This document provides an introduction to the CS150 course at the University of Virginia. It discusses what computer science is, comparing it to fields like science, engineering, and liberal arts. It introduces some of the main themes that will be covered, including recursive definitions and how language and definitions can recursively refer to themselves. It also outlines expectations for the course and provides some background context.
This document provides an overview of a computer science course being taught at the University of Virginia. It discusses what computer science is, comparing it to science, engineering, and the liberal arts. It outlines the course's roadmap from Euclid to modern topics like quantum computing and the World Wide Web. It also provides information about course resources, expectations, and assignments.
What is Computer Science?
Computer Science and the Liberal Arts
The Apollo Guidance Computer
Recursive Definitions and hippopotomonstrosesquipedaliophobia
Logic and mathematics history and overview for studentsBob Marcus
Math and logic overview for students. Covers a wide range of topics including algorithms, proofs, probability, networks, number theory, statistics, causality, WolframAlpha, and Python programs.
A programming language is a mathematical theory. It includes concepts, notations, definitions, axioms and theorems, which help a programmer to develop a ..
Deep Learning with Python: Getting started and getting from ideas to insights in minutes.
PyData Seattle 2015
Alex Korbonits (@korbonits)
This presentation was given July 25, 2015 at the PyData Seattle conference hosted by PyData and NumFocus.
This lecture introduces VLSI design and biosensors. It discusses why VLSI design is interesting, focusing on applications like biosensors. The general idea of a biosensor is explained, including how fluorescence and voltammetry detection work. The lecture outlines the course, which will cover VLSI economics, design flows, hierarchical design methods, performance bottlenecks, and more. Students will complete three lab exercises involving register file design, ALU design, and bus controller design using EDA tools like Cadence and Synopsys. A brief history of transistors and integrated circuits is also provided.
This document provides an introduction to the CS150 course at the University of Virginia. It discusses what computer science is, comparing it to fields like science, engineering, and liberal arts. It introduces some of the main themes that will be covered, including recursive definitions and how language and definitions can recursively refer to themselves. It also outlines expectations for the course and provides some background context.
This document provides an overview of a computer science course being taught at the University of Virginia. It discusses what computer science is, comparing it to science, engineering, and the liberal arts. It outlines the course's roadmap from Euclid to modern topics like quantum computing and the World Wide Web. It also provides information about course resources, expectations, and assignments.
What is Computer Science?
Computer Science and the Liberal Arts
The Apollo Guidance Computer
Recursive Definitions and hippopotomonstrosesquipedaliophobia
Logic and mathematics history and overview for studentsBob Marcus
Math and logic overview for students. Covers a wide range of topics including algorithms, proofs, probability, networks, number theory, statistics, causality, WolframAlpha, and Python programs.
A programming language is a mathematical theory. It includes concepts, notations, definitions, axioms and theorems, which help a programmer to develop a ..
Deep Learning with Python: Getting started and getting from ideas to insights in minutes.
PyData Seattle 2015
Alex Korbonits (@korbonits)
This presentation was given July 25, 2015 at the PyData Seattle conference hosted by PyData and NumFocus.
This lecture introduces VLSI design and biosensors. It discusses why VLSI design is interesting, focusing on applications like biosensors. The general idea of a biosensor is explained, including how fluorescence and voltammetry detection work. The lecture outlines the course, which will cover VLSI economics, design flows, hierarchical design methods, performance bottlenecks, and more. Students will complete three lab exercises involving register file design, ALU design, and bus controller design using EDA tools like Cadence and Synopsys. A brief history of transistors and integrated circuits is also provided.
The document discusses basic science process skills like observing, inferring, measuring, classifying, predicting and communicating. It provides examples of activities to identify observations versus inferences and how to measure and classify objects. The document also covers the basics of static electricity including charging objects by friction, attractions and repulsions of charged materials, and practical applications like photocopiers.
