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61A Lecture 1
Wednesday, August 24, 2016
Welcome to CS 61A!
2
I'm John DeNero
Welcome to CS 61A!
2
I'm John DeNero
Welcome to CS 61A!
2
I'm John DeNero
Welcome to CS 61A!
2
I'm John DeNero
Welcome to CS 61A!
2
How to contact John:[email protected]
piazza.com/berkeley/fall2016/cs61a
I'm John DeNero
Welcome to CS 61A!
2
How to contact John:[email protected]
piazza.com/berkeley/fall2016/cs61a
John's office hours:
781 Soda
Monday & Wednesday 11am - 12pm
By appointment: denero.org/meet
I'm John DeNero
The 61A Community
3
The 61A Community
3
45 undergraduate student instructors / teaching assistants (TAs):
The 61A Community
3
45 undergraduate student instructors / teaching assistants (TAs):
• Teach lab & discussion sections
The 61A Community
3
45 undergraduate student instructors / teaching assistants (TAs):
• Teach lab & discussion sections
• Hold office hours
The 61A Community
3
45 undergraduate student instructors / teaching assistants (TAs):
• Teach lab & discussion sections
• Hold office hours
• Lots of other stuff: develop assignments, grade exams, etc.
The 61A Community
3
45 undergraduate student instructors / teaching assistants (TAs):
• Teach lab & discussion sections
• Hold office hours
• Lots of other stuff: develop assignments, grade exams, etc.
45+ tutors & mentors:
The 61A Community
3
45 undergraduate student instructors / teaching assistants (TAs):
• Teach lab & discussion sections
• Hold office hours
• Lots of other stuff: develop assignments, grade exams, etc.
45+ tutors & mentors:
• Teach mentoring sections
The 61A Community
3
45 undergraduate student instructors / teaching assistants (TAs):
• Teach lab & discussion sections
• Hold office hours
• Lots of other stuff: develop assignments, grade exams, etc.
45+ tutors & mentors:
• Teach mentoring sections
• Hold office hours
The 61A Community
3
45 undergraduate student instructors / teaching assistants (TAs):
• Teach lab & discussion sections
• Hold office hours
• Lots of other stuff: develop assignments, grade exams, etc.
45+ tutors & mentors:
• Teach mentoring sections
• Hold office hours
• Lots of other stuff: homework parties, mastery sections, etc.
The 61A Community
3
45 undergraduate student instructors / teaching assistants (TAs):
• Teach lab & discussion sections
• Hold office hours
• Lots of other stuff: develop assignments, grade exams, etc.
45+ tutors & mentors:
• Teach mentoring sections
• Hold office hours
• Lots of other stuff: homework parties, mastery sections, etc.
200+ lab assistants help answer your individual questions
The 61A Community
3
45 undergraduate student instructors / teaching assistants (TAs):
• Teach lab & discussion sections
• Hold office hours
• Lots of other stuff: develop assignments, grade exams, etc.
45+ tutors & mentors:
• Teach mentoring sections
• Hold office hours
• Lots of other stuff: homework parties, mastery sections, etc.
200+ lab assistants help answer your individual questions
1,500+ fellow students make CS 61A unique
Parts of the Course
4
Parts of the Course
Lecture: Videos posted to cs61a.org before each live lecture
4
Parts of the Course
Lecture: Videos posted to cs61a.org before each live lecture
Lab section: The most important part of this course (next week)
4
Parts of the Course
Lecture: Videos posted to cs61a.org before each live lecture
Lab section: The most important part of this course (next week)
Discussion section: The most important part of this course (this week)
4
Parts of the Course
Lecture: Videos posted to cs61a.org before each live lecture
Lab section: The most important part of this course (next week)
Discussion section: The most important part of this course (this week)
Staff office hours: The most important part of this course (next week)
4
Parts of the Course
Lecture: Videos posted to cs61a.org before each live lecture
Lab section: The most important part of this course (next week)
Discussion section: The most important part of this course (this week)
Staff office hours: The most important part of this course (next week)
Online textbook: http://composingprograms.com
4
Parts of the Course
Lecture: Videos posted to cs61a.org before each live lecture
Lab section: The most important part of this course (next week)
Discussion section: The most important part of this course (this week)
Staff office hours: The most important part of this course (next week)
Online textbook: http://composingprograms.com
Weekly homework assignments, three exams, & four programming projects
4
Parts of the Course
Lecture: Videos posted to cs61a.org before each live lecture
Lab section: The most important part of this course (next week)
Discussion section: The most important part of this course (this week)
Staff office hours: The most important part of this course (next week)
Online textbook: http://composingprograms.com
Weekly homework assignments, three exams, & four programming projects
Lots of optional special events to help you complete all this work
4
An Introduction to Computer Science
What is Computer Science?
