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10801 工程
電路與電子學
王俊堯 教授

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... 

 

【課程簡述】 
     Brief course description  
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. 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. 
 

 
【課程說明】
     Course Description 
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. 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. 
  
 
 【指定 / 參考書籍】  
       Text Books / References
  Electronic Circuit analysis and Design X Ed. by Donald A. Neamen 
Electrical Engineering - Principles and Applications 4th Ed.
   by Allan R. Hambley  
  
 

 【教學方式】    
      Teaching Method 
以講授為主,輔以白板說明
  The cousres are mainly based on lectures and supplemented by whiteboard explanations
 
點閱次數:547858
10801 工程
工程數學
王俊堯 教授

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....

 

【課程說明】
       Course Description
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. It will cover the following topics: 

     1 First order differential equations 
     2 Second order differential equations
     3 Laplace transform 
     4 Series solutions for differential equations 
     5 Systems of differential equations 
     6 Fourier series
  
 

 
【指定用書】
        Textbooks    
♠ 

5th edition,Thomson Brooks/Cole. 
 
 
  
【參考書籍】
       References     
  Erwin Kreyszig, "Advanced Engineering Mathematics",  8th edition, Wiley. 
 
  
【教學方式】
       Teaching Method     
 Lecture with white boarding writing 
 
  

【教學進度】
        Syllabus 
1  First order differential equations 
2 Second order differential equations 
3 Laplace transform 
4 Series solutions for differential equations 
5 Systems of differential equations 
6 Fourier series 
  

 

【工程數學一題庫練習工程數學講義

 

點閱次數:991646
10801 工程
數位邏輯設計
王俊堯 教授
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!
  
 
 

【課程大綱
 
     What do you expect to learn in this course  

 1    Introduction Number systems and Conversion
 2    Boolean Algebra
 3    Boolean Algebra (Continued)
 4    Application of Boolean Algebra  Minterm and Maxterm Expansion
 5    Karnaugh Maps
 6    Quine-McClusky Method
 7    Multi-Level Gate Circuits  NAND and NOR Gates
 8    Combinational Circuit Design and Simulation Using Gates
 9    Multiplexers, Decoders, and Programmable Logic Devices
 10    Flip-Flops
 11    Registers and Counters
 12    Analysis of Clocked Sequential Circuits
 13    Derivation of State Graph and Table
 14    Reduction of State Tables  State Assignment16

 

 
 【指定用書】 
           Textbook 

  Fundamentals of Logic Design (7th Edition International Edition) by Charles H. Roth, Jr. and Larry L. Kinney(CENGAGE Learning) 滄海圖書代理
  ISBN-10: 1133628486
ISBN-13: 9781133628484

 
 

 

數位邏輯設計講義!】 

點閱次數:684278
10702 工程
Web Programming, Technologies, and Applications
吳尚鴻 教授

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


 
 

Syllabus 
Lecture 01 HTTP&HTML
Lecture 02 CSS
Lecture 03 Bootstrap and Responsive Design
Lecture 04 Javascript & DOM
Lecture 05 Modern Javascript
   


 

Reference Books 

Alexander Osterwalder, Business Model Generation: A Handbook for 
  Visionaries, Game Changers, and Challengers, 2010
Eric Ries, The Lean Startup: How Today's Entrepreneurs Use Continuous 
  Innovation to Create Radically Successful Businesses, 2011
Peter Thiel, Blake Masters, Zero to One: Notes on Startups, or How to Build
  the Future, 2014
   
   
點閱次數:90136
10702 工程
深度學習
吳尚鴻 教授
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......
 
  

【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.

 
 

【Syllabus】  
Lecture 01  
Introduction/Scientific Python 101
Lecture 02     
Linear Algebra/Data Exploration & PCA
Lecture 03
Probability & Information Theory/Decision Trees & Random Forest

Lecture 04

Numerical Optimization/Perceptron & Adaline/Regression
Lecture 05
Learning Theory & Regularization /Regularization
Lecture 06
Probabilistic Models/Logistic Regression & Metrics 
Lecture 07
Non-Parametric Methods & SVMs/SVMs & Scikit-Learn Pipelines
Lecture 08
Cross Validation & Ensembling/CV & Ensembling

 

Competition01  

Predicting Appropriate Response
Lecture 09
Large-Scale Machine Learning
Lecture 10
Neural Networks: Design/TensorFlow101 & Word2Vec
Lecture 11
Neural Networks: Optimization & Regularization
Lecture 12

Convolutional Neural Networks/Nuts and Bolts of Convolutional Neural Networks/Visualization and Style Transfer

 

Competition 02

Image Object Detection & Localization

Lecture 13

Recurrent Neural Networks/Seq2Seq Learning for Machine Translation
Competition 03 Image Caption
Lecture 14
Unsupervised Learning/Autoencoders/GANs
Competition 04 Reverse Image Caption 
Lecture 15
Semisupervised/Transfer Learning and the Future
Lecture 16
Reinforcement Learning/Q-learning
Lecture 17
Deep Reinforcement Learning/ DQN & Policy Network
Competition 05 You Draw I Draw
   
