Overview Discrete Mathematics and Its Applications Baojian Hua

Slides:



Advertisements
Similar presentations
Computer Science 20 Discrete Mathematics for Computer Science All the Math you need for your Computer Science courses that you won’t learn in your Math.
Advertisements

Introduction to CS170. CS170 has multiple sections Each section has its own class websites URLs for different sections: Section 000:
CS 581: Introduction to the Theory of Computation Lecture 1 James Hook Portland State University
CS/CMPE 535 – Machine Learning Outline. CS Machine Learning (Wi ) - Asim LUMS2 Description A course on the fundamentals of machine.
About the Course Lecture 0: Sep 2 AB C. Plan  Course Information and Arrangement  Course Requirement  Topics and objectives of this course.
CS 331 / CMPE 334 – Intro to AI CS 531 / CMPE AI Course Outline.
COMP171 Data Structures and Algorithm Huamin Qu Lecture 1 (Sept. 1, 2005)
CSC 171 – FALL 2004 COMPUTER PROGRAMMING LECTURE 0 ADMINISTRATION.
COMP171 Data Structures and Algorithm Qiang Yang Lecture 1 ( Fall 2006)
EE 220 (Data Structures and Analysis of Algorithms) Instructor: Saswati Sarkar T.A. Prasanna Chaporkar, Programming.
Overview Discrete Mathematics and Its Applications Baojian Hua
COMP152 Object-Oriented Programming and Data Structures Spring 2011.
Welcome to CSCA67 Discrete Mathematics for Computer Scientists
CS 581: Introduction to the Theory of Computation Lecture 1 James Hook Portland State University
Overview C and Data Structures Baojian Hua
1 SWE Introduction to Software Engineering Fall Semester (081) King Fahd University of Petroleum & Minerals Information & Computer Science.
COMP 151: Computer Programming II Spring Course Topics Review of Java and basics of software engineering (3 classes. Chapters 1 and 2) Recursion.
WEEK 1 CS 361: ADVANCED DATA STRUCTURES AND ALGORITHMS Dong Si Dept. of Computer Science 1.
© 2004 Goodrich, Tamassia CS2210 Data Structures and Algorithms Lecture 1: Course Overview Instructor: Olga Veksler.
Computer Network Fundamentals CNT4007C
Cpt S 471/571: Computational Genomics Spring 2015, 3 cr. Where: Sloan 9 When: M WF 11:10-12:00 Instructor weekly office hour for Spring 2015: Tuesdays.
About the Course Lecture 0: Sep 10 AB C. Plan  Course Information and Arrangement  Course Requirement  Topics and objectives of this course.
COMP Introduction to Programming Yi Hong May 13, 2015.
CS 103 Discrete Structures Lecture 01 Introduction to the Course
Computer Networks CEN 5501C Spring, 2008 Ye Xia (Pronounced as “Yeh Siah”)
Introduction to Network Security J. H. Wang Feb. 24, 2011.
CPS120: Introduction to Computer Science Fall: 2002 Instructor: Paul J. Millis.
Object Oriented Programming (OOP) Design Lecture 1 : Course Overview Bong-Soo Sohn Associate Professor School of Computer Science and Engineering Chung-Ang.
CST 229 Introduction to Grammars Dr. Sherry Yang Room 213 (503)
Introduction to Discrete Mathematics J. H. Wang Sep. 14, 2010.
CSC Discrete Mathematical Structures Dr. Karl Ricanek Jr.
Overview Algorithms Baojian Hua
Introduction to Data Structures
CSE 3358 NOTE SET 1 Data Structures and Algorithms.
Discrete Mathematics CS204 Spring CS204 Discrete Mathematics Instructor: Professor Chin-Wan Chung (Office: Rm 3406, Tel:3537) 1.Lecture 1)Time:
Welcome to CMPSC 360!. Today Introductions Student Information Sheets, Autobiography What is Discrete Math? Syllabus Highlights
Course Information Sarah Diesburg Operating Systems COP 4610.
Course Information Andy Wang Operating Systems COP 4610 / CGS 5765.
Course Introduction Andy Wang COP 4530 / CGS 5425 Fall 2003, Section 4.
CSE 3358 NOTE SET 1 Data Structures and Algorithms.
Object Oriented Programming (OOP) Design Lecture 1 : Course Overview Bong-Soo Sohn Associate Professor School of Computer Science and Engineering Chung-Ang.
Introduction COMP283 – Discrete Structures. JOOHWI LEE Dr. Lee or Mr. Lee ABD Student working with Dr. Styner
CPS120: Introduction to Computer Science Winter 2002 Instructor: Paul J. Millis.
Introduction to ECE 2401 Data Structure Fall 2005 Chapter 0 Chen, Chang-Sheng
June 19, Liang-Jun Zhang MTWRF 9:45-11:15 am Sitterson Hall 011 Comp 110 Introduction to Programming.
CS Welcome to CS 5383, Topics in Software Assurance, Toward Zero-defect Programming Spring 2007.
ICS202 Data Structures King Fahd University of Petroleum & Minerals College of Computer Science & Engineering Information & Computer Science Department.
Class Info. Course Website Full version of syllabus will be available there as well.
CMSC 2021 CMSC 202 Computer Science II for Majors Spring 2002 Sections Ms. Susan Mitchell.
CMSC 2021 CMSC 202 Computer Science II for Majors Spring 2001 Sections Ms. Susan Mitchell.
1 CS 381 Introduction to Discrete Structures Lecture #1 Syllabus Week 1.
Data Structures and Algorithms in Java AlaaEddin 2012.
COP4020 INTRODUCTION FALL COURSE DESCRIPTION Programming Languages introduces the fundamentals of the design and implementation of programming languages.
Computer Networks CNT5106C
Course Information CSE 2031 Fall Instructor U. T. Nguyen /new-yen/ Office: CSEB Office hours:  Tuesday,
CS 225 Discrete Structures in Computer Science Winter, 2014: 157 Spring, 2014: 151 Summer, 2014: Two sections 97 and 53.
Course Overview Stephen M. Thebaut, Ph.D. University of Florida Software Engineering.
1 Computer Science 1021 Programming in Java Geoff Draper University of Utah.
Computer Science 20 Discrete Mathematics for Computer Science 1 All the Math you need for your Computer Science courses that you won’t learn in your Math.
RAIK 283 Data Structures and Algorithms
Welcome to CS 4390/CS5381: Introduction to Formal Methods
Course Overview CS 4501 / 6501 Software Testing
Robotics – Syllabus and Logistics
COMP 283 Discrete Structures
Artificial Intelligence (CS 461D)
CS 201 – Data Structures and Discrete Mathematics I
CS 201 – Data Structures and Discrete Mathematics I
Automata and Formal Languages
26 July 2011 SC 611 Class 1.
CMPUT101: Purpose of the Course
Presentation transcript:

