#### 所有課程

10801 工程

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
 ♠ Peter V. O'Neil, "Advanced Engineering Mathematics",5th edition,Thomson Brooks/Cole.

【參考書籍】
References

【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 ﻿ 【﻿

10801 工程

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

10801 工程

【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 人文社會

【課程目標
Course Objectives
本課程擬從一個個體經濟概念開始，引領進入不同的應用領域。除了經濟，這門課打算 串接法律學、演化生物學、國際關係等許多學門，希望能幫助非財經本科學生理解經濟 觀念如何應用在多面向問題的分析上。

【課程資訊】
Course Information
 ♠上課時間: 每周三、第5堂至第7堂 (13:20-16:20) ♠上課地點: 台積館 - 孫運璿演講廰  (111教室)

【課程說明 】
Course Description
這門課不想教大家「制式」的經濟分析，而要從一個個體經濟概念開始，引領進入不同 的應用領域。除了經濟，這門課打算串接法律學、演化生物學、國際關係等許多學門， 希望能幫助非財經本科學生理解以下問題：

 1.為什麼要唸經濟思辨？         1a. 什麼是「通識」經濟學？        1b. 為什麼只懂數學的咖能在財經科系招搖撞騙？ 2.需求、供給、完全競爭均衡  延伸閱讀         2a. 生物界的完全競爭 －－ 為什麼海豚聰明又長壽？        2b. 語言演變的競爭規 （原，哪裡來那麼多的「不規則動詞」？ 3.從傳統經濟到創新經濟        3a. 究竟什麼是知識經濟？        3b. 知識研發的特殊角色        3c. 為什麼川普要對「七年後的產品」課稅？ 4.網路經濟時代的競爭        4a. 網路經濟下的競爭與定價        4b. 電子商務的國際競爭 5.生產要素的報酬與分配        5a. 全球化下的「異形」勞資關係        5b. 勞動基準法與罷工 6.所得與財富分配的不均        6a. 該不該課徵遺產贈與稅？        6b. 台灣所得分配不均的幾個觀察        6c. 股利分離課稅，有道理嗎？ 7.國際貿易的理論與挑戰        7a. 川普何時決定貿易戰「收兵」？        7b. 自由貿易之外，政府究竟該不該有「產業政策」？ 8.市場失靈與永續發展        8a. 在市場失靈與政府失靈之間        8b. 從永續發展理念，談「九二共識」的衍生應對 9.資訊經濟學 ﻿       9a.孔雀開屏傳遞了什麼訊息？  ﻿      9b.家族企業裡的訊息不對稱 10.經濟發展過程中家族角色的蛻變        10a. 超級富豪家族成員之間，彼此親近嗎？        10b. 股票投資，為什麼女性比男性厲害？        10c. 土地投資，為什麼台灣男性比女性厲害？ 11.經濟轉型與經濟困境        11a. 中國與蘇聯不同的轉型策略        11b. 從韜光養晦到一帶一路 12.不完全競爭市場        12a. 陸域風電與離岸風電背後的不同故事　　　        12b. 為什麼 Amazon 拿不下紅白葡萄酒的零售市場? 13.國際金融        13a. 台灣的外匯存底        13b. 歐債危機是怎麼回事？
10801 工程

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

【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

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.

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.

Course Material

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

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

【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

【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

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

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.

prerequisite Course

 ♠

Course Material

References

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

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

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

【6/21 @ 109學年度第2學期休學申請截止Last Day to Withdraw from School】   ♠   【6/28 @ 教師送繳應屆畢業生109學年度第2學期成績截止Deadline for 2021 Spring Grade Submission for Graduating Students】   ♠   【6/28 @ 暑假開始Summer Vacation Begins】   ♠   【6/28 @ 暑期班選課及繳費開始(至7月9日止)Course Selection and Fee Paying Begins for Summer Session (6/28-7/9)】   ♠   【7/1 @ 暑期班上課開始Summer Session Begins】   ♠   【7/5 @ 110學年度暑碩專班上課開始、註冊日、休退學及畢業生免繳學雜費截止2021 Summer In-service Master Program Begins; Registration (2021 Summer In-service Master Program)】   ♠   【7/9 @ 教師送繳非應屆畢業生109學年度第2學期成績截止Deadline for 2021 Spring Grade Submission】   ♠   【7/23 @ 110學年度暑碩專班休退學及畢業生退2/3學雜費(學分費)截止Last Day for 2/3 Tuition and Fees Refunded(graduates or full withdrawal of 2021 Summer In-service Master Program)】   ♠   【7/30 @ 109學年度第2學期結束2021 Spring Semester Ends】   ♠   109學年度【暑期學生讀書會】開始申請囉~至7/15止!   ♠   【110-1教師社群】即日起開始申請~110/7/31止   ♠   【6/15資安漏洞預警】Google Chrome瀏覽器存在安全漏洞，請儘速確認並進行更新！   ♠   【6/15-7/2人事室 問卷調查】110年員工子女托育需求及課後照顧需求調查   ♠   【7/26 人事室】科技部111年度(第60屆)補助科學與技術人員國外短期研究案!   ♠