6
What is Computer Science?
6
The study of
What is Computer Science?
6
What problems can be solved using computation,The study of
What is Computer Science?
6
What problems can be solved using computation,How to solve those problems, andThe study of
What is Computer Science?
6
What problems can be solved using computation,How to solve those problems, andWhat techniques lead to effective solutions
The study of
What is Computer Science?
Systems
6
What problems can be solved using computation,How to solve those problems, andWhat techniques lead to effective solutions
The study of
What is Computer Science?
Systems
Artificial Intelligence
6
What problems can be solved using computation,How to solve those problems, andWhat techniques lead to effective solutions
The study of
What is Computer Science?
Systems
Artificial Intelligence
Graphics
6
What problems can be solved using computation,How to solve those problems, andWhat techniques lead to effective solutions
The study of
What is Computer Science?
Systems
Artificial Intelligence
Graphics
Security
6
What problems can be solved using computation,How to solve those problems, andWhat techniques lead to effective solutions
The study of
What is Computer Science?
Systems
Artificial Intelligence
Graphics
Security
Networking
Programming Languages
Theory
Scientific Computing
...
6
What problems can be solved using computation,How to solve those problems, andWhat techniques lead to effective solutions
The study of
What is Computer Science?
Systems
Artificial Intelligence
Graphics
Security
Networking
Programming Languages
Theory
Scientific Computing
...
6
What problems can be solved using computation,How to solve those problems, andWhat techniques lead to effective solutions
The study of
What is Computer Science?
Systems
Artificial Intelligence
Graphics
Security
Networking
Programming Languages
Theory
Scientific Computing
...
6
Decision Making
What problems can be solved using computation,How to solve those problems, andWhat techniques lead to effective solutions
The study of
What is Computer Science?
Systems
Artificial Intelligence
Graphics
Security
Networking
Programming Languages
Theory
Scientific Computing
...
6
Decision Making
Robotics
What problems can be solved using computation,How to solve those problems, andWhat techniques lead to effective solutions
The study of
What is Computer Science?
Systems
Artificial Intelligence
Graphics
Security
Networking
Programming Languages
Theory
Scientific Computing
...
6
Decision Making
Robotics
Natural Language Processing
What problems can be solved using computation,How to solve those problems, andWhat techniques lead to effective solutions
The study of
What is Computer Science?
Systems
Artificial Intelligence
Graphics
Security
Networking
Programming Languages
Theory
Scientific Computing
...
6
Decision Making
Robotics
Natural Language Processing
...
What problems can be solved using computation,How to solve those problems, andWhat techniques lead to effective solutions
The study of
What is Computer Science?
Systems
Artificial Intelligence
Graphics
Security
Networking
Programming Languages
Theory
Scientific Computing
...
6
Decision Making
Robotics
Natural Language Processing
...
What problems can be solved using computation,How to solve those problems, andWhat techniques lead to effective solutions
The study of
What is Computer Science?
Systems
Artificial Intelligence
Graphics
Security
Networking
Programming Languages
Theory
Scientific Computing
...
6
Decision Making
Robotics
Natural Language Processing
...
What problems can be solved using computation,How to solve those problems, andWhat techniques lead to effective solutions
The study of
Answering Questions
What is Computer Science?
Systems
Artificial Intelligence
Graphics
Security
Networking
Programming Languages
Theory
Scientific Computing
...
6
Decision Making
Robotics
Natural Language Processing
...
What problems can be solved using computation,How to solve those problems, andWhat techniques lead to effective solutions
The study of
Answering Questions
Translation
What is Computer Science?
Systems
Artificial Intelligence
Graphics
Security
Networking
Programming Languages
Theory
Scientific Computing
...
