理學碩士學位（數據科學） 人工智能應用專業
與FST合作
所有課程都是必修課：
CISC7298 項目報告
（必修）6學分
The Project Report is designed to integrate academic theories and cutting-edge technologies through a comprehensive analysis of a case study or academic project. This approach aims to equip students with a structured methodology for problem-solving, as well as to enhance their professional research and development capabilities and project management expertise. The overarching objective is to bridge the gap between theoretical knowledge and practical application, ensuring that academic insights are effectively translated into real-world solutions. Students may engage in collaborative visits to industrial partners, with the alignment of these visits to their project report topics. These interactions provide students with firsthand insights, enhancing the content and relevance of their project reports.
人工智能應用 專業 必修科目選修表（表A/表B）:
（同一選修表中至少選 3 門。）
表A:
CISC7027 人工智能應用專題
3 學分
This course introduces special topics and advanced technologies in Artificial Intelligence Applications. The detailed contents may change from year to year depending on current developments and teacher specialization.
ECEN7106 應用於智慧物聯網的凸優化
3 學分
This course focuses on convex optimization with applications to wireless communication systems, information theory, signal processing, control systems and machine learning. The first part will be on the theory of convex optimization–recognizing convex sets, convex functions, convex optimization problems and duality. The second part of the course will be on algorithms for solving convex optimization problems. This course is crucial to students and researchers in the above fields of engineering.
ECEN7107 物聯網數據分析
3 學分
This course is an introductory course on data analytics and its application in IoT. It covers three major topics: 1) Primary data analytics theory including classification, regression, principal component analysis, etc.; 2) Hands on data analytics experiences with NumPy, Pandas, Matplotlib, & Scikit-learn packages; and 3) Applications in IOT (with a special example on buildings energy systems), in which comprehensive experiments with real data will be included. In this course, students will learn systematic knowledge on data analytics and Python. They will also gain solid hands-on experiences in using Python to analyze IOT data.
CISC7013 人工智能原理
3 學分
Overview of Artificial Intelligence Application Areas, Languages and Programming Techniques for Artificial Intelligence, Problem Solving, Knowledge-based Systems, Knowledge Representation, Planning, Machine Learning, Natural Language Processing, Genetic Algorithms. Read More
CISC7018 計算機視覺和模式識別
3 學分
This course introduces the fundamentals and advanced topics of pattern recognition for postgraduate students. It emphasizes both theory and applications of pattern recognition. Topics include overviews of general pattern recognition techniques, statistical decision theory, linear discriminant functions, multilayer neural networks, supervised learning, unsupervised learning and clustering, and applications of pattern recognition (such as biometrics and multimedia database retrieval.) Read More
CISC7019 萬維網數據挖掘
3 學分
The course will cover the fundamental concepts, principles and algorithms in the area of Web Mining. It will firstly give an introduction to the concepts of the traditional information retrieval systems and the principles of web search engines, then, the course will extensively discuss techniques and algorithms of web mining, including Link-Base analysis, web page classifications, web advertisement, recommendation algorithms, web information extractions, web image indexing. The course also requires each student to complete a related course project. Read More
CISC7021 應用自然語言處理
3 學分
This course covers both the fundamental and advanced topics in Natural Language Processing(NLP), which deals with the application of computational models to text data. In this course, the core tasks in natural language processing will be examined, including minimum edit distance, language modelling, Nävie Bayes, Maximum Entropy, text classification, sequence labelling, POS tagging, syntax parsing and computational lexical semantics. Modern NLP applications will be explored such as information retrieval, and statistical machine translation. Students will learn how to formulate and investigate research questions on related topics. Read More
CISC7022 大數據處理與分析
3 學分
This course introduces the latest development of data engineering techniques, including data query processing (e.g., multi-dimensional data, sequence data, and spatial-temporal data) in cloud computing and HPC environments. Students will learn study and learn how to formulate and investigate the state-of-the-art problems and solutions on related topics. Read More
CISC7026 深度學習導論
3 學分
The course introduces Deep Learning (DL) basics, methods, and algorithms, with hands-on practice using modern DL library tools (e.g., PyTorch). After the introductory lecture on deep learning, the course first covers the fundamental of neural networks, including universal approximator theory, learning neural networks, backpropagation, optimization, stochastic gradient descent, and tricks on training neural networks, and then focuses on typical neural network architectures, including Convolutional Neural Networks, Recurrent Neural Networks, and Generative Neural Networks.