This presentation contains my one day lectures which introduces fuzzy set theory, operations on fuzzy sets, some engineering control applications using Mamdamn model.
This document outlines a presentation about helping students write arguments using claims, evidence, and reasoning. The presentation introduces the claims-evidence-reasoning framework, provides examples of how it applies to different science disciplines, and offers strategies for implementing it in the classroom. These include engaging students in generating claims and evidence before writing, using transition words to connect ideas, and providing rubrics or peer review to give feedback on student work. The goal is to teach students to structure arguments like scientists by making claims and supporting them with logical reasoning and evidence.
01 Course Intro, Administrative, Etc After ClassSteve Koch
This document provides an introduction and overview for a Physics 102 course. It outlines the instructor's background, contact information, course goals and topics. Key aspects include:
- The course aims to teach physics concepts with minimal math for non-science majors.
- Students will use iClickers for in-class participation and four exams will determine 90% of the final grade.
- The first homework assignment is to read the syllabus on the course website by the next class.
- Technical support is available through the listed teaching assistant.
What knowledge bases know (and what they don't)srazniewski
This document discusses knowledge bases and their completeness and recall. It begins by introducing knowledge bases and some examples of factual knowledge bases that have been created. It then discusses how knowledge bases are useful for question answering and language generation. However, it notes that knowledge bases know only a small portion of what is actually true. It discusses several approaches that have been used to assess knowledge base completeness, including rule mining to predict completeness based on patterns in the data, information extraction to add new facts, and analyzing data presence to estimate completeness of single-value properties. The document outlines challenges with each of these approaches and aims to better understand what knowledge bases are approximating in order to improve assessments of their recall.
This document provides an overview of the CS101 Introduction to Computing course. It discusses the course contents and structure, which will cover fundamental computing concepts, web page development, and productivity software over 15 weeks. Students will complete assignments, a midterm exam, and a final exam. The first assignment requires students to email the instructor about their future plans and post a message on the course message board about customizing the class material. Upcoming lectures will discuss the history of computing from Babbage's Analytical Engine to modern computers.
This document outlines the structure and content of a university module on research questions and design. It discusses administrative details like communication methods and expectations. It describes the format of weekly classes, assignments, and required readings. Common dissertation failures like inadequate research questions or methods are also addressed. Students complete short writing exercises to demonstrate understanding of key concepts like qualitative vs. quantitative research. The importance of well-designed research and answerable questions is emphasized.
This document contains instructions and content for an English language exam consisting of multiple choice questions, word and phrase completion tasks, and an essay prompt. It provides guidelines on how to format responses, specifies a 3 hour exam duration, and notes the materials allowed. The document includes a reading passage and comprehension questions about changes in language used for technology over time. It also includes sections assessing grammatical knowledge, vocabulary, and ability to produce a written text on the given topic.
This document provides guidance on how to conduct high-quality research and write good papers. It discusses that research can involve solving existing problems using existing methods, improving existing solutions, or identifying new problems and generalizing solutions. The most innovative and impactful research involves identifying new problems. It emphasizes the importance of conducting new and useful research. It then provides tips for training innovation through extensive reading, writing, and rewriting to develop ideas. It discusses finding meaningful topics by starting from real problems and convincing others of the topic's importance. The document concludes by offering writing techniques such as overcoming language barriers, using an active voice, including visual elements, and being specific rather than vague.
This document summarizes a class on research question and design. It discusses:
1. Examining examples of quantitative rationales and research designs, including a case study on Sullivan.
2. An exercise where students rewrite and provide feedback on each other's research questions.
3. A discussion on generalizing qualitative research findings and the importance of context when formulating research questions.
The document provides an overview of the topics and activities covered in the class to help students refine their research questions and think about research design.
[D2 COMMUNITY] Spark User Group - 머신러닝 인공지능 기법NAVER D2
1) The document discusses various approaches and techniques in artificial intelligence including symbolic logic, planning, expert systems, fuzzy logic, genetic algorithms, Bayesian networks, and more.
