SlideShare a Scribd company logo
1CS150 Fall 2005: 1. Introduction
David Evans
http://www.cs.virginia.edu/evans
CS150 Spring 2007
University of Virginia
Computer Science
Class 1:Class 1:
IntroductionIntroduction
21. Introduction
What is
Computer Science?
31. 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)
41. 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
51. 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
61. 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)
71. 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.
81. 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?
91. Introduction
Science, Engineering, Other?
101. 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
111. 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
121. Introduction
Apollo Guidance Computer, 1969
1 Cubic Foot
Why did they need to fit the
guidance computer in the
rocket?
131. 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
141. 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
15CS150 Fall 2005: 1. Introduction
0
10,000,000
20,000,000
30,000,000
40,000,000
50,000,000
60,000,000
70,000,000
80,000,000
1969
1972
1975
1978
1981
1984
1987
1990
1993
1996
1999
2002
2005
2008
Computing Power 1969-2008
(in Apollo Control Computer Units)
Moore’s “Law”: computing power
roughly doubles every 18 months!
161. 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
171. 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
181. 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
191. Introduction
The Liberal Arts
Trivium (3 roads)
language
Quadrivium (4 roads)
numbers
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!
201. Introduction
Course
Expectations
211. 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
LiberalArts
(Intellectual)
IlliberalArts
($$$$)
221. 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.
231. 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”
241. 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!)
251. 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
261. 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!
271. 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
281. Introduction
First Main Theme:
Recursive Definitions
291. Introduction
What is the longest word
in the English language?
301. Introduction
According to Guinness
floccipoccinihilipilification
the act of rendering useless
311. Introduction
Making Longer Words
antifloccipoccinihilipilification
the act of rendering not useless
antiantifloccipoccinihilipilification
the act of rendering useless
321. 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.
331. 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
341. Introduction
Recursive Definitions
Allow us to express infinitely
many things starting with a
few.
This is powerful!
We will see lots of examples
in this course.
351. 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
361. 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

More Related Content

Similar to Computer science

lecture1.ppt
lecture1.pptlecture1.ppt
lecture1.ppt
lilywatermen
 
Introduction to Computer Science Lecture
Introduction to Computer Science LectureIntroduction to Computer Science Lecture
Introduction to Computer Science Lecture
rpython2030
 
introduction to computer science.ppt
introduction to computer science.pptintroduction to computer science.ppt
introduction to computer science.ppt
LearnEnglishEnglishC
 
AI Guide for Schools and Colleges in 2023
AI Guide for Schools and Colleges in 2023AI Guide for Schools and Colleges in 2023
AI Guide for Schools and Colleges in 2023
VashirAhmad
 
lecture1.ppt
lecture1.pptlecture1.ppt
lecture1.ppt
DanielePremarini
 
Lecture 1: Introduction
Lecture 1: IntroductionLecture 1: Introduction
Lecture 1: Introduction
David Evans
 
Logic and mathematics history and overview for students
Logic and mathematics history and overview for studentsLogic and mathematics history and overview for students
Logic and mathematics history and overview for students
Bob Marcus
 
What is computer science
What is computer scienceWhat is computer science
What is computer science
Ronald Fuller
 
Deep Learning with Python (PyData Seattle 2015)
Deep Learning with Python (PyData Seattle 2015)Deep Learning with Python (PyData Seattle 2015)
Deep Learning with Python (PyData Seattle 2015)
Alexander Korbonits
 
SY 7034 Week1
SY 7034 Week1SY 7034 Week1
SY 7034 Week1
Edmund Chattoe-Brown
 
Cs101lec01 100130102405-phpapp02
Cs101lec01 100130102405-phpapp02Cs101lec01 100130102405-phpapp02
Cs101lec01 100130102405-phpapp02
shobejee
 
