世界级思维的商业建造者。 通过指导、实践和评审的结合，学生将体验一个完整的识别、提炼和消除新风险机会的过程。在这个过程中,学生将逐渐建立起一个从行为习惯到领导风格的商业建造者心态,成为一个能更有效的解决问题,有思想的企业家,并在高度不确定性的环境中进行有序的工作，这也同时是商业、技术、公共服务领域中不可或缺的技能。

项目内容包括可穿戴设备、心电图ECG、前沿心电放大器设计理念等理论知识与实战。学生将掌握仪表放大器的基本知识，运用LTSpice软件设计一款可以植入新一代智能手表或可穿戴设备中的仪表放大器，帮助医生清晰监测心电信号，在课程结束时提交报告，进行成果展示。 个性化研究课题参考： 新型电化学传感器的构建及其在环境检测中的应用 乳腺癌标记物的太赫兹生物传感研究 面向智能服装的无线传感器研究 This project includes theoretical knowledge of wearable devices, ECG, and ECG amplifier design concepts. In this project, students can grasp the basic knowledge of instrumentation amplifiers, use LTSpice to design an instrumentation amplifier which can be implanted in smart watches or wearable devices to help doctors monitor the ECG signal. Students should submit their research report at the end of the course and show their results. Suggested Future Research Fields: Construction of electrochemical sensors and their applications in environmental detection Terahertz biosensing study of breast cancer markers Research on wireless sensors for smart clothing