2) It provides examples of each technique including using logic to represent arguments, planning routes for a traveling salesman, building financial expert systems, applying fuzzy logic to tipping recommendations, and using Bayesian networks for medical diagnosis.
3) The key challenges of AI discussed are computational complexity, problems with first-order logic like undecidability and uncertainty, and the difficulty of non-symbolic approaches like uncertainty in real-world problems.
review tips for Environmental Planning ExamCindyOmapas1
The document provides tips for preparing for and taking board exams. It discusses the importance of logical reasoning to deduce answers to unfamiliar questions. It advises carefully reading questions, looking out for words like "not" and "except" that can change the meaning. It also recommends practicing elimination of incorrect answer choices to improve odds of getting questions right. The document stresses making good use of time by answering easier questions first and not rushing. It emphasizes the importance of physical and mental preparation for the long exam.
- High-level overview
- Challenges in natural language processing
- What is intelligence?
- Sequence prediction
- A very short history of Solomonoff induction
- Meaning acquisition
- Logistic loss
- Gradient descent
- Applications
This document summarizes Greg Wilson's presentation titled "Two Solitudes". The presentation discusses the divide between academic computer science research and practical software development work. Academics do not respect practitioners' timelines and priorities, and their work is often inaccessible to practitioners. Practitioners do not understand that research is not focused on building software products. The presentation explores how other fields like medicine have addressed similar divides between theory and practice over long periods of time.
The document discusses knowledge representation and reasoning in artificial intelligence. It provides examples of how humans acquire and combine knowledge with reasoning to make inferences. Logical agents represent complex knowledge about the world and use inference to derive new information. Key issues in knowledge-based agents include representing knowledge in a knowledge base and performing reasoning and inference. The document discusses using a formal knowledge representation language to represent knowledge with clear syntax and semantics. It provides the example of the Wumpus World, where an agent explores a world using perception and reasoning about the rules of the world.
This document provides an overview and requirements for an Algebra 2 course. The course builds upon skills learned in Algebra 1 and covers additional topics like exponential, logarithmic, and trigonometric functions. Students must have earned a C or better in Algebra 1 and are expected to attend class daily, complete homework, study materials, and show determination. The course uses a basic algebra text along with tools like calculators and makes use of technologies like email, wikis, and presentation software. Grading is based on homework, projects, quizzes, exams, and participation.
1. The document discusses communicating science effectively to different audiences.
2. It emphasizes the importance of understanding the audience and bridging the gap between the content and how it is presented.
3. Examples are provided of generating awareness of scientific concepts through mechanisms, predictions, and experiments, such as explaining how Saturn's rings were discovered.
The document discusses basic science process skills like observing, inferring, measuring, classifying, predicting and communicating. It provides examples of activities to identify observations versus inferences and how to measure and classify objects. The document also covers the basics of static electricity including charging objects by friction, attractions and repulsions of charged materials, and practical applications like photocopiers.
This presentation contains my one day lectures which introduces fuzzy set theory, operations on fuzzy sets, some engineering control applications using Mamdamn model.
This document outlines a presentation about helping students write arguments using claims, evidence, and reasoning. The presentation introduces the claims-evidence-reasoning framework, provides examples of how it applies to different science disciplines, and offers strategies for implementing it in the classroom. These include engaging students in generating claims and evidence before writing, using transition words to connect ideas, and providing rubrics or peer review to give feedback on student work. The goal is to teach students to structure arguments like scientists by making claims and supporting them with logical reasoning and evidence.
01 Course Intro, Administrative, Etc After ClassSteve Koch
This document provides an introduction and overview for a Physics 102 course. It outlines the instructor's background, contact information, course goals and topics. Key aspects include:
- The course aims to teach physics concepts with minimal math for non-science majors.
- Students will use iClickers for in-class participation and four exams will determine 90% of the final grade.
- The first homework assignment is to read the syllabus on the course website by the next class.