6
Decision Making
Robotics
Natural Language Processing
...
What problems can be solved using computation,How to solve those problems, andWhat techniques lead to effective solutions
The study of
Answering Questions
Translation
...
What is This Course About?
7
What is This Course About?
A course about managing complexity
7
What is This Course About?
A course about managing complexity
Mastering abstraction
7
What is This Course About?
A course about managing complexity
Mastering abstraction
Programming paradigms
7
What is This Course About?
A course about managing complexity
Mastering abstraction
Programming paradigms
An introduction to programming
7
What is This Course About?
A course about managing complexity
Mastering abstraction
Programming paradigms
An introduction to programming
Full understanding of Python fundamentals
7
What is This Course About?
A course about managing complexity
Mastering abstraction
Programming paradigms
An introduction to programming
Full understanding of Python fundamentals
Combining multiple ideas in large projects
7
What is This Course About?
A course about managing complexity
Mastering abstraction
Programming paradigms
An introduction to programming
Full understanding of Python fundamentals
Combining multiple ideas in large projects
How computers interpret programming languages
7
What is This Course About?
A course about managing complexity
Mastering abstraction
Programming paradigms
An introduction to programming
Full understanding of Python fundamentals
Combining multiple ideas in large projects
How computers interpret programming languages
Different types of languages: Scheme & SQL
7
What is This Course About?
A course about managing complexity
Mastering abstraction
Programming paradigms
An introduction to programming
Full understanding of Python fundamentals
Combining multiple ideas in large projects
How computers interpret programming languages
Different types of languages: Scheme & SQL
A challenging course that will demand a lot of you
7
Alternatives to CS 61A
CS 10: The Beauty and Joy of Computing
9
CS 10: The Beauty and Joy of Computing
9
CS 10: The Beauty and Joy of Computing
9
CS 10: The Beauty and Joy of Computing
Designed for students without prior experience
9
CS 10: The Beauty and Joy of Computing
Designed for students without prior experience
A programming environment created by Berkeley, now used in courses around the world and online
9
CS 10: The Beauty and Joy of Computing
Designed for students without prior experience
A programming environment created by Berkeley, now used in courses around the world and online
9
CS 10: The Beauty and Joy of Computing
Designed for students without prior experience
A programming environment created by Berkeley, now used in courses around the world and online
9
CS 10: The Beauty and Joy of Computing
Designed for students without prior experience
A programming environment created by Berkeley, now used in courses around the world and online
An introduction to fundamentals (& Python) that sets students up for success in CS 61A
9
CS 10: The Beauty and Joy of Computing
Designed for students without prior experience
A programming environment created by Berkeley, now used in courses around the world and online
An introduction to fundamentals (& Python) that sets students up for success in CS 61A
Taught in Fall 2016 by Dan Garcia
9
CS 10: The Beauty and Joy of Computing
Designed for students without prior experience
A programming environment created by Berkeley, now used in courses around the world and online
An introduction to fundamentals (& Python) that sets students up for success in CS 61A
Taught in Fall 2016 by Dan Garcia
More info: cs10.org
9
Data Science 8: Foundations of Data Science
10
Data Science 8: Foundations of Data Science
Fundamentals of computing, statistical inference, & machine learning applied to real-world data sets
10
Data Science 8: Foundations of Data Science
Fundamentals of computing, statistical inference, & machine learning applied to real-world data sets
10
Data Science 8: Foundations of Data Science
Fundamentals of computing, statistical inference, & machine learning applied to real-world data sets
Great programming practice for CS 61A
10
Data Science 8: Foundations of Data Science
Fundamentals of computing, statistical inference, & machine learning applied to real-world data sets
Great programming practice for CS 61A
Cross-listed as CS C8, Stat C8, & Info C8
10
Data Science 8: Foundations of Data Science
Fundamentals of computing, statistical inference, & machine learning applied to real-world data sets
Great programming practice for CS 61A
Cross-listed as CS C8, Stat C8, & Info C8
Taught in Fall 2016 by Ani Adhikari
10
Data Science 8: Foundations of Data Science
Fundamentals of computing, statistical inference, & machine learning applied to real-world data sets
Great programming practice for CS 61A
Cross-listed as CS C8, Stat C8, & Info C8
Taught in Fall 2016 by Ani Adhikari
More info: data8.org & databears.berkeley.edu
10
Course Policies
Course Policies
12
Course Policies
12
Learning
Course Policies
12
Learning
Community
Course Policies
12
Learning
Course Staff
Community
Course Policies
12
Learning
Course Staff
Details...
http://cs61a.org/articles/about.html
Community
Collaboration
13
Collaboration
13
Asking questions is highly encouraged
Collaboration
• Discuss everything with each other; learn from your fellow students!
