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10801 工程
工程數學一
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    


  
【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

 

 

10801 工程
數位邏輯設計
林永隆 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
      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

1. Introduction to computer circuits
2. Two level Combinational Logic
3. Multilevel Combinational Logic
4. Programmable Logic
5. Arithmetic Logic Circuits
6. Sequential Logic Design
7. Sequential Logic Case Studies
8. Finite State Machine Design
9. Finite State Machine Optimization
10. Computer Organization

 

 

【課程教材】
      Course Material

  ♠  Logic and Computer Design Fundamentals, 4th ed Mano & Kime Prentice Hall

 

 【教學方式】
       Teaching Method

   Lecturing
Home work

Machine problem
(Using Verilog Hardware Description Language and its Simulator)
Quiz, Two Midterms and Final Exam

 

10801 工程
電路與電子學
林永隆 教授

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 

   ♠ 

"Electrical Engineering - Principles and Applications",by Allan R. Hambley,
5th Edition.

 

教學方式  
       Teaching Method
   ♠ Lecture and discussion.


 教學進度 
      Schedule

   Chapter  1  Introduction
Chapter 2  Resistive Circuits
Chapter 3  Inductance and Capacitance
Chapter 4  Transients
Chapter 5  Steady-State Sinusoidal Analysis
Chapter 6  Frequency Plots, Bode Plots, and Resonance
Chapter 10  Diodes
Chapter 12  Field-Effect Transistors
Chapter 11  Amplifiers : Specifications and External Characteristics
     
     


10801 工程
電路與電子學一
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

 

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

 

10801 工程
工程數學
蔡仁松 教授

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:

  (1) 一階微分方程式 (4) 聯立微分方程式
  (2) 二階線性微分方程式 (5) 微分方程式級數解
  (3) 高階線性微分方程式 (6) 拉普拉斯轉換

 


【課程教材】

        Course Material

   Erwin Kreyszig, Advanced Engineering Mathematics, 10th edition, 2011, Wiley.


 

【參考教材】
         References 

 ♠ 

Dennis G. Zill, Advanced Engineering Mathematics, 6th edition, Jones & Bartlett Learning.

  

C. Henry Edwards and David E. Penney, Differential Equations and Boundary Value Problems: Computing and Modeling, 5th Edition, 2016, Pearson.

 ♠

Peter V. O'Neil, Advanced Engineering Mathematics, 8th edition, 2017, Thomson Brooks/Cole.


 

【教學方式】
       Teaching Method

 Lectures and labs.

 

 

【教學進度】
       Schedule

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

 

10801 工程
資料結構
蔡仁松 教授

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

  ♠  C/C++ Programming Language



課程教材
      Course Material 

 ♠  Fundamentals of Data Structures in C++, E. Horowitz, S. Sahni, and D. Mehta, 2nd ed., 2006.

 


參考教材
      References 

   Introduction to Algorithms, 3rd ed., by Cormen et al. C++ reference 


教學方式
      Teaching Method 

  Online Lectures + In class discussions


 

 教學進度
       Schedule

1. Basic Concepts
2. Arrays
3. Stacks and queues
4. linked lists
5. Trees
6. Graphs
7. Sorting
8. Hashing
9. Selected related topics

 

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= ilms  
* 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

 

2/19,2/21

CH. 1 Getting Ready

CH. 2 Introducing C

 

Lab #0 2/21 Thu.

2

 

2/26,2/28

CH. 3 Data and C

CH. 4 Formatted Input/Output

2/28 放假

3

 

3/5, 3/7

CH. 4 Formatted Input/Output

Lab #1 3/7 Thu.

4

 

3/12, 3/14

Binary Representations

CH. 15 Bit Manipulation

CH. 5 Operators, Expressions, and Statements

 

5

 

3/19,3/21

CH. 6 Control Statements: Looping

Lab #2 3/21 Thu.

6

 

3/26,3/28

CH. 6 Control Statements: Looping CH. 7 Control Statements: Branching

Written Exam  3/28 Thu. @ Delta 109

7

 

4/2, 4/4

CH. 8 Character I/O and Redirection

4/4 放假

8

 

4/9, 4/11

CH. 9 Functions

Recursion

Lab #3 4/11 Thu.

9

 

4/16, 4/18

CH. 9 Functions

Recursion

 

10

 

4/23,4/25

CH. 10 Arrays and Pointers

Arrays

 

Midterm Exam I  4/25 Thu.

11

 

4/30, 5/2

CH. 10 Arrays and Pointers

Pointers

12

 

5/7, 5/9

CH. 10 Arrays and Pointers

Pointers

Lab #4 5/9 Thu.

13

 

5/14,5/16

Midterm Exercise (5/14)

Midterm Exam II 5/16 Thu.

14

 

5/21, 5/23

CH. 10 Arrays and Pointers

Pointers

CH. 11 String Functions

 

CH. 12 Memory Management

CH. 13 File Input/Output

CH. 14 Structures


Term Project Hackathon 5/25 Sat.

15

 

5/28,5/30

CH. 12 Memory Management

CH. 14 Structures

Lab #5 5/30 Thu.

16

 

6/4, 6/6

CH. 15 Bit Manipulation

CH. 14 Structures

CH. 17 Advanced Data Representations

Linked Lists

 

17

 

6/11,6/13

CH. 17 Advanced Data Representations

Lab #6 6/13 Thu.

18

 

6/18,6/20

No class

 

 

Final Exam 6/20 Thu.


Final Project Demo 6/25 Next Tue.

 
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
  

 

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.

 
 

【 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


 

【 Online Courses 】