Engineering Mathematics in this class is to teach how to solve differential equations, which are models in many engineering problems. This post-calculus mathematics is needed and used by today's scientists and engineers....

【工程數學一題庫練習】【工程數學講義】

【數位邏輯設計講義!】 

This course introduces the basic concept of data representation and manipulation. 

【課程說明】
     Description of the course

This course introduces the basic concept of data representation and manipulation. We will teach how to solve problems efficiently and effectively by using proper and specific data structures, and organizing series of operations called algorithms to manipulate data to solve the problems. For instance, you will be ble to understand how to use link list and hash function to create block chains.

【前導課程】
     prerequisite Course

【課程教材】
      Course Material 

【參考教材】
      References 

【教學方式】
      Teaching Method 

 【教學進度】
       Schedule

尋找興趣，提早準備，贏在起跑點！！想追求更多課本以外的專業知識嗎？ 清華大學開放式課程為你種植了一座學習資源森林，等你來探索！現在就走進開放式課程的森林，品嚐最甜美的知識果實！

【課程說明】
      Description of the course
This course is about the principles of digital logic and its implementation in circuits and systems. Modern electronics/computer engineers should be able to effectively utilize millions or even billions of logic gates available from advanced semiconductor manufacturing process. Logic design is fundamental to such applications as computer, audio/video/graphics, wired/wireless communication. Some technology from this course will be useful in other courses. For example, finite state machine is essential in compiler design.
   ♠ We will cover the following topics ♠

【課程教材】
      Course Material

 【教學方式】
       Teaching Method

This course is intended for 2nd-year undergraduates in the computer science and other engineering department. In this course, we focus on two main topics, electronics and circuits. 

【課程說明 】
      Description of the course

This course is intended for 2nd-year undergraduates in the computer science and other engineering department. In this course, we focus on two main topics, electronics and circuits. To give students better understanding of the models and circuits of the electronics devices, we will introduce the basic concepts of electric circuits first. It starts from the definition of current, voltage, power and energy. Then it covers the basic circuit components including resister, capacitor, and inductor. We also discuss the basic circuit analysis, such as nodal analysis of resistive circuits, transients in electrical circuits and sinusoidal steady-state circuit behavior.

For electronics section, we will present the diode and MOS field-effect transistor. We will use simple models to describe these electronic devices and their I-V characteristics. Since the majority of electronic circuits today are designed as integrated circuits (ICs),we will discuss how to analyze and design the basic elements of integrated circuits with the emphasis on digital logic designs.

【課程教材】
     Course Material 

【教學方式  】
       Teaching Method
   ♠ Lecture and discussion.

 【教學進度 】
      Schedule

工程數學為一切工程學科的基礎，提供解決工程問題的基本工具。

【課程說明】
      Description of the course
     工程數學為一切工程學科的基礎，提供解決工程問題的基本工具。預修科目為微積分。課程內容包括：

【課程教材】
        Course Material

【參考教材】
         References 

【教學方式】
       Teaching Method

【教學進度】
       Schedule

This course is intended for junior undergraduates in computer science and engineering. In this course, we will introduce the basic concepts of semiconductor devices and applications. Some basic circuit theorems will be introduced as well... 

This course gives a comprehensive, self-contained, and up-to-date introduction to the web/app development. We focus on the development challenges in real-world situations and present guidelines, tools, and best practices. Students are asked to team up and build real, useful applications (websites and/or mobile apps) accessible to the public in the end.

Description 
The classes are divided into three parts. First, we give a primer to web fundamentals such as HTTP, HTML, CSS, and Javascript. We cover different programming paradigms, including the OOP and functional programming. Handy tools such as Git are covered to get students familiar with the project-based and team-based development. In the second part, we introduce modern web development techniques such as responsive design, Bootstrap, ES6/7, React, and Redux. Last, we extend our horizon to the backend and mobile development landscapes by introducing the Node.js, PostgreSQL database system, Amazon Web Services (AWS), and React Native. We also give case studies on how to leverage Machine Learning algorithms to convert raw user data into the AI.
　♠ https://nthu-datalab.github.io/webapp/index.html

Reference Books 

This course is aimed to help the students learn how to program in C. There will be several labs, two midterm exams, one final exam, and the final project, with the following percentages.......

 

Syllabus

Week	Topics	Labs and Exams
1	CH. 1 Getting Ready	Lab #0 2/21 Thu.
2	CH. 3 Data and C	2/28 放假
3	CH. 4 Formatted Input/Output	Lab #1 3/7 Thu.
4	Binary Representations CH. 15 Bit Manipulation
5	CH. 6 Control Statements: Looping	Lab #2 3/21 Thu.
6	CH. 6 Control Statements: Looping CH. 7 Control Statements: Branching	Written Exam  3/28 Thu. @ Delta 109
7	CH. 8 Character I/O and Redirection	4/4 放假
8	CH. 9 Functions	Lab #3 4/11 Thu.
9	CH. 9 Functions
10	CH. 10 Arrays and Pointers	Midterm Exam I  4/25 Thu.
11	CH. 10 Arrays and Pointers
12	CH. 10 Arrays and Pointers	Lab #4 5/9 Thu.
13	Midterm Exercise (5/14)	Midterm Exercise (5/14)
14	CH. 10 Arrays and Pointers Pointers CH. 11 String Functions CH. 12 Memory Management CH. 13 File Input/Output	Term Project Hackathon 5/25 Sat.
15	CH. 12 Memory Management	Lab #5 5/30 Thu.
16	CH. 15 Bit Manipulation CH. 14 Structures CH. 17 Advanced Data Representations
17	CH. 17 Advanced Data Representations	Lab #6 6/13 Thu.

10410講義1      11020程式設計1課程大綱

【Description】
This class introduces the concepts and practices of deep learning. The course consists of three parts. In the first part, we give a quick introduction of classical machine learning and review some key concepts required to understand deep learning.In the second part, we discuss how deep learning differs from classical machine learning and explain why it is effective in dealing with complex problems such as the image and natural language processing. Various CNN and RNN models will becovered. In the third part, we introduce the deep reinforcement learning and its applications.This course also gives coding labs. We will use Python 3 as the main programming language throughout the course. Some popular machine learning libraries such as Scikit-learn and Tensorflow will be used and explained in detials.