- Technical support is available through the listed teaching assistant.
What knowledge bases know (and what they don't)srazniewski
This document discusses knowledge bases and their completeness and recall. It begins by introducing knowledge bases and some examples of factual knowledge bases that have been created. It then discusses how knowledge bases are useful for question answering and language generation. However, it notes that knowledge bases know only a small portion of what is actually true. It discusses several approaches that have been used to assess knowledge base completeness, including rule mining to predict completeness based on patterns in the data, information extraction to add new facts, and analyzing data presence to estimate completeness of single-value properties. The document outlines challenges with each of these approaches and aims to better understand what knowledge bases are approximating in order to improve assessments of their recall.
This document provides an overview of the CS101 Introduction to Computing course. It discusses the course contents and structure, which will cover fundamental computing concepts, web page development, and productivity software over 15 weeks. Students will complete assignments, a midterm exam, and a final exam. The first assignment requires students to email the instructor about their future plans and post a message on the course message board about customizing the class material. Upcoming lectures will discuss the history of computing from Babbage's Analytical Engine to modern computers.
This document outlines the structure and content of a university module on research questions and design. It discusses administrative details like communication methods and expectations. It describes the format of weekly classes, assignments, and required readings. Common dissertation failures like inadequate research questions or methods are also addressed. Students complete short writing exercises to demonstrate understanding of key concepts like qualitative vs. quantitative research. The importance of well-designed research and answerable questions is emphasized.
This document contains instructions and content for an English language exam consisting of multiple choice questions, word and phrase completion tasks, and an essay prompt. It provides guidelines on how to format responses, specifies a 3 hour exam duration, and notes the materials allowed. The document includes a reading passage and comprehension questions about changes in language used for technology over time. It also includes sections assessing grammatical knowledge, vocabulary, and ability to produce a written text on the given topic.
This document provides guidance on how to conduct high-quality research and write good papers. It discusses that research can involve solving existing problems using existing methods, improving existing solutions, or identifying new problems and generalizing solutions. The most innovative and impactful research involves identifying new problems. It emphasizes the importance of conducting new and useful research. It then provides tips for training innovation through extensive reading, writing, and rewriting to develop ideas. It discusses finding meaningful topics by starting from real problems and convincing others of the topic's importance. The document concludes by offering writing techniques such as overcoming language barriers, using an active voice, including visual elements, and being specific rather than vague.
This document summarizes a class on research question and design. It discusses:
1. Examining examples of quantitative rationales and research designs, including a case study on Sullivan.
2. An exercise where students rewrite and provide feedback on each other's research questions.
3. A discussion on generalizing qualitative research findings and the importance of context when formulating research questions.
The document provides an overview of the topics and activities covered in the class to help students refine their research questions and think about research design.
[D2 COMMUNITY] Spark User Group - 머신러닝 인공지능 기법NAVER D2
1) The document discusses various approaches and techniques in artificial intelligence including symbolic logic, planning, expert systems, fuzzy logic, genetic algorithms, Bayesian networks, and more.
2) It provides examples of each technique including using logic to represent arguments, planning routes for a traveling salesman, building financial expert systems, applying fuzzy logic to tipping recommendations, and using Bayesian networks for medical diagnosis.
3) The key challenges of AI discussed are computational complexity, problems with first-order logic like undecidability and uncertainty, and the difficulty of non-symbolic approaches like uncertainty in real-world problems.
review tips for Environmental Planning ExamCindyOmapas1
The document provides tips for preparing for and taking board exams. It discusses the importance of logical reasoning to deduce answers to unfamiliar questions. It advises carefully reading questions, looking out for words like "not" and "except" that can change the meaning. It also recommends practicing elimination of incorrect answer choices to improve odds of getting questions right. The document stresses making good use of time by answering easier questions first and not rushing. It emphasizes the importance of physical and mental preparation for the long exam.
- High-level overview
- Challenges in natural language processing
- What is intelligence?