Overview Discrete Mathematics and Its Applications Baojian Hua

What ’ s this course about? Discrete mathematics: basic concepts and results theory-oriented Applications: heavily used in many fields focus on computer science project-oriented

Is this Course Important? Knowledge preparation (CS) Data structure, algorithms design & analysis, data base, computability & complexity, … Discrete mathematics itself is an amazing subject full of beautiful & elegant results Improve our thinking Not only in computer science Start point for current research We ’ ll cover some state-of-the-art research projects and open problems

Who are We? Instructor: Hua, Baojian 302 in Mingde buiding Office hour: at every class, or to appoint TAs: Wang, Xi: Feel free to contact us for help :-)

Course Page Home page Course administrative Lecture notes Programming assignments Softwares Test and evaluation issues Check that page frequently Join the Google discussion group To be announced

Textbooks and References There are no required textbooks for this course None of them is as of the sufficient depth and width as we ’ d cover Instead, we ’ ll choose topics from various sources, see the course web page for some recommended references We ’ ll rely heavily on lecture notes Attend the class

Contents We ’ ll Cover (tentative) Inductive definition & structural induction Map, set, function, relation Counting Logic Syntax, semantics, soundness and completeness Constructive logic, Curry-Howard isomorphism Case studies & applications Graph and Trees Computability Formal language, automaton, lambda calculus

Homework Part theory, part practice theory on paper practice in code in whatever language you love Policy: Solve them independently Late homework should only be considered under extraordinary circumstances Submit to TAs

Programming Assignments Two purposes: Get more familiar with the theory in another way You understand it, if you can teach it to the computer See the applications of theory (in computer science) Approximately 1/every two weeks Solve them independently or a group of two Submitted to TAs

Test and Evaluation Policy for the final test: Close book Score evaluation: 20% homework 30% projects 50% test Be concerned this course is more profitable and illuminating (and exciting) than you may assume

Any question?