Digital communication is the key technology for modern day’s communication systems. This course aims to familiarize students with the basic techniques of digital communications, including 1. System architecture of digital communication systems 2. Comparisons of analog and digital communications 3. A/D conversion and coding 4. Base-band digital communication 5. Carrier-modulated digital communication.

The contents of automatic Engineering course include broad techniques such as microelectronics, mechanics, optical and computer engineering. Through this effective training, the students will be capable of the special abilities of system design applied in industry field. This course will illustrate some practical examples to deep the concepts of design. The practical exercises in this course should be requested to enhanced the abilities of design and development in automatic engineering.

This course is mainly for everyone to learn how to speak clearly and understand mathematics. In addition to the basic training necessary for all mathematics courses, the concepts it conveys are also widely used in information science. Fields of artificial intelligence, editors, programming languages, and logical semantics in philology.

This course presents the principle, components, current research and application examples in biomechatronics engineering. Topics consist of engineering in biotechnology industry, automation in agricultural, fishery, and animal productions, and biomedical engineering.

Course contents include the safety of workshop, the use of measuring tools, tool grinding, bench work, welding, paint work, pipe work, electrical work, concrete work, sheet material work and developing etc. Match up the program training students to learn the skill which they will work in the plant, course contents include the safety of workshop, the use of measuring tools, tool grinding, bench work, welding, paint work, pipe work, electrical work, concrete work, sheet material work and developing etc.

This course aims to enable students to electronic control, machinery, sensors, controllers and other components commonly used in the industry, and to learn how to read sensor signals or control external parts by using communication methods commonly used in the industry, so that students can have the basic ability of mechanical and electrical integration.

本課程期待培養學生於影像處理、電腦視覺及深度學習領域技術設計及整合實作的能力，透過務實的作業實例來培育學生具備研發思考、程式設計及解決現存問題的能力，藉由分組計劃的實作來培養學生具備發現問題、解決問題及團隊分工合作的能力與精神，並可把所學的理論基礎應用到工業界、臨床醫學影像處理及精準運動的實務面。 Computer Vision and Image Processing 3 E C. Y. Chen This course is expected to cultivate students' abilities in technical design and integrated practice in the fields of image processing, computer vision and deep learning. Through practical work examples, students will be cultivated to have the ability of R&D thinking, programming and solving existing problems. The practice is to train students to have the ability and spirit of discovering problems, solving problems, and teamwork division and cooperation, and can apply the theoretical foundations they have learned to the practical aspects of industry, clinical medical image processing and precision sports.

This course uses C++ to demonstrate the programming concept, instruction and algorithm. Topics include introduction of integrate development environment, fundamental process of programming, object-oriented programming, etc….

In addition to programming technique, the principle and techniques of digital image processing will be presented in this course. The digital image data structure, transforming methods, image enhancing technique and features extraction are the issues presented in this course. The open source tools for digital image processing and applications in agriculture and biology are introduced as well.

This course provides an overview for Python beginners, how to set up Python on your computer, Python variables, Python comments, reading, machine learning and writing files in Python.

According to the development of Agriculture 4.0, the ecology of farming has gradually changed from traditional manpower to automation, unmanned, intelligent and spatial three-dimensional. Among them, the application of unmanned vehicles is a major trend. This course introduces the current development of smart agriculture and unmanned vehicles, the application of remote-control vehicle, the operation of remote -control aircraft, GPS application, and the integration of IoT. Moreover, the application of remote-control unmanned fixed-wing and multi-rotor aircraft and license examination exercises are also the focus of the course.

The theme of this course is the analysis of electric circuits. Especially D.C-circuits and A.C-circuits. The theory of magnetism and its application will be also discussed. The various components and interconnection of an electrical system comprise what is described as an electric circuit, and a circuit diagram is a graphic representation of an electric circuit. It provides the basic concept of electric circuits.The laboratory main topics of this course includes: Use of meters (AV)；DC. AC. Voltage；Resistor and Ohm’s Law；Serial and Parallel circuit and Kirchhoff’s law；Super position theory；DC power testing and maximum power output testing；RLC in Series (resonance)；RLC in parallel；.LC pass-filter testing；Characteristics of Transformer Testing；Thermal Resistor and Thermo-control circuit testing； Oscilloscope Training; AC-DC Testing； Speed and power of a motor；Generator；Fundamental Design of Transmission and Distribution system。

1. Possess the integration principles and basic skills of building intelligent home monitoring, and actively face and solve various problems in the workplace with systematic thinking and the use of scientific and technological information. 2. Capable of controlling, designing and applying technology for lighting, energy saving, electrical and environment, and actively face and solve various problems in the workplace with systematic thinking and the use of scientific and technological information. 3. With the design and application technical capabilities of access control, disaster prevention and monitoring, and remote home smart control, it demonstrates the ability of maintenance and repair and the quality of problem solving. 4. Understand the smart home monitoring factory facilities, and understand the related knowledge of industrial safety and sanitation and fire safety, 5. Have the understanding and practice of occupational safety and sanitation knowledge at work, and show a good working attitude and sentiment. Be able to contemplate labor laws, regulations and related issues, and reflect on self's social responsibility.

This course teaches AI infrastructure from the shallower to the deeper, step by step, and lays the foundation for AI learning. It is a compulsory course for stepping into the door of AI learning. You will learn data processing Python suites (Numpy, Pandas, Scipy, Matplotlib, Seaborn...); learn to use scikit-learn to implement machine learning algorithms (Regression, Decision Forest, KNN or Kmeans, etc.) in application topics, and verify models Performance and parameter tuning to optimize the model; learn to use Keras/TensorFlow to build deep neural networks, such as Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Reinforcement Learning, and Generative Confrontation Internet (Generative Adversarial Networks), etc., to realize artificial intelligence topics such as face recognition and natural language dialogue.