- Sequence prediction
- A very short history of Solomonoff induction
- Meaning acquisition
- Logistic loss
- Gradient descent
- Applications
This document summarizes Greg Wilson's presentation titled "Two Solitudes". The presentation discusses the divide between academic computer science research and practical software development work. Academics do not respect practitioners' timelines and priorities, and their work is often inaccessible to practitioners. Practitioners do not understand that research is not focused on building software products. The presentation explores how other fields like medicine have addressed similar divides between theory and practice over long periods of time.
The document discusses knowledge representation and reasoning in artificial intelligence. It provides examples of how humans acquire and combine knowledge with reasoning to make inferences. Logical agents represent complex knowledge about the world and use inference to derive new information. Key issues in knowledge-based agents include representing knowledge in a knowledge base and performing reasoning and inference. The document discusses using a formal knowledge representation language to represent knowledge with clear syntax and semantics. It provides the example of the Wumpus World, where an agent explores a world using perception and reasoning about the rules of the world.
This document provides an overview and requirements for an Algebra 2 course. The course builds upon skills learned in Algebra 1 and covers additional topics like exponential, logarithmic, and trigonometric functions. Students must have earned a C or better in Algebra 1 and are expected to attend class daily, complete homework, study materials, and show determination. The course uses a basic algebra text along with tools like calculators and makes use of technologies like email, wikis, and presentation software. Grading is based on homework, projects, quizzes, exams, and participation.
1. The document discusses communicating science effectively to different audiences.
2. It emphasizes the importance of understanding the audience and bridging the gap between the content and how it is presented.
3. Examples are provided of generating awareness of scientific concepts through mechanisms, predictions, and experiments, such as explaining how Saturn's rings were discovered.
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Chapter wise All Notes of First year Basic Civil Engineering.pptxDenish Jangid
Chapter wise All Notes of First year Basic Civil Engineering
Syllabus
Chapter-1
Introduction to objective, scope and outcome the subject
Chapter 2
Introduction: Scope and Specialization of Civil Engineering, Role of civil Engineer in Society, Impact of infrastructural development on economy of country.
Chapter 3
Surveying: Object Principles & Types of Surveying; Site Plans, Plans & Maps; Scales & Unit of different Measurements.
Linear Measurements: Instruments used. Linear Measurement by Tape, Ranging out Survey Lines and overcoming Obstructions; Measurements on sloping ground; Tape corrections, conventional symbols. Angular Measurements: Instruments used; Introduction to Compass Surveying, Bearings and Longitude & Latitude of a Line, Introduction to total station.
Levelling: Instrument used Object of levelling, Methods of levelling in brief, and Contour maps.
Chapter 4
Buildings: Selection of site for Buildings, Layout of Building Plan, Types of buildings, Plinth area, carpet area, floor space index, Introduction to building byelaws, concept of sun light & ventilation. Components of Buildings & their functions, Basic concept of R.C.C., Introduction to types of foundation
Chapter 5
Transportation: Introduction to Transportation Engineering; Traffic and Road Safety: Types and Characteristics of Various Modes of Transportation; Various Road Traffic Signs, Causes of Accidents and Road Safety Measures.
Chapter 6
Environmental Engineering: Environmental Pollution, Environmental Acts and Regulations, Functional Concepts of Ecology, Basics of Species, Biodiversity, Ecosystem, Hydrological Cycle; Chemical Cycles: Carbon, Nitrogen & Phosphorus; Energy Flow in Ecosystems.