13
Asking questions is highly encouraged
Collaboration
• Discuss everything with each other; learn from your fellow students!
• Homework can be completed with a partner
13
Asking questions is highly encouraged
Collaboration
• Discuss everything with each other; learn from your fellow students!
• Homework can be completed with a partner
• Projects should be completed with a partner
13
Asking questions is highly encouraged
Collaboration
• Discuss everything with each other; learn from your fellow students!
• Homework can be completed with a partner
• Projects should be completed with a partner
• Choose a partner from your discussion section
13
Asking questions is highly encouraged
Collaboration
• Discuss everything with each other; learn from your fellow students!
• Homework can be completed with a partner
• Projects should be completed with a partner
• Choose a partner from your discussion section
13
The limits of collaboration
Asking questions is highly encouraged
Collaboration
• Discuss everything with each other; learn from your fellow students!
• Homework can be completed with a partner
• Projects should be completed with a partner
• Choose a partner from your discussion section
13
• One simple rule: Don’t share your code, except with your partner
The limits of collaboration
Asking questions is highly encouraged
Collaboration
• Discuss everything with each other; learn from your fellow students!
• Homework can be completed with a partner
• Projects should be completed with a partner
• Choose a partner from your discussion section
13
• One simple rule: Don’t share your code, except with your partner
• Copying project solutions causes people to fail
The limits of collaboration
Asking questions is highly encouraged
Collaboration
• Discuss everything with each other; learn from your fellow students!
• Homework can be completed with a partner
• Projects should be completed with a partner
• Choose a partner from your discussion section
13
• One simple rule: Don’t share your code, except with your partner
• Copying project solutions causes people to fail
• We really do catch people who violate the rules, because...
The limits of collaboration
Asking questions is highly encouraged
Collaboration
• Discuss everything with each other; learn from your fellow students!
• Homework can be completed with a partner
• Projects should be completed with a partner
• Choose a partner from your discussion section
13
• One simple rule: Don’t share your code, except with your partner
• Copying project solutions causes people to fail
• We really do catch people who violate the rules, because...
• We also know how to search the web for solutions
The limits of collaboration
Asking questions is highly encouraged
Collaboration
• Discuss everything with each other; learn from your fellow students!
• Homework can be completed with a partner
• Projects should be completed with a partner
• Choose a partner from your discussion section
13
• One simple rule: Don’t share your code, except with your partner
• Copying project solutions causes people to fail
• We really do catch people who violate the rules, because...
• We also know how to search the web for solutions
• We use computers to check your work
The limits of collaboration
Asking questions is highly encouraged
Collaboration
• Discuss everything with each other; learn from your fellow students!
• Homework can be completed with a partner
• Projects should be completed with a partner
• Choose a partner from your discussion section
13
• One simple rule: Don’t share your code, except with your partner
• Copying project solutions causes people to fail
• We really do catch people who violate the rules, because...
