Artificial Intelligence

专业代码：080717T             学  制：4年

Program Code: 080717TDuration：4 years

培养目标（Educational Objectives）

以国家信息化发展历史机遇和粤港澳大湾区社会经济发展需求为引领，培养具有高度社会责任感和良好职业道德的复合型技术领军人才：具备人工智能领域的基础知识、基本技能和科学研究的基本素质；具有应用人工智能理论和方法以学科交叉方式解决行业关键性技术问题的综合能力，具有源头创新和引领行业技术发展的潜质，具有一定的国际视野和国际交往能力；能够在工业界、学术界、教育界等成功地开展与专业职业相关的工作；适应独立和团队工作环境，成为人工智能相关领域的创新技术引领者、重要工程管理者和专业市场开拓者。

Driven by the historical opportunities presented by a nation-wide information development and catering to the needs of social and economic progress in the Guangdong-Hong Kong-Macao Greater Bay Area, we aim to cultivate all-round high-caliber technology talents that has a strong sense of social responsibility and good professional ethics. The one that has basic knowledge and fundamental skills in the field of artificial intelligence and in scientific research; the one that possesses comprehensive abilities to solve key industrial problems with an inter-disciplinary approach by applying theories and methods of AI; the one that has great potential in innovation and industrial leadership skills; the one that has a global outlook and international communication skills; the one that has the potential to develop a career related to AI in the industrial, academic or educational circle; the one that could work independently or as team member to become technological innovators, key engineering managers or professional market pioneers in AI-related fields.

毕业要求（Student Outcomes）

№1.工程知识：能够将数学、自然科学、工程基础和专业知识用于解决与人工智能相关的复杂工程问题。

№1.1 能够应用数学、自然科学、工程基础和专业知识表述人工智能领域工程问题，并建立具体对象的数学模型；

№1.2 能够应用数学、自然科学、工程基础和专业知识解释模型的物理含义，对模型进行正确的推理和解答；

№1.3 能够将数学、自然科学、工程基础和专业知识用于人工智能领域工程问题的分析、计算和设计。

№1.4能够将数学、自然科学、工程基础和专业知识用于人工智能领域工程问题的解决方案的比较与综合。

№2.问题分析：能够应用数学、自然科学、工程科学和信息科学的基本原理，识别、表达、并通过文献研究分析人工智能领域相关复杂工程问题，以获得有效结论。

№2.1对人工智能领域的相关工程问题，能分析其需求，给出任务目标的需求描述，并识别其面临的各种制约条件。

№2.2对人工智能领域的相关工程问题，能根据需求描述，建立解决问题的抽象模型。

№2.3对人工智能领域的相关工程问题，能根据所建立的抽象模型，通过文献检索与资料查询等方式获取知识和方法，对问题进行分析，并得出有效结论。

№3.解决方案：能够设计针对复杂工程问题的解决方案，设计满足特定需求的模块或系统，能够在设计环节中体现创新意识，并考虑社会、健康、安全、法律、文化以及环境等因素。

№3.1针对特定需求，能对人工智能领域中的相关工程问题进行分解和细化，能够进行软、硬件模块的设计与开发。

№3.2了解人工智能领域技术发展的现状与趋势，能够在方案设计中体现创新意识。

№3.3结合社会、健康、安全、法律、文化及环境等因素，综合考虑复杂工程问题的应用背景、系统特性、器件指标、设计流程等因素，分析对比候选方案的可行性和性能，确定解决方案。

№4.研究能力：能够基于科学原理并采用科学方法对人工智能领域相关的复杂工程问题进行研究，包括设计实验、分析与解释数据、并通过信息综合得到合理有效的结论。№4.1能够基于科学原理并采用科学方法进行人工智能领域的相关复杂工程问题的系统分析和建模。

№4.2能够针对复杂工程系统进行实验方案设计、实验平台搭建、实验数据获取。

№4.3能够对实验数据进行信息综合分析，并得到合理有效的结论，反馈到工程设计实践中。

№5.使用现代工具：能够针对人工智能领域相关的复杂工程问题，开发、选择与使用恰当的技术、资源、现代工程工具和信息技术工具，包括对复杂工程问题的预测与模拟，并能够理解其局限性。

№5.1能恰当使用计算机软、硬件技术，通信协议及算法仿真工具，完成人工智能系统中的复杂工程问题的模拟与仿真分析，能理解其局限性。

№5.2能熟练使用电子仪器仪表观察分析人工智能系统性能，能运用图表、公式等手段表达和解决人工智能的设计问题，能理解其局限性。

№6.工程与社会：能够基于人工智能工程相关背景知识进行合理分析，评价专业工程实践和复杂工程问题解决方案对社会、健康、安全、法律以及文化的影响，并理解应承担的责任。