Water Pollution: Water Quality standards, Introduction to Treatment & Disposal of Waste Water. Reuse and Saving of Water, Rain Water Harvesting. Solid Waste Management: Classification of Solid Waste, Collection, Transportation and Disposal of Solid. Recycling of Solid Waste: Energy Recovery, Sanitary Landfill, On-Site Sanitation. Air & Noise Pollution: Primary and Secondary air pollutants, Harmful effects of Air Pollution, Control of Air Pollution. . Noise Pollution Harmful Effects of noise pollution, control of noise pollution, Global warming & Climate Change, Ozone depletion, Greenhouse effect
Text Books:
1. Palancharmy, Basic Civil Engineering, McGraw Hill publishers.
2. Satheesh Gopi, Basic Civil Engineering, Pearson Publishers.
3. Ketki Rangwala Dalal, Essentials of Civil Engineering, Charotar Publishing House.
4. BCP, Surveying volume 1
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The recent surge in pro-Palestine student activism has prompted significant responses from universities, ranging from negotiations and divestment commitments to increased transparency about investments in companies supporting the war on Gaza. This activism has led to the cessation of student encampments but also highlighted the substantial sacrifices made by students, including academic disruptions and personal risks. The primary drivers of these protests are poor university administration, lack of transparency, and inadequate communication between officials and students. This study examines the profound emotional, psychological, and professional impacts on students engaged in pro-Palestine protests, focusing on Generation Z's (Gen-Z) activism dynamics. This paper explores the significant sacrifices made by these students and even the professors supporting the pro-Palestine movement, with a focus on recent global movements. Through an in-depth analysis of printed and electronic media, the study examines the impacts of these sacrifices on the academic and personal lives of those involved. The paper highlights examples from various universities, demonstrating student activism's long-term and short-term effects, including disciplinary actions, social backlash, and career implications. The researchers also explore the broader implications of student sacrifices. The findings reveal that these sacrifices are driven by a profound commitment to justice and human rights, and are influenced by the increasing availability of information, peer interactions, and personal convictions. The study also discusses the broader implications of this activism, comparing it to historical precedents and assessing its potential to influence policy and public opinion. The emotional and psychological toll on student activists is significant, but their sense of purpose and community support mitigates some of these challenges. However, the researchers call for acknowledging the broader Impact of these sacrifices on the future global movement of FreePalestine.
1. 1
CS150 Fall 2005: 1. Introduction
David Evans
http://www.cs.virginia.edu/evans
CS150 Spring 2007
University of Virginia
Computer Science
Class 1:
Introduction
3. 3
1. Introduction
Let AB and CD be the two given numbers
not relatively prime. It is required to find the
greatest common measure of AB and CD.
If now CD measures AB, since it also
measures itself, then CD is a common
measure of CD and AB. And it is manifest
that it is also the greatest, for no greater
number than CD measures CD.
Euclid’s Elements, Book VII, Proposition 2 (300BC)
4. 4
1. Introduction
The note on the inflected line is
only difficult to you, because it is so
easy. There is in fact nothing in it,
but you think there must be some
grand mystery hidden under that
word inflected!
Whenever from any point
without a given line, you draw a long
to any point in the given line, you
have inflected a line upon a given
line. Ada Byron (age 19), letter to Annabella
Acheson (explaining Euclid), 1834
5. 5
1. Introduction
By the word operation, we mean any process
which alters the mutual relation of two or more
things, be this relation of what kind it may.
This is the most general definition, and would
include all subjects in the universe...
Supposing, for instance, that the fundamental
relations of pitched sounds in the science of
harmony and of musical composition were
susceptible of such expression and
adaptations, the engine might compose
elaborate and scientific pieces of music of any
degree of complexity or extent.
Ada Byron, 1843
6. 6
1. Introduction
What is the
difference
between Euclid
and Ada?
“It depends on what your
definition of ‘is’ is.”
Bill Gates (at Microsoft’s
anti-trust trial)
7. 7
1. Introduction
Geometry vs. Computer Science
• Geometry (mathematics) is about
declarative knowledge: “what is”
If now CD measures AB, since it also measures itself,
then CD is a common measure of CD and AB
• Computer Science is about imperative
knowledge: “how to”
Computer Science has little to do with
beige (or translucent blue) boxes called
“computers” and is not a real science.