表 B:
CIVL7045 智慧交通及智能車輛
3 學分
This course explores the cutting-edge field of Intelligent Transportation and Vehicle Systems, focusing on the integration of advanced technologies with transportation and vehicular systems to enhance performance, safety, and sustainability. Topics include autonomous vehicles, traffic management systems, vehicle-to-vehicle communication, and smart infrastructure.
CIVL7022 高級計算方法：原理與應用
3 學分
This is an introductory course on advanced computational methods for civil and coastal dynamical system analysis. The methods are potentially applied to coastal city vulnerability and resilience analysis, system modeling and updating, dynamical system identification, structural reliability and control, statistical analysis and uncertainty quantification, and more. Students will learn foundational knowledge and principles of advanced computational methods. Also, the students will be equipped with exploring state-of-the-art computational tools and methods to enter the corresponding research fields.
CIVL7206 創新建造方法與信息技術應用
3 學分
This course is designed to introduce the concept and application of instrumentation system in Civil Engineering. The following topics will be discussed in the class: (1) Instrumentation systems, Signals and Errors, (2) Characteristics of instruments – Transducers, Noise and Nonlinearity, Static characteristics, Dynamic characteristics, (3) Signal conditioning – Introduction, Operating amplifier, Applications of Op-amps, filtering, (4) Data acquisition – Analog devices, Digital Devices, Sampling Theorem, Nyquist frequency, Quantization error, (5) Noise Reduction – Interference, Shielding, Grounding, Noise mode, Noise elimination or reduction, (6) Instruments and Sensors – Strain gauge, LVDT, Pressure transducer, Load cell (7) Signal Processing – Sampling Theorem, Laplace-transform and Z-transform. Students are expected to obtain knowledge about the background theory and application of different type of instruments used in Civil Engineering.
EMEN7032 智慧理論與工程應用
3 學分
This course introduces the fundamentals of intelligent systems technologies and their broad engineering applications, involving essential topics such as Proportional-Integral-Derivative (PID) control, engineering optimisation, and modeling and control of dynamic systems using neural network techniques. It will introduce the principles of knowledge-based systems, fuzzy logic, artificial neural networks, evolutionary computing and explore how intelligent machines and automation processes could benefit from the application of these technologies. It will also discuss knowledge representation, knowledge acquisition, decision making mechanisms, learning and machine learning, as well as highlight the applications of these technologies in various engineering domains, with particular emphasis on their role in the optimisation of automation processes, control engineering and robotics.
EMEN7039 工程系統預診斷與健康管理
3 學分
This course provides the concepts and methods of prognostics and health management (PHM) of engineering system, which describes PHM techniques and their applications in engineering systems. A variety of tools and techniques for developing health management and monitoring of components and systems will be discussed. Topics related to sensor signal acquisition, data pre-processing techniques, various signals processing methods for feature extraction, machine learning methods and data driven prognostics models. After successfully completing this course, students will have a good understanding of system health monitoring, optimum sensor placement for health assessment, and current challenges and opportunities in the PHM field.
OCES7001 海洋遙感
3 學分
This course is designed to introduce students to important concepts and fundamental principles in remote sensing and applications in oceans and coastal environments. Topics cover sensors, microwaves, image analysis, applications of remote sensing in oceans and coastal area, and application of artificial intelligence in ocean remote sensing.
OCES7005 海洋機器人及應用
3 學分
This course introduces the broad spectrum of marine vehicles and their applications in ocean environments, the fundamental principles of autonomous underwater and surface vehicles, as well as theoretical and practical design considerations for marine robotic systems.