• We also know how to search the web for solutions
• We use computers to check your work
The limits of collaboration
Asking questions is highly encouraged
Build good habits now
Expressions
Types of expressions
15
Types of expressions
15
An expression describes a computation and evaluates to a value
18 + 69
Types of expressions
15
An expression describes a computation and evaluates to a value
18 + 696
23
Types of expressions
15
An expression describes a computation and evaluates to a value
18 + 696
23
p3493161
Types of expressions
15
An expression describes a computation and evaluates to a value
18 + 696
23
p3493161
sin⇡
Types of expressions
15
An expression describes a computation and evaluates to a value
18 + 696
23
p3493161
sin⇡
|� 1869|
Types of expressions
15
An expression describes a computation and evaluates to a value
18 + 696
23
p3493161
sin⇡
100X
i=1
i
|� 1869|
Types of expressions
15
An expression describes a computation and evaluates to a value
18 + 696
23
p3493161
sin⇡
100X
i=1
i
|� 1869|
✓69
18
◆
Types of expressions
15
An expression describes a computation and evaluates to a value
18 + 696
23
p3493161
sin⇡
f(x)100X
i=1
i
|� 1869|
✓69
18
◆
Types of expressions
15
An expression describes a computation and evaluates to a value
18 + 696
23
p3493161
sin⇡
f(x)100X
i=1
i
|� 1869|
✓69
18
◆
2100
Types of expressions
15
An expression describes a computation and evaluates to a value
18 + 696
23
p3493161
sin⇡
f(x)100X
i=1
i
|� 1869|
✓69
18
◆
2100
log2 1024
Types of expressions
15
An expression describes a computation and evaluates to a value
18 + 696
23
p3493161
sin⇡
f(x)100X
i=1
i
|� 1869|
✓69
18
◆
2100
log2 1024
7 mod 2
Types of expressions
15
An expression describes a computation and evaluates to a value
18 + 696
23
p3493161
sin⇡
f(x)100X
i=1
i
|� 1869|
✓69
18
◆
2100
log2 1024
7 mod 2
limx!1
1
x
Types of expressions
15
An expression describes a computation and evaluates to a value
18 + 696
23
p3493161
sin⇡
f(x)100X
i=1
i
|� 1869|
✓69
18
◆
2100
log2 1024
7 mod 2
limx!1
1
x
Types of expressions
15
An expression describes a computation and evaluates to a value
Call Expressions in Python
All expressions can use function call notation
(Demo)
16
Anatomy of a Call Expression
17
Anatomy of a Call Expression
17
add ( 2 , 3 )
Anatomy of a Call Expression
17
add ( 2 , 3 )
Anatomy of a Call Expression
17
add ( 2 , 3 )
Operator
Anatomy of a Call Expression
17
add ( 2 , 3 )
Operator Operand Operand
Anatomy of a Call Expression
17
add ( 2 , 3 )
Operator Operand Operand
Operators and operands are also expressions
Anatomy of a Call Expression
17
add ( 2 , 3 )
Operator Operand Operand
Operators and operands are also expressions
So they evaluate to values
Anatomy of a Call Expression
17
Evaluation procedure for call expressions:
add ( 2 , 3 )
Operator Operand Operand
Operators and operands are also expressions
So they evaluate to values
Anatomy of a Call Expression
17
Evaluation procedure for call expressions:
add ( 2 , 3 )
Operator Operand Operand
Operators and operands are also expressions
1. Evaluate the operator and then the operand subexpressions
So they evaluate to values
Anatomy of a Call Expression
17
Evaluation procedure for call expressions:
add ( 2 , 3 )
Operator Operand Operand
Operators and operands are also expressions
1. Evaluate the operator and then the operand subexpressions
2. Apply the function that is the value of the operator subexpression to
the arguments that are the values of the operand subexpression
So they evaluate to values
mul(add(4, mul(4, 6)), add(3, 5))