 

 

【Reference Books】 
Ian Goodfellow, Yoshua Bengio, Aaron Courville, Deep Learning, MIT Press, 2016, ISBN: 0387848576
Trevor Hastie, Robert Tibshirani, Jerome Friedman, The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition, Springer, 2009, ISBN: 0387848576
Christopher M. Bishop, Pattern Recognition and Machine Learning, Springer, 2006, ISBN: 0387310738
Sebastian Raschka, Python Machine Learning, Packt Publishing, 2015, ISBN: 1783555130
  
 
 
 
【Online Courses】  
CS231n: Convolutional Neural Networks for Visual Recognition, Stanford
 CS224d: Deep Learning for Natural Language Processing, Stanford
CS 294: Deep Reinforcement Learning, Berkeley
 MIT 6.S094: Deep Learning for Self-Driving Cars, MIT
   
點閱次數:339189
10702 工程
計算機程式設計一(資工版)
陳煥宗 教授

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.......

  

Text Books 
 S. Prata, C PRIMER PLUS 
 Lecture notes 
  https://github.com/htchen/i2p-nthu/tree/master/程式設計一
 清大開放課程影片(17週)
  http://ocw.nthu.edu.tw/ocw/index.php?page=course&cid=134
 
 
 
  
 Reference  
 Essential C
  http://cslibrary.stanford.edu/101/EssentialC.pdf
 The C Book
  http://publications.gbdirect.co.uk/c_book/the_c_book.pdf 


MIT: A Crash Course in C

  http://www.mattababy.org/~belmonte/Teaching/CCC/handouts.pdf
  MIT: A Crash Course in C
  Reference Manual
  http://www.gnu.org/software/libc/manual/html_mono/libc.html
 
 
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.





 
點閱次數:179138
10701 工程
平行程式
周志遠 教授

本課程將介紹平行計算的基礎觀念和電腦系統架構,並教授針對不同平行計算環境所設計的程式語言,包括多核心系統使用的 Pthread、OpenMP, 叢集計算使用的MPI, GPU使用的CUDA, 以及分散式系統使用的MapReduce計算框架。修課同學必須使用 這些平行計算的語言和工具完成5個程式作業,並且以程式的執行效能結果作為學習的評量標準。 

 

 

【課程說明 】
                  Course Description       
           本課程將介紹平行計算的基礎觀念和電腦系統架構,並教授針對不同平行計算環境所設計的程式語言,包括多核心系統使用的 PthreadOpenMP, 叢集計算使用的MPI, GPU使用的CUDA, 以及分散式系統使用的MapReduce計算框架。修課同學必須使用 這些平行計算的語言和工具完成5個程式作業,並且以程式的執行效能結果作為學習的評量標準。 

 
 

【指定用書 
           Textbooks

♠  Parallel Programming– 

Techniques and applications Using Networked Workstations and Parallel Computers, Barry Wilkinson and Michael Allen, Prentice Hall, 1999. 
Parallel Programming in C with MPI and OpenMP, Michael J. Quinn, 

McGraw- Hill, 2003. 
Intel Multi-Core Programming 

      

 

【參考書籍   】
        References

♠  Documentation

(PVM, MPI, Cilk, Pthread, TreadMark, SAM) 
Designing and Building Parallel Programs, Ian Foster, Addison Wesley, 1995. 


 

 

【教學進度】
        Syllabus

Part I Introduction 
       - Introduction to Parallel Computers  
     - Introduction to Parallel Computing 
 
Part II  Parallel Programming
 
     - Message-Passing Programming (MPI)  
     - Shared Memory Programming (Pthread and OpenMP) 
 
Part III  Parallel Computing Techniques 
       - Embarrassingly Parallel Computations  
     - Partitioning and Divide-and-Conquer Strategies  
     - Pipelined Computations  
     - Synchronous Computations  
     - Load Balancing and Termination Detection 
 
 Part IV  GPU Programming 
      - Heterogeneous computing  
    - CUDA programming model  
    - GPU Architecture & Multi-GPU  
    - Advanced CUDA Programming & Optimization 
 
 Part V  Distributed Programming 
      - MapReduce  
    - Hadoop Programming 

  

點閱次數:272377
10701 人文社會
台灣的水文
陳鸞鳳 教授

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! NTHU Open Courses Ware has planted a learning-material forest, now it’s waiting for you to explore! Now, go into the OCW forest, and taste the sweetest knowledge fruits.