№6.1具备社会、健康、法律、安全以及文化的基本知识和素养。

№6.2能够合理评价人工智能领域相关工程实践和复杂工程问题解决方案对社会、健康、安全、法律以及文化的影响，并理解应承担的责任。

№7.环境和可持续发展：能够理解和评价针对复杂工程问题的人工智能专业工程实践对环境、社会可持续发展的影响。

№7.1了解人工智能相关产业、人工智能服务业相关的方针、政策与法律法规。

№7.2理解人工智能产业与环境的关系，理解和评价针对复杂工程问题的工程实践对环境、社会可持续发展的影响，理解用技术手段降低其负面影响的作用与其局限性。

№8.职业规范：具有人文社会科学素养、社会责任感，能够在工程实践中理解并遵守工程职业道德和规范，履行责任。

№8.1具有人文知识、思辨能力、处事能力和科学精神，理解应担负的社会责任。

№8.2能够在人工智能项目实践中理解并遵守工程职业道德和规范，具有法律意识，做到责任担当、贡献国家、服务社会。

№9.个人和团队：能够在多学科背景下的团队中承担个体、团队成员以及负责人的角色。

№9.1能够在人工智能领域相关研究、开发和生产的团队中承担个体和成员角色，具有团队合作精神或意识；

№9.2 能够在多学科背景下充分理解和消化其他学科的知识和方法，掌握团队合作的组织管理方式，具有团队负责人意识。

№10.沟通能力：能够就人工智能相关的复杂工程问题与业界同行及社会公众进行有效沟通和交流，包括撰写报告和设计文稿、陈述发言、清晰表达或回应指令。并具备一定的国际视野，能够在跨文化背景下进行沟通和交流。

№10.1具有良好的表达能力，能够就复杂工程问题与业界同行及社会公众进行有效沟通和交流，包括撰写报告和设计文稿、陈述发言、清晰表达或回应指令。

№10.2具备运用外语的能力和一定的国际视野，能够在跨文化背景下进行沟通和交流。

№11.项目管理：理解并掌握工程管理原理与经济决策方法，并能在多学科环境中应用。

№11.1理解并掌握工程管理原理与经济决策方法，能够识别人工智能领域相关工程项目管理与经济决策中的关键因素。

№11.2 能够将工程管理原理和经济决策方法运用于跨学科的复杂工程项目中。

№12.终身学习：具有自主学习和终身学习的意识，有不断学习和适应发展的能力。

№12.1理解不断探索和学习的必要性，具有自主学习的方法，了解拓展知识和能力的途径。

№12.2具有自主学习意识和终身学习的意识，能够根据社会环境和个人角色变化有不断学习和适应发展的能力。

№1.Engineering Knowledge: An ability to apply knowledge of mathematics, science, engineering fundamentals and engineering specialization to the solution of complex engineering problems.

№1.1 Being able to apply knowledge in mathematics, natural sciences, engineering fundamentals and Artificial Intelligence to describe AI-related engineering problems, and to establish mathematical models of related subjects;

№1.2 Being able to explain the physical meaning of said models using knowledge in mathematics, natural sciences, engineering fundamentals and Artificial Intelligence, and to make proper reasoning and explanation to the models.

№1.3 Being able to analyze, compute and design AI-related problems using knowledge in mathematics, natural sciences, engineering fundamentals and Artificial Intelligence.

№1.4 Being able to compare and combine solutions using knowledge in mathematics, natural sciences, engineering fundamentals and Artificial Intelligence.

№2.Problem Analysis: An ability to identify, formulate and analyze complex engineering problems, reaching to substantiated conclusions using basic principles of mathematics, science, and engineering.

№2.1 Being able to analyze what is required to solve a particular AI-related engineering problem, describe detailed requirements and identify potential constrains before reaching target outcomes

№2.2 Being able to build abstract models according to the descriptions of detailed requirements of a particular AI-related engineering problem

№2.3 Being able acquire knowledge and methodology through literature retrieval and material searching, analyze problems and reach effective conclusions according to the abstract model established to solve a particular AI-related engineering problem.

№3.Design/Development Solutions: An ability to design solutions for complex engineering problems and innovatively design systems, components or process that meet specific needs with societal, public health, safety, legal, cultural and environmental considerations.

№3.1 Being able to design and develop software and hardware modules after careful disintegration and division of AI-related engineering problems according to specific needs.

№3.2 Being able to catch up with the current status and trends in AI-related technological development and to demonstrate innovation in the solution design.