8. 8
1. Introduction
Computer Science
“How to” knowledge:
• Ways of describing information
processes (computations)
• Ways of predicting properties of
information processes
Language
Logic
What kinds of things do we want to predict?
10. 10
1. Introduction
Science?
• Understanding Nature through
Observation
– About real things like bowling balls, black
holes, antimatter, electrons, comets, etc.
• Math and Computer Science are about
fake things like numbers, graphs,
functions, lists, etc.
– Computer Science is a useful tool for doing
real science, but not a real science
11. 11
1. Introduction
Engineering?
“Engineering is design under
constraint… Engineering is synthetic
- it strives to create what can be, but
it is constrained by nature, by cost,
by concerns of safety, reliability,
environmental impact,
manufacturability, maintainability and
many other such 'ilities.' ...”
William Wulf
13. 13
1. Introduction
Measuring Computers
• 1 bit = smallest unit of information
– True or False
– 0 or 1
– If we start with 2 possible choices, and get 1
bit, we can eliminate one of the choices
14. 14
1. Introduction
How much power?
• Apollo Computer: 30720 bits of changeable memory
• Lab machines have 1 GB (RAM)
– 1 Gigabyte = 1024 Megabytes,
1 Megabyte = 1024 Kilobytes,
1 Kilobyte = 1024 Bytes,
1 Byte = 8 bits
> (* 1024 1024 1024 8)
8589934592 ~ 8.6 Billion bits
> (round (/ (* 1024 1024 1024 8) 30720))
279620
If Apollo Guidance Computer power is 1 inch, you have 4.4 miles!
You have 105 404 times more power than AGC
You will understand this
notation soon…but don’t worry
if you don’t now
16. 16
1. Introduction
Constraints Computer Scientists Face
• Not like those for engineers:
– Cost, weight, physics, etc.
– If ~20 Million times what people had in 1969
isn’t enough for you, wait until 2010 and you
will have 80 Million times…
• More like those for Musicians and Poets:
– Imagination and Creativity
– Complexity of what we can understand
17. 17
1. Introduction
So, what is computer science?
• Science
– No: its about fake things like numbers, not
about observing and understanding nature
• Engineering
– No: we don’t have to deal with engineering-
type constraints
• Liberal Art
18. 18
1. Introduction
Liberal Arts: ~1100
• Illiberal Arts
– arts for the non-free: pursued for economic
reasons
• Liberal Arts
– arts for the free: pursued for intrinsic reasons
19. 19
1. Introduction
The Liberal Arts
Trivium (3 roads) Quadrivium (4 roads)
Grammar
study of meaning in
written expression
Rhetoric
comprehension
of discourse
Logic
argument
for
discovering
truth
Arithmetic
Geometry
quantification
of space
Music
number
in time
Astronomy
We will see all of these in this class!
21. 21
1. Introduction
Course Roadmap
Computer Science
from Euclid and Ada
to
Quantum Computing
and
the World Wide Web
1st Class
PS 7-8
Lecture
PS 1-6
Liberal
Arts
(Intellectual)
Illiberal
Arts
($$$$)
22. 22
1. Introduction
Like Drinking from a Firehose
It may hurt a little bit, and a lot of water will
go by you, but you won’t go away thirsty!
Don’t be overwhelmed!
You will do fine.
23. 23
1. Introduction
Books
Computational Thinking
A Whirlwind Introduction
to the Third Millennial Liberal Art
from Ada and Euclid
to Quantum Computing
and the World Wide Web
“GEB”
New Book!: written for course
Chapters 2 and 3 out today
Bonuses for helping me improve it:
- Less pretentious title (?)
- More exciting cover
- Notice any mistakes
- Improve the writing or presentation
“Course Book”
24. 24
1. Introduction
Help Available
• Me: David Evans (Call me “Dave” or “Coach”)
– Office Hours will be posted (after your surveys)
– Always available by email, if I don’t reply in 24
hours, send again and complain
• Assistant Coaches: Richard Hsu and Kinga Dobolyi
– Staffed lab hours in Small Hall
– Upcoming lab hours: Thursday 6-9pm; Friday after class
• Web site: http://www.cs.virginia.edu/cs150
– Everything goes on the web, you should visit it often
• Your classmates (read the course pledge
carefully!)