ABOUT ELPT AND SUBJECTABOUT ELPT AND elp
ABOUT ELPT AND SUBJECTABOUT ELPT AND elpABOUT ELPT AND SUBJECTABOUT ELPT AND elp
ABOUT ELPT AND SUBJECTABOUT ELPT AND elp
IlukZhrtlu1
 
lecture_1.pptx
lecture_1.pptxlecture_1.pptx
lecture_1.pptx
GargTutorials
 
Introduction To Computer Science (getting started)
Introduction To Computer Science (getting started)Introduction To Computer Science (getting started)
Introduction To Computer Science (getting started)
Lawrence Wachs
 
Electronic Productions - Year 10 - Lesson 3 - S.I Units And Ohms Law
Electronic Productions - Year 10 - Lesson 3 - S.I Units And Ohms LawElectronic Productions - Year 10 - Lesson 3 - S.I Units And Ohms Law
Electronic Productions - Year 10 - Lesson 3 - S.I Units And Ohms Law
Rob Winter
 
Claim, Evidence, and Reasoning
Claim, Evidence, and ReasoningClaim, Evidence, and Reasoning
Claim, Evidence, and Reasoning
Devron Miller
 
Basic Science Process Skills.pptx
Basic Science Process Skills.pptxBasic Science Process Skills.pptx
Basic Science Process Skills.pptx
DahliaSuello2
 
Lecture 2: Language
Lecture 2: LanguageLecture 2: Language
Lecture 2: Language
David Evans
 
Intro to missing_basics_goldberg
Intro to missing_basics_goldbergIntro to missing_basics_goldberg
Intro to missing_basics_goldberg
Missing Basics
 
review tips for Environmental Planning Exam
review tips for Environmental Planning Examreview tips for Environmental Planning Exam
review tips for Environmental Planning Exam
CindyOmapas1
 

Similar to Computer science (20)

lecture1.ppt
lecture1.pptlecture1.ppt
lecture1.ppt
 
Introduction to Computer Science Lecture
Introduction to Computer Science LectureIntroduction to Computer Science Lecture
Introduction to Computer Science Lecture
 
introduction to computer science.ppt
introduction to computer science.pptintroduction to computer science.ppt
introduction to computer science.ppt
 
AI Guide for Schools and Colleges in 2023
AI Guide for Schools and Colleges in 2023AI Guide for Schools and Colleges in 2023
AI Guide for Schools and Colleges in 2023
 
lecture1.ppt
lecture1.pptlecture1.ppt
lecture1.ppt
 
Lecture 1: Introduction
Lecture 1: IntroductionLecture 1: Introduction
Lecture 1: Introduction
 
Logic and mathematics history and overview for students
Logic and mathematics history and overview for studentsLogic and mathematics history and overview for students
Logic and mathematics history and overview for students
 
What is computer science
What is computer scienceWhat is computer science
What is computer science
 
Deep Learning with Python (PyData Seattle 2015)
Deep Learning with Python (PyData Seattle 2015)Deep Learning with Python (PyData Seattle 2015)
Deep Learning with Python (PyData Seattle 2015)
 
SY 7034 Week1
SY 7034 Week1SY 7034 Week1
SY 7034 Week1
 
Cs101lec01 100130102405-phpapp02
Cs101lec01 100130102405-phpapp02Cs101lec01 100130102405-phpapp02
Cs101lec01 100130102405-phpapp02
 
ABOUT ELPT AND SUBJECTABOUT ELPT AND elp
ABOUT ELPT AND SUBJECTABOUT ELPT AND elpABOUT ELPT AND SUBJECTABOUT ELPT AND elp
ABOUT ELPT AND SUBJECTABOUT ELPT AND elp
 
lecture_1.pptx
lecture_1.pptxlecture_1.pptx
lecture_1.pptx
 
Introduction To Computer Science (getting started)
Introduction To Computer Science (getting started)Introduction To Computer Science (getting started)
Introduction To Computer Science (getting started)
 
Electronic Productions - Year 10 - Lesson 3 - S.I Units And Ohms Law
Electronic Productions - Year 10 - Lesson 3 - S.I Units And Ohms LawElectronic Productions - Year 10 - Lesson 3 - S.I Units And Ohms Law
Electronic Productions - Year 10 - Lesson 3 - S.I Units And Ohms Law
 