 

【課程說明】 
      Course Description 

【   周   次  】  【           教        學        內         容         】 
第  1  講 地球上的水與台灣水資源


The Water on Earth and the Water Resources in Taiwan
第  2  講 地下水


Groundwater

第  3  講 水資源的保育 


Conservation of Water Resources
第  4   台灣的陂塘

 

Ponds in Taiwan
第  5   水的議題 

 

Issues of Water

 

點閱次數:26406
10701 人文社會
台灣的地名
陳鸞鳳 教授

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】

      Course Description 

周 次   【            教            學          內            容       】 


 
* 1-1 地名的特性、結構與分類
             
Characteristics, Structure, and Catalogs of Toponomy
 
* 1-2 地名的演變
                Evolution of Toponomy
 
* 1-3 跟農業有關的地名 
               Toponomy related to Agriculture

* 1-4 以動植物命名的地名
                The Toponomy Using Names of Animals and Plants

 
 


 
 
* 2-1 從地圖上認識台灣的地名
             Knowing Names of Places in Taiwan through Maps 
 
* 2-2 跟族群有關的地名 
               Names of Places Related to Ethnic Group 
 
* 2-3 從地圖上認識台灣的其他地名
         Knowing Other Names of Places in Taiwan through Maps
 
* 2-4 台灣堡圖中的舊地名(一) 
                Old Names of Places in Earlier Topographic Map in Taiwan(I)

* 2-5 台灣堡圖中的舊地名(二)
                Old Names of Places in Earlier Topographic Map in Taiwan(II)
 

 

點閱次數:40900
10602 自然科學
高等微積分二
高淑蓉 教授
本課程以訓練嚴謹的邏輯推導、撰寫明確的證明、流利的口語表達為手段,追求如何思考、如何有效的學習為目標。This course is based on teaching you how to think logically, how to prove clearly and express yourself fluency.Also,how to think and how to learn effectively and the goals of this course.
 
 
【課程簡述】
       Brief course description 
       本課程以訓練嚴謹的邏輯推導、撰寫明確的證明、流利的口語表達為手段,追求如何思考、如何有效的學習為目標。 
This course is based on teaching you how to think logically, how to prove clearly and 
express yourself fluency.Also,how to think and how to learn effectively and the goals of this course.
  
  
【課程說明】
       Course Description 
         本課程以訓練嚴謹的邏輯推導、撰寫明確的證明、流利的口語表達為手段,追求如何思考、如何有效的學習為目標。本課程內容探討歐幾里德空間的多變數函數之解析理論。本學期將介紹以下題材: 
    This course is based on teaching you how to think logically, how to prove clearly and express yourself fluency.Also,how to think and how to learn effectively and the goals of this course.The content of this course includes  the analysis of the multivariable functions in Euclidean space. The following topics are introduced in this semester:  
 1. Differentiable Mappings 
 2. The Inverse and Implicit Function Theorems and Related Topics 
 3. Integration 
 4. Fubini's Theorem and The Change of Variables Formula 
 5. Fourier Analysis 
 
 
 
【指定用書】
        Text Books  
 J. E. Marsden and M. J. Hoffman, Elementary Classical Analysis,  

 second edition.
 
 
【參考書籍】
        References    
D. Widder, Advanced Calculus. 

T. Apostal, Advanced Calculus. 


【教學方式/教學進度】
       Teaching Method / Syllabus
 黑板授課/循序漸進 

 Teaching with Blackboard / Step by step

點閱次數:309772
【10/17-12/2 Calendar】期中教學意見反映週(至12月2日止) Mid-term Feedback on Teaching (10/17-12/2)!   ♠   【10/31 -12/16 Calendar】期中成績預警開始(至12月16日止)Academic Warning System Starts Sending out Alert (10/31-12/16)   ♠   【11/30 Calendar】教師進修及休假研究申請案送人事室截止Deadline for Faculty’s Sabbatical Leave Application   ♠   【12/2 Calendar】休退學及畢業生退1/3學雜費(學分費)截止Last Day for 1/3 Tuition and Fees Refunded(graduates or full withdrawal)   ♠   【12/5-12/9 Calendar】申請111學年度第2學期學雜費減免開始(至9日止)   ♠   【12/9-1/8 Calendar】教學意見調查開始(至112年1月8日止)Online Course Evaluation (12/9-1/8)   ♠   【12/22 Calendar】111學年度第2學期第1次選課開始(至26日止)1st Course Selection Period for 2023 Spring Semester (12/22-12/26)   ♠   【1/1 Calendar】 開國紀念日New Year's Day (no class)!   ♠   【1/2 Calendar】開國紀念日補假Holiday-New Year's Day (no class)1   ♠   【1/9 Calendar】期末考試開始(至13日止)Final Exams (1/9-1/13)!   ♠   【1/13-1/15 Calendar】111學年度第2學期第3次選課開始(至15日止)3rd Course Selection Period for 2023 Spring Semester (1/13-1/15)   ♠   【1/16 Calendar】寒假開始Winter Break Begins!   ♠   【1/20 Calendar】春節彈性放假Holiday-Chinese New Year!   ♠   【1/21 Calendar】除夕Chinese New Year’s Eve!   ♠   【1/22-1/27 Calendar】春節及春節彈性放假(至27日止)Chinese New Year (1/22-1/27)   ♠   【10/17 Calendar】期中教學意見反映週(至12月2日止) Mid-term Feedback on Teaching (10/17-12/2)   ♠   【9/16 Calendar】教師提出更改110學年度第2學期學生成績截止Deadline for 2022 Spring Semester grade adjustments   ♠   【10/17 Calendar】期中教學意見反映週(至12月2日止) Mid-term Feedback on Teaching (10/17-12/2)   ♠