for the first lecture of, well, Introduction

to Computing and Programming.

Also known as CS50 or well, CPSC 100, officially here at Yale.

>> So we couldn't be more excited to welcome you all here.

My name is Patrick Rebeschini.

I'm the head instructor for the class.

I am here representing a group of about 60 staff members

that will work with you throughout the semester.

This number is almost 60 of us.

Yet along the extraordinary level of commitments

that we put into this class, makes CS50 the class

at Yale University that offers the greatest level of support

to all of you.

And we couldn't be more proud of offering this class here again.

>> In fact, as you will soon experience, CS50 is much more than a class.

It's a community.

And you will be part soon of this community.

This is the second year that Yale is offering this class.

We are building on the extreme success of last year, where

for the first time, here at this university,

undergraduate learning assistant were adopted in classrooms.

It all started with this class last year.

>> So as you know, the class is taught jointly with Harvard University.

To teach this course we are relying-- we can

count on the great expertise of David Malan and the Harvard team.

So David has been teaching CS50 for well, 10 years now.

And every year he has been pushing the boundaries

and improving the classroom experience.

Again, we couldn't be more happy to continue this collaboration with them.

>> In fact, one of the most interesting parts,

I will say of running this class now, both at Harvard and here at Yale,

is the really incredible cross-fertilization

of ideas, aimed at improving the learning experience to you all.

So as a result of this extensive collaboration between the two

university, CS50 is proud to announce the new version this year

with noticeable changes.

David will all tell us about them now.

So please-- this being said, please join me

and welcome to give a big round of applause

to welcome David and Harvard team here at Yale.

>> [APPLAUSE]

>> DAVID MALAN: Thank you.

Thanks.

This is CS50, Harvard University's and Yale University's introduction

to the intellectual enterprises of computer science

and the art of programming.

And what that means is that this course ultimately, is about problem solving.

Indeed many of you might have come out of high school

or have spent the past couple of years wondering what some of your friends

did last year or in other classes.

And yet, the reality is, no matter what we

do at the end of the day in this class, it's going to be about problem solving.

>> And as such, perhaps take some reassurance in the fact

that 73% of the students that take this class, both here

at Yale as well as at Harvard, have never taken a CS class before.

So if you're sitting here in the audience today wondering

why you are sitting here in the audience today,

or maybe you just followed along with some friends,

or maybe you've been a little curious as to what

computer science and programming is, realize

that most of your classmates to the left and to the right of you

are very much in that same demographic.

>> And indeed, if we look at last year statistics

within the student body of CS50, both here and at Harvard, 58% of students

describe themselves as less comfortable.

9% is more comfortable.

And then 33% is somewhere in between.

And there's no formal definition of what these buckets means.

You sort of know you're less comfortable if you are.

You're feeling a little uneasy with maybe being in the class.

You're not quite sure if a computer science class is ultimately for you,

and realize that you are in very good company.

And indeed the grading, and the assessment,

and the feedback, and all of that support structure in the class

is ultimately very much individualized.

More so than most any other class by design.

And indeed, what ultimately matters in this class is not

so much where you end up relative to others,

but where you, in week 11 or last, and relative to yourself in week

0 here our first.

So what does that mean?

Well, this means of those 73% of students last year that had never taken

a CS class before, by the start of the semester they

were dabbling in a language called Scratch, which we ourselves

will see here today.

And by the end of the semester had they gone

through this entire list of challenges.

Starting with a language called c.

Implementing, what's at first glance, going

to be a bit of a challenge for some, but fairly gratifying once you

get Super Mario bouncing up and down a pyramid

implemented, albeit, with just something called ASCII art.

Implementing last year-- what the students last year then

did after that was implement their own Caesar cipher and vigenere cipher.

So encryption algorithms with which you could

scramble information and then unscramble information to send secret messages.

The game of 15.

If you remember from childhood or some party favor,

that little plastic game where you move the numbers up, down, left and right

to try to get them in order, actually implementing that game

and solving the logic required there.

And then we dabbled in forensics last year.

>> So by mid-semester, students who had never

used their keyboards for this purpose before,

were writing software to recover, so to speak,

JPEGs or photographs that we had accidentally

deleted from a digital memory card from a camera.

Recovering secret messages from inside of a bitmap image,

and other such types of graphics as well.