№3.3 Being able to compare the feasibility and performance of different solutions and choose the better ones taking into consideration the background of said complex engineering problems, systematic characters, indicators of devices used and procedures of designing etc. with an overall assessment on social, health, safety, legal, cultural and environmental concerns.

№4.Research: An ability to conduct investigations of complex engineering problems based on scientific theories and adopting scientific methods including design of experiments, analysis and interpretation of data and synthesis of information to provide valid conclusions.

№4.1 Being able to perform systematic analysis and build models on AI-related complex engineering problems based on scientific principles and using scientific methods.

№4.2 Being able to design experiments, build experimental platforms, and acquire data for complex engineering systems.

№4.3 Being able to conduct comprehensive information analysis on the data acquired, and to reach reasonable and effective conclusion that in turn guides solution design.

№5.Applying Modern Tools: An ability to create, select and apply appropriate techniques, resources, and modern engineering and IT tools, including prediction and modelling, to complex engineering activities, with an understanding of the limitations.

№5.1 Being able to develop, choose and use proper technology, resources, modern engineering and information technology tools to predict and simulate complex AI-related engineering problems and understand its constrains.

№5.2 Being able to use electronic instruments well to observe and analyze the performance of AI systems, and to use diagrams, formulas and others to express and solve AI design problems with awareness of its limitations.

№6.Engineering and Society: An ability to apply reasoning informed by contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to professional engineering practice.

№6.1 Being well-equipped with basic knowledge of society, health, law, safety and culture.

№6.2 Being able to give a reasonable evaluation on the impact of AI-related engineering practices and complex engineering problem solutions on society, health, safety, law, and culture, with an understanding of duties that needs to be undertaken.

№7.Environment and Sustainable Development: An ability to understand and evaluate the impact of professional engineering solutions in environmental and societal contexts and demonstrate knowledge of and need for sustainable development.

№7.1 Having a good knowledge of the guidelines, policies, laws and regulations on AI-related industries and service sectors.

№7.2 Having a good understanding of the relation between AI industry and the environment, of the impact of engineering practice on environment and the sustainable development of society, and of the role technology can play in reducing these negative impacts and its constrain.

№8.Professional Standards: An understanding of humanity science and social responsibility, being able to understand and abide by professional ethics and standards responsibly in engineering practice.

№8.1 Having a good knowledge in humanities, developing strong critical thinking, interpersonal skills, and scientific spirit, with an awareness of the social responsibilities that needs to be undertaken.

№8.2 Being able to understand and abide by professional ethic and norms during the carrying-out of AI projects, having a good legal sense and being ready to take responsibility for the country and the society.

№9.Individual and Teams: An ability to function effectively as an individual, and as a member or leader in diverse teams and in multi-disciplinary settings.

№9.1 Being able to work well with team members in AI-related research, development and production projects;

№9.2 Being able to understand and learn knowledge and methods of other disciplines in a multi-disciplinary team, to engage in the management of the team and act with good leadership skills.

№10.Communication: An ability to communicate effectively on complex engineering problems with the engineering community and with society at large, such as being able to comprehend and write effective reports and design documentation, make effective presentations, give and receive clear instructions, and communicate in cross-cultural contexts with international perspective.

№10.1 Being able to express oneself well and conduct effective communication with peers and the public on complex engineering problems by ways of report-writing, designing, public speech, instruction responding etc.

№10.2 Having a good command of foreign languages and global outlook, and being able to communicate in a cross-cultural context.

№11.Project Management: Demonstrate knowledge and understanding of engineering management principles and methods of economic decision-making, to function in multidisciplinary environments.

№11.1 Being able to understand and master management fundamental in engineering and economic decision-making methods, and to identify key factors in the managing and economic decision-making of AI related projects.

№11.2 Being able to apply knowledge in engineering management and economics in complex interdisciplinary engineering projects.

№12.Lifelong Learning: A recognition of the need for, and an ability to engage in independent and life-long learning with the ability to learn continuously and adapt to new developments.

№12.1 Understanding the need of continuous study, being able to study independently and knowing ways to expand knowledge and improve oneself.

№12.2 Having a good sense of independent learning and lifelong learning, and being able to learn continuously and adapt to the surroundings.