Claim, Evidence, and Reasoning
Claim, Evidence, and ReasoningClaim, Evidence, and Reasoning
Claim, Evidence, and Reasoning
 
Basic Science Process Skills.pptx
Basic Science Process Skills.pptxBasic Science Process Skills.pptx
Basic Science Process Skills.pptx
 
Lecture 2: Language
Lecture 2: LanguageLecture 2: Language
Lecture 2: Language
 
Intro to missing_basics_goldberg
Intro to missing_basics_goldbergIntro to missing_basics_goldberg
Intro to missing_basics_goldberg
 
review tips for Environmental Planning Exam
review tips for Environmental Planning Examreview tips for Environmental Planning Exam
review tips for Environmental Planning Exam
 

Recently uploaded

Skybuffer SAM4U tool for SAP license adoption
Skybuffer SAM4U tool for SAP license adoptionSkybuffer SAM4U tool for SAP license adoption
Skybuffer SAM4U tool for SAP license adoption
Tatiana Kojar
 
AWS Cloud Cost Optimization Presentation.pptx
AWS Cloud Cost Optimization Presentation.pptxAWS Cloud Cost Optimization Presentation.pptx
AWS Cloud Cost Optimization Presentation.pptx
HarisZaheer8
 
Building Production Ready Search Pipelines with Spark and Milvus
Building Production Ready Search Pipelines with Spark and MilvusBuilding Production Ready Search Pipelines with Spark and Milvus
Building Production Ready Search Pipelines with Spark and Milvus
Zilliz
 
Programming Foundation Models with DSPy - Meetup Slides
Programming Foundation Models with DSPy - Meetup SlidesProgramming Foundation Models with DSPy - Meetup Slides
Programming Foundation Models with DSPy - Meetup Slides
Zilliz
 
Overcoming the PLG Trap: Lessons from Canva's Head of Sales & Head of EMEA Da...
Overcoming the PLG Trap: Lessons from Canva's Head of Sales & Head of EMEA Da...Overcoming the PLG Trap: Lessons from Canva's Head of Sales & Head of EMEA Da...
Overcoming the PLG Trap: Lessons from Canva's Head of Sales & Head of EMEA Da...
saastr
 
A Comprehensive Guide to DeFi Development Services in 2024
A Comprehensive Guide to DeFi Development Services in 2024A Comprehensive Guide to DeFi Development Services in 2024
A Comprehensive Guide to DeFi Development Services in 2024
Intelisync
 
UI5 Controls simplified - UI5con2024 presentation
UI5 Controls simplified - UI5con2024 presentationUI5 Controls simplified - UI5con2024 presentation
UI5 Controls simplified - UI5con2024 presentation
Wouter Lemaire
 
Main news related to the CCS TSI 2023 (2023/1695)
Main news related to the CCS TSI 2023 (2023/1695)Main news related to the CCS TSI 2023 (2023/1695)
Main news related to the CCS TSI 2023 (2023/1695)
Jakub Marek
 
Best 20 SEO Techniques To Improve Website Visibility In SERP
Best 20 SEO Techniques To Improve Website Visibility In SERPBest 20 SEO Techniques To Improve Website Visibility In SERP
Best 20 SEO Techniques To Improve Website Visibility In SERP
Pixlogix Infotech
 
Columbus Data & Analytics Wednesdays - June 2024
Columbus Data & Analytics Wednesdays - June 2024Columbus Data & Analytics Wednesdays - June 2024
Columbus Data & Analytics Wednesdays - June 2024
Jason Packer
 
Monitoring and Managing Anomaly Detection on OpenShift.pdf
Monitoring and Managing Anomaly Detection on OpenShift.pdfMonitoring and Managing Anomaly Detection on OpenShift.pdf
Monitoring and Managing Anomaly Detection on OpenShift.pdf
Tosin Akinosho
 
Introduction of Cybersecurity with OSS at Code Europe 2024
Introduction of Cybersecurity with OSS  at Code Europe 2024Introduction of Cybersecurity with OSS  at Code Europe 2024
Introduction of Cybersecurity with OSS at Code Europe 2024
Hiroshi SHIBATA
 
Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...
Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...
Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...
saastr
 
Letter and Document Automation for Bonterra Impact Management (fka Social Sol...
Letter and Document Automation for Bonterra Impact Management (fka Social Sol...Letter and Document Automation for Bonterra Impact Management (fka Social Sol...
Letter and Document Automation for Bonterra Impact Management (fka Social Sol...
Jeffrey Haguewood
 
Deep Dive: Getting Funded with Jason Jason Lemkin Founder & CEO @ SaaStr
Deep Dive: Getting Funded with Jason Jason Lemkin Founder & CEO @ SaaStrDeep Dive: Getting Funded with Jason Jason Lemkin Founder & CEO @ SaaStr
Deep Dive: Getting Funded with Jason Jason Lemkin Founder & CEO @ SaaStr
saastr
 
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing InstancesEnergy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Alpen-Adria-Universität
 
Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...
Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...
Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...
Jeffrey Haguewood
 
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUHCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
panagenda
 
GraphRAG for Life Science to increase LLM accuracy
GraphRAG for Life Science to increase LLM accuracyGraphRAG for Life Science to increase LLM accuracy
GraphRAG for Life Science to increase LLM accuracy
Tomaz Bratanic
 
leewayhertz.com-AI in predictive maintenance Use cases technologies benefits ...
leewayhertz.com-AI in predictive maintenance Use cases technologies benefits ...leewayhertz.com-AI in predictive maintenance Use cases technologies benefits ...
leewayhertz.com-AI in predictive maintenance Use cases technologies benefits ...
alexjohnson7307
 

Recently uploaded (20)

Skybuffer SAM4U tool for SAP license adoption
Skybuffer SAM4U tool for SAP license adoptionSkybuffer SAM4U tool for SAP license adoption
Skybuffer SAM4U tool for SAP license adoption
 
AWS Cloud Cost Optimization Presentation.pptx
AWS Cloud Cost Optimization Presentation.pptxAWS Cloud Cost Optimization Presentation.pptx
AWS Cloud Cost Optimization Presentation.pptx
 
Building Production Ready Search Pipelines with Spark and Milvus
Building Production Ready Search Pipelines with Spark and MilvusBuilding Production Ready Search Pipelines with Spark and Milvus
Building Production Ready Search Pipelines with Spark and Milvus
 
Programming Foundation Models with DSPy - Meetup Slides
Programming Foundation Models with DSPy - Meetup SlidesProgramming Foundation Models with DSPy - Meetup Slides
Programming Foundation Models with DSPy - Meetup Slides
 
Overcoming the PLG Trap: Lessons from Canva's Head of Sales & Head of EMEA Da...
Overcoming the PLG Trap: Lessons from Canva's Head of Sales & Head of EMEA Da...Overcoming the PLG Trap: Lessons from Canva's Head of Sales & Head of EMEA Da...
Overcoming the PLG Trap: Lessons from Canva's Head of Sales & Head of EMEA Da...
 
A Comprehensive Guide to DeFi Development Services in 2024
A Comprehensive Guide to DeFi Development Services in 2024A Comprehensive Guide to DeFi Development Services in 2024
A Comprehensive Guide to DeFi Development Services in 2024
 
UI5 Controls simplified - UI5con2024 presentation
UI5 Controls simplified - UI5con2024 presentationUI5 Controls simplified - UI5con2024 presentation
UI5 Controls simplified - UI5con2024 presentation
 
Main news related to the CCS TSI 2023 (2023/1695)
Main news related to the CCS TSI 2023 (2023/1695)Main news related to the CCS TSI 2023 (2023/1695)
Main news related to the CCS TSI 2023 (2023/1695)
 
Best 20 SEO Techniques To Improve Website Visibility In SERP
Best 20 SEO Techniques To Improve Website Visibility In SERPBest 20 SEO Techniques To Improve Website Visibility In SERP
Best 20 SEO Techniques To Improve Website Visibility In SERP
 