Evaluating Nested Expressions
18
mul(add(4, mul(4, 6)), add(3, 5))
Evaluating Nested Expressions
18
mul(add(4, mul(4, 6)), add(3, 5))
Evaluating Nested Expressions
18
mul
mul(add(4, mul(4, 6)), add(3, 5))
add(4, mul(4, 6))
Evaluating Nested Expressions
18
mul
mul(add(4, mul(4, 6)), add(3, 5))
add(4, mul(4, 6))
Evaluating Nested Expressions
18
mul
add
mul(add(4, mul(4, 6)), add(3, 5))
add(4, mul(4, 6))
Evaluating Nested Expressions
18
mul
add 4
mul(add(4, mul(4, 6)), add(3, 5))
add(4, mul(4, 6))
Evaluating Nested Expressions
18
mul
add 4
mul(4, 6)
mul(add(4, mul(4, 6)), add(3, 5))
add(4, mul(4, 6))
Evaluating Nested Expressions
18
mul
add 4
mul(4, 6)
mul 4 6
mul(add(4, mul(4, 6)), add(3, 5))
add(4, mul(4, 6))
Evaluating Nested Expressions
18
mul
add 4
mul(4, 6)
mul 4 6
mul(add(4, mul(4, 6)), add(3, 5))
add(4, mul(4, 6))
Evaluating Nested Expressions
18
mul
add 4
mul(4, 6)
mul 4 6
24
mul(add(4, mul(4, 6)), add(3, 5))
add(4, mul(4, 6))
Evaluating Nested Expressions
18
mul
add 4
mul(4, 6)
mul 4 6
24
mul(add(4, mul(4, 6)), add(3, 5))
add(4, mul(4, 6))
Evaluating Nested Expressions
18
28mul
add 4
mul(4, 6)
mul 4 6
24
mul(add(4, mul(4, 6)), add(3, 5))
add(4, mul(4, 6))
Evaluating Nested Expressions
18
28mul
add 4
mul(4, 6)
mul 4 6
24
add(3, 5)
mul(add(4, mul(4, 6)), add(3, 5))
add(4, mul(4, 6))
Evaluating Nested Expressions
18
28mul
add 4
mul(4, 6)
mul 4 6
24
add(3, 5)
add 3 5
mul(add(4, mul(4, 6)), add(3, 5))
add(4, mul(4, 6))
Evaluating Nested Expressions
18
28mul
add 4
mul(4, 6)
mul 4 6
24
add(3, 5)
add 3 5
mul(add(4, mul(4, 6)), add(3, 5))
add(4, mul(4, 6))
Evaluating Nested Expressions
18
28mul
add 4
mul(4, 6)
mul 4 6
24
add(3, 5)
add 3 5
8
mul(add(4, mul(4, 6)), add(3, 5))
add(4, mul(4, 6))
Evaluating Nested Expressions
18
28mul
add 4
mul(4, 6)
mul 4 6
24
add(3, 5)
add 3 5
8
224mul(add(4, mul(4, 6)), add(3, 5))
add(4, mul(4, 6))
Evaluating Nested Expressions
18
28mul
add 4
mul(4, 6)
mul 4 6
24
add(3, 5)
add 3 5
8
224mul(add(4, mul(4, 6)), add(3, 5))
add(4, mul(4, 6))28mul
add 4
mul(4, 6)
mul 4 6
24
add(3, 5)
add 3 5
8
Evaluating Nested Expressions
19
224mul(add(4, mul(4, 6)), add(3, 5))
add(4, mul(4, 6))28mul
add 4
mul(4, 6)
mul 4 6
24
add(3, 5)
add 3 5
8
Evaluating Nested Expressions
19
Expression tree
224mul(add(4, mul(4, 6)), add(3, 5))
add(4, mul(4, 6))28mul
add 4
mul(4, 6)
mul 4 6
24
add(3, 5)
add 3 5
8
Evaluating Nested Expressions
19
Expression tree
Operand subexpression
224mul(add(4, mul(4, 6)), add(3, 5))
add(4, mul(4, 6))28mul
add 4
mul(4, 6)
mul 4 6
24
add(3, 5)
add 3 5
8
Evaluating Nested Expressions
19
Expression tree
Operand subexpression
Value of subexpression
224mul(add(4, mul(4, 6)), add(3, 5))
add(4, mul(4, 6))28mul
add 4
mul(4, 6)
mul 4 6
24
add(3, 5)
add 3 5
8
Evaluating Nested Expressions
19
Expression tree
Operand subexpression
1st argument to mulValue of subexpression
224mul(add(4, mul(4, 6)), add(3, 5))
add(4, mul(4, 6))28mul
add 4
mul(4, 6)
mul 4 6
24
add(3, 5)
add 3 5
8
Evaluating Nested Expressions
19
Expression tree
Operand subexpression
1st argument to mul
Value of the whole expression
Value of subexpression
Functions, Objects, and Interpreters
(Demo)
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![61A Lecture 12 - University of California, Berkeleycs61a/sp15/assets/slides/... · 2015. 6. 14. · [Demo]! BABY same_person Unicode character name. Some Objects Can Change First](https://img.pdfslide.net/doc/110x75/6140194ee59fcb3c636a47ae/61a-lecture-12-university-of-california-berkeley-cs61asp15assetsslides.jpg)