专业简介（Program Profile）

信息技术的高速发展与产业变革引发了各国间人工智能的战略竞争。粤港澳大湾区是全世界电子信息产业的基地，对人工智能人才需求巨大。

人工智能专业依托粤港澳大湾区电子信息产业优势，紧密围绕产业需求，着眼行业发展前沿，深入推进学科交叉，融入产业创新生态，贯通人工智能人才培养与产业知识价值链条的联系通道，提供丰富的实验和实训课程，面向人工智能未来技术发展培养具有创新能力和国际视野的高层次拔尖人才。本专业课程体系注重数学基础（微积分、线性代数、数理统计等）和计算机基础（数据结构、程序设计基础等）；在此基础上开设专业课加深人工智能专业理论和技术学习（机器学习、深度学习等），并增加智能硬件与学科交叉特色课程（电路分析与电子线路、数字逻辑电路、智能硬件与交互设计、人工智能芯片设计等）。

本专业涉及包括自然科学、工程技术、信息技术的大量理论知识与技术方法，聚焦行业需求，注重前沿交叉，深耕产学合作，推进产学融合。学生毕业后可以继续攻读相关领域的硕士博士，也可以在人工智能+的行业，诸如智慧医疗、智慧教育、智慧金融、智慧生活、智慧交通、智慧城市、智慧交通等产业从事技术和管理工作。

The rapid development of information technology and industrial revolution triggers strong strategic competition between different countries in AI. As an international base of electronic industries, the Guangdong-Hong Kong-Macau Greater Bay ares harbours huge demands for AI-related talents.

The program of Artificial Intelligence takes advantage of the local industrial resources in electrics and information, pivots around industrial needs to develop an inter-disciplinary education approach. With an eye on the latest of the industry and introducing innovation from industry into university, we aim to build a channel between talent-cultivation and industrial knowledge creation. Through the provision of rich experiment courses and hands-on practice courses, we are dedicated to producing top talents with innovation skills and global outlook that caters to the needs of future AI technology developments. The curriculum system of this program emphasizes solid math foundation (with course such as Calculus, Linear Algebra, Mathematical Statics, etc.) and computational sills (with course such as Data Structure, Programming Fundamentals, etc.). With these foundations, we then add AI theory and technology courses (such as Machine Learning, Deep Learning, etc.) and on top of that, provide intelligent hardware and inter-disciplinary courses (such as Circuit Analysis and Electronic Circuits, Digital Logic Circuits, Intelligent Hardware and Interactive Design, AI Chip Design, etc.).

This program involves courses that introduce rich theoretical knowledge and technical methods in natural science, engineering technology, and information technology. With particular focus on industrial needs and emphasis on an inter-disciplinary approach, we are constantly deepening the industry-university link. Upon graduation, students can choose between pursuing master or doctoral level study and finding technical and managerial jobs in AI+ industries, such as smart healthcare, smart education, smart finance, smart life, smart transportation, smart cities, and smart transportation.

专业特色（Program Features）

人工智能专业依托粤港澳大湾区电子信息产业优势，紧密围绕产业需求，聚焦前沿技术，深入推进及学科交叉与产学融合，打通人工智能与其他学科的联系通道，面向未来技术培养具有创新能力和国际视野的高层次创新人才。

The major of AI takes advantage of the robust industrial development in electronics and information in Guangdong-Hong Kong-Macau Greater Bay Area, produces innovative and international talents that caters to the needs of future technology development with a close examination on industrial needs, latest technology development and under the educational philosophy of promoting inter-disciplinary and industry-university combined learning and teaching.

授予学位（Degree Conferred）

工学学士学位 Bachelor of Engineering

核心课程（Core Courses）

人工智能导论、高级语言程序设计、数据结构、机器学习、数字逻辑电路、信号与系统、数字信号处理、数字图像处理、深度学习与计算机视觉、人工智能系统综合设计、大数据及数据挖掘。

Introduction to Artificial Intelligence, Advanced Language Programming, Data Structures, Foundations of Machine Learning, Digital Logic Circuits, Signals & Systems, Digital Signal Processing, Digital Image Processing, Deep Learning and Computer Vision, Synthetic Design of Artificial Intelligence System, Big Data and Data Mining.

特色课程（Featured Courses）

n 新生研讨课：工程导论I、人工智能导论

n 专题研讨课：人工智能系统综合设计

n 慕课：Python语言程序设计

n 学科前沿课：几何感知与智能、生物启发智能感知、强化学习、自然语言处理、区块链

n 跨学科课程：智能硬件与交互设计、智能传感及穿戴计算、人工智能芯片设计

n 校企合作课：人工智能系统综合设计、智能硬件与交互设计、虚拟现实与增强现实

n 竞教结合：人工智能系统综合设计

n 创新实践课：人工智能系统综合设计

n 创业教育课：人工智能系统综合设计（“三个一”课程）

n 工作坊：智能硬件与交互设计

n 专题设计课：智能硬件与交互设计、人工智能系统综合设计

n 劳动教育课：工程训练I

n Freshmen Seminars: Introduction to Engineering I, Introduction to Artificial Intelligence