Columbus Data & Analytics Wednesdays - June 2024
Columbus Data & Analytics Wednesdays - June 2024Columbus Data & Analytics Wednesdays - June 2024
Columbus Data & Analytics Wednesdays - June 2024
 
Monitoring and Managing Anomaly Detection on OpenShift.pdf
Monitoring and Managing Anomaly Detection on OpenShift.pdfMonitoring and Managing Anomaly Detection on OpenShift.pdf
Monitoring and Managing Anomaly Detection on OpenShift.pdf
 
Introduction of Cybersecurity with OSS at Code Europe 2024
Introduction of Cybersecurity with OSS  at Code Europe 2024Introduction of Cybersecurity with OSS  at Code Europe 2024
Introduction of Cybersecurity with OSS at Code Europe 2024
 
Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...
Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...
Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...
 
Letter and Document Automation for Bonterra Impact Management (fka Social Sol...
Letter and Document Automation for Bonterra Impact Management (fka Social Sol...Letter and Document Automation for Bonterra Impact Management (fka Social Sol...
Letter and Document Automation for Bonterra Impact Management (fka Social Sol...
 
Deep Dive: Getting Funded with Jason Jason Lemkin Founder & CEO @ SaaStr
Deep Dive: Getting Funded with Jason Jason Lemkin Founder & CEO @ SaaStrDeep Dive: Getting Funded with Jason Jason Lemkin Founder & CEO @ SaaStr
Deep Dive: Getting Funded with Jason Jason Lemkin Founder & CEO @ SaaStr
 
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing InstancesEnergy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
 
Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...
Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...
Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...
 
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUHCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
 
GraphRAG for Life Science to increase LLM accuracy
GraphRAG for Life Science to increase LLM accuracyGraphRAG for Life Science to increase LLM accuracy
GraphRAG for Life Science to increase LLM accuracy
 
leewayhertz.com-AI in predictive maintenance Use cases technologies benefits ...
leewayhertz.com-AI in predictive maintenance Use cases technologies benefits ...leewayhertz.com-AI in predictive maintenance Use cases technologies benefits ...
leewayhertz.com-AI in predictive maintenance Use cases technologies benefits ...
 

Computer science

  • 1. 1CS150 Fall 2005: 1. Introduction David Evans http://www.cs.virginia.edu/evans CS150 Spring 2007 University of Virginia Computer Science Class 1:Class 1: IntroductionIntroduction
  • 3. 31. 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. 41. 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. 51. 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. 61. 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. 71. 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. 81. 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. 101. 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. 111. 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
  • 12. 121. Introduction Apollo Guidance Computer, 1969 1 Cubic Foot Why did they need to fit the guidance computer in the rocket?
  • 13. 131. 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. 141. 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
  • 15. 15CS150 Fall 2005: 1. Introduction 0 10,000,000 20,000,000 30,000,000 40,000,000 50,000,000 60,000,000 70,000,000 80,000,000 1969 1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005 2008 Computing Power 1969-2008 (in Apollo Control Computer Units) Moore’s “Law”: computing power roughly doubles every 18 months!
  • 16. 161. 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. 171. 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. 181. 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. 191. Introduction The Liberal Arts Trivium (3 roads) language Quadrivium (4 roads) numbers 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. 211. 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 LiberalArts (Intellectual) IlliberalArts ($$$$)
  • 22. 221. 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. 231. 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. 241. 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. 251. 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. 261. 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. 271. 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
  • 28. 281. Introduction First Main Theme: Recursive Definitions
  • 29. 291. Introduction What is the longest word in the English language?
  • 30. 301. Introduction According to Guinness floccipoccinihilipilification the act of rendering useless
  • 31. 311. Introduction Making Longer Words antifloccipoccinihilipilification the act of rendering not useless antiantifloccipoccinihilipilification the act of rendering useless
  • 32. 321. 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. 331. 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
  • 34. 341. Introduction Recursive Definitions Allow us to express infinitely many things starting with a few. This is powerful! We will see lots of examples in this course.
  • 35. 351. 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. 361. 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