25. 25
1. Introduction
What I Expect of You
1. Everything on the Course Pledge
– You should actually read it not just sign it
(you will lose points on PS1 if your
submission reveals that you didn’t read it!)
2. You are a “Jeffersonian Student”
1.Believe knowledge is powerful
2.Interested in lots of things, ahead of your time
3.Want to use what you learn to do good things
4.Care more about what you learn than grades
and degree requirements
26. 26
1. Introduction
Background Expected
• Language:
– Reasonable reading and writing in English
– Understanding of subject, verb and object
• Math:
– Numbers, add, subtract, multiply, divide
– Exponentiation, logarithms (we will review)
• Logic: and, or, not
• Computer Literacy: read email, browse web
If I ever appear to expect anything else, stop me!
27. 27
1. Introduction
A Course for Everyone!
• CLAS, SEAS, Commerce, Arch, etc.
• 1st, 2nd, 3rd, 4th, 5th Years, Community
Scholars, Faculty
• No background expected…but challenging
even for students with lots of previous CS
courses
• Computer Science (future-) majors…but
worthwhile even if you don’t take another
CS course
31. 31
1. Introduction
Making Longer Words
antifloccipoccinihilipilification
the act of rendering not useless
antiantifloccipoccinihilipilification
the act of rendering useless
32. 32
1. Introduction
Language is Recursive
No matter what word you think is the
longest word, I can always make up a
longer one!
word ::= anti-word
If you have a word, you can always make up
a new word by adding anti in front. Since
the result is a word, you can make a longer
new word by adding anti- in front again.
33. 33
1. Introduction
Recursive Definitions
• We can define things in terms of
themselves
• Recursive definitions are different from
circular definitions: they eventually end
with something real
word ::= anti-word
word ::= floccipoccinihilipilification
35. 35
1. Introduction
Charge
• Before 11:59pm Thursday:
– Registration survey (see course web site)
• Reading Before Friday:
– Read Course Book Chapters 2 and 3
– GEB p. 3-41
• Anyone who can produce “MU”, gets an
automatic A+ in the course
• Don’t floccipoccinihilipilificate
36. 36
1. Introduction
Thanks!
• 2004, 2005 CS150 students, 2003 CS 200 students, 2002 CS200 students, 2001
CS655 students
• 2002 Assistant Coaches: Jon Erdman, Dante Guanlao, Stephen Liang, Portman
Wills
• 2003 Assistant Coaches: Rachel Dada, Jacques Fournier, Spencer Stockdale,
Katie Winstanley
• 2004 Assistant Coaches: Sarah Bergkuist, Andrew Connors, Patrick Rooney,
Katie Winstanley
• 2005 Assistant Coaches: David Faulkner, Dan Upton
• Guest Speakers: Radhika Nagpal (2002), Tim Koogle (2003); Alan Kay (2005)
• Spring 2006: Greg Humphreys; Kristen Walcott, Gillian Smith
• Teaching Resource Center: Marva Barnett, Freda Fretwell
• 2001-2 UTF Fellows: Phoebe Crisman, John Lach, Debra Lyon, Emily Scida,
Brian Smith, David Waldner; UTF Mentor: Judith Shatin
• 6.001 teachers: Gerry Sussman, Bob Berwick
• CS Department: Jim Cohoon, Ginny Hilton, Tom Horton, Greg Humphreys, Anita
Jones, John Knight, Worthy Martin, Chris Milner, Brenda Perkins, Gabe Robins,
Mary Lou Soffa, Jack Stankovic
• Anna Chefter, Chris Frost, Thad Hughes, Jerry McGann, Shawn O’Hargan, Mike
Peck