n Special Topics: Synthetic Design of Artificial Intelligence System

n MOOC: Introduction to Programming Using Python

n Subject Frontiers Courses: Geometric Perception and Intelligence, Bioinspired Intelligent Perception, Reinforcement Learning, Natural Language Processing, Blockchain

n Interdisciplinary Courses: Intelligent Hardware and Interaction Design, Intelligent Sensor and Wearable Computing, AI Chip Design

n Cooperative Courses with Enterprises: Synthetic Design of Artificial Intelligence System, Intelligent Hardware and Interaction Design, Virtual Reality (VR) and Augmented Reality (AR)

n Contest-Teaching Integrated Courses: Synthetic Design of Artificial Intelligence System

n Innovation Practice: Synthetic Design of Artificial Intelligence System

n Entrepreneurship Courses: Synthetic Design of Artificial Intelligence System (Three ones Courses)

n Workshops: Intelligent Hardware And Interaction Design

n Special Designs: Intelligent Hardware and Interaction Design, Synthetic Design of Artificial Intelligence System

n Labor Education Courses: Engineering Training I

一、各类课程学分登记表（Registration Form of Curriculum Credits）

1.学分统计表（Credits Registration Form）

备注：学生毕业时须修满专业教学计划规定学分，并取得第二课堂3个人文素质教育学分和4个创新能力培养学分。

2.类别统计表（Category Registration Form）

备注：

1.通识课计入选修一项中；

2.实验教学包括“专业教学计划表”中的实验、实习和其他；

3.创新创业教育学分：培养计划中的课程，由各学院教学指导委员会认定，包括竞教结合课程、创新实践课程、创业教育课程等学分；

4.必修学时＋选修学时=总学时数；理论教学学时＋实验教学学时=总学时数；必修学分＋选修学分=总学分数；集中实践教学环节学分＋理论教学学分＋实验教学学分=总学分数

二、课程设置表（Courses Schedule）

备注：学时中其他可以为上机和实践学时。

二、课程设置表（续）（Courses Schedule）

备注：

专业选修课共开设四个课程模块（智能计算、智能硬件、网络安全、跨学科），学生修读通过同一模块中三门或以上课程则达成该模块，学生至少需达成2个课程模块。

创新创业学分认定：学生根据自己开展科研训练项目、学科竞赛、发表论文、获得专利和自主创业等情况申请折算为一定的专业选修课学分（创新研究训练、创新研究实践I、创新研究实践II、创业实践等创新创业课程）。每个学生累计申请为专业选修课总学分不超过4个学分。经学校批准认定为选修课学分的项目、竞赛等不再获得对应第二课堂的创新学分。

学时中其他可以为上机和实践学时。

三、集中实践教学环节（Practice-concentrated Training）

四、第二课堂（Second Classroom Activities）

第二课堂由人文素质教育和创新能力培养两部分组成。

1.人文素质教育基本要求

学生在取得专业教学计划规定学分的同时，还应结合自己的兴趣适当参加课外人文素质教育活动，参加活动的学分累计不少于3个学分。其中新增大学体育教学团队开设课外体育课程，高年级本科生必修，72学时，1学分，纳入第二课堂人文素质教育学分。

2.创新能力培养基本要求

学生在取得本专业教学计划规定学分的同时，还必须参加国家创新创业训练计划、广东省创新创业训练计划、SRP（学生研究计划）、百步梯攀登计划或一定时间的各类课外创新能力培养活动（如学科竞赛、学术讲座等），参加活动的学分累计不少于4个学分。

4.Second Classroom Activities

Second Classroom Activities are comprised of two parts, Humanities Quality Education and Innovative Ability Cultivation.

1) Basic Requirements of Humanities Quality Education

Besides gaining course credits listed in one's subject teaching curriculum, a student is required to participate in extracurricular activities of Humanities Quality Education based on one's interest, acquiring no less than three credits. The advanced undergraduates must complete one of courses of Humanities Quality Education which has seventy-two class hours (it's equivalent to one credit which belongs to Humanities Quality Education Credit of Extracurricular Class) offered by the College Physical Education Teaching Group.

2) Basic Requirements of Innovative Ability Cultivation

Besides gaining course credits listed in one's subject teaching curriculum, a student is required to participate in any one of the following activities: National Undergraduate Training Programs for Innovation and Entrepreneurship, Guangdong Undergraduate Training Programs for Innovation and Entrepreneurship, Student Research Program (SRP), One-hundred-steps Innovative Program, or any other extracurricular activities of Innovative Ability Cultivation that last a certain period of time (e.g. subject contests, academic lectures), acquiring no less than four credits.