>> We then transitioned to giving the whole class a dictionary.

Just a really big text file with 150,000 English words.

And everyone was challenged to somehow read, so to speak,

those words into memory.

Into the computer's memory.

And then answer questions of the form, is this a word?

Is this a word?

Is this a word?

Really just implementing a spell checker.

And then challenging each other with a big board--

a leader board to see who could use the least amount of memory,

in the least amount of time to actually spell check large documents.

>> We transitioned from then to implementing ones own web server.

So not making web pages in languages like HTML and CSS, if you're familiar.

But actually implementing the server that

listens on the internet for requests from browsers

and then responding to those requests.

Then implementing our own e-trade like website, where

students could buy and sell stocks.

Drawing in nearly real time stock quotes from Yahoo Finance.

And allowing students to see how their portfolio develops.

And then finally a mash up of Google News and Google

Maps whereby students by term by terms end

had the ability to click, and round, and search on a Google map.

And then see all of the news articles that

are proximal to those particular areas.

So truly going from zero to 60.

>> And along the way having what we had last year called, hacker additions.

That raise the bar further for those of you

who might very well have a good amount of experience being in that 9%

of more comfortable.

So realize that there's a very high ceiling

even within those challenges for students

coming from a different background.

Because at the end of the day, we're ultimately

focused quite simply on this.

>> But what does this mean, problem solving?

So let's propose that we distill it like this.

So problem solving is really just this kind of picture.

So you've got inputs to some problem, something you actually want to solve.

The goal is to get outputs, a solution to that problem.

And then in the middle is what we'll call a black box.

You don't necessarily know or even care what's inside that black box.

All you know is that when you feed input into it,

you hopefully get output or a solution from it.

And while today we'll look both at inputs and outputs,

we'll long term, and over the course of the whole semester,

focus on what's inside that box.

>> And therein will lie something called algorithms.

Step by step instructions for actually solving some problems.

But what's an example of some inputs?

So maybe a simple thing at the start of every school year, someone

might want to take attendance.

So we might do one, two, three, four, five, six,

and how would I keep track of that information.

I might just go one, two, three, four, five, six.

And just use sort of single digits.

>> Or I could actually record this a little longer term.

And how do I represent all the humans in this room?

Well, I might do something like, OK.

I see one person.

All right.

I see another person, a third person, and so forth.

But no one counts people like this.

So literally, most of us if we're even going to draw anything at all,

are probably going to go one, two, three, four,

maybe get a little fancy, five, six, seven, eight, nine, ten and so forth.

>> And that's actually a system called unary.

Uno, like uno implying one, where you just have one letter of the alphabet.

You've just got this hash mark.

And I, for efficiency, just drew these hash marks, ultimately

as straight lines.

But I could have drawn them as little stick figures.

Where to represent one person, one input,

I just draw a stick figure or a hash mark.

But this isn't all that expressive.

>> If all I have is these hash marks, let alone stick figures,

how might I represent something like the number 15?

Or 15 people in the room?

I might have to do something like 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,

14, 15.

It just does not scale very well.

As the inputs get large, we need a better system than this.

>> And it turns out that the system that computers use

is not all that different from what you and I know.

In fact, most people in this room, even if you are among those less

comfortable, don't necessarily know how your Mac or PC really works,

you've probably at least heard, that underneath the hood are 0's and 1's.

The so-called binary system.

So indeed, computers have more than just hash marks in their vocabulary,

but not as much of a vocabulary as we humans.

>> Indeed, we humans don't use binary.

Bi meaning 2, 0 and 1.

But decimal, deca meaning 10, 0 through 9.

So we have a lot more expressive capabilities in our normal human world.

But I'd argue that these systems, binary, and decimal, and everything

in between and beyond, are actually all quite familiar.

For instance, consider this example here, 123.

So this really is, of course, a number we know as 123.

But all I just drew was just this pattern of symbols, glyphs so to speak.

Sort of shapes on the board in chalk.

>> But why do we immediately and intuitively grasp this as 123?

Well, if you were like me in grade school,

you probably learned that this is the 1s column, this is the 10s column,

this is the 100s column.

And why is that useful?

Well, it's simple arithmetic you now do to get from a pattern of symbols

to a number we understand intuitively.

Is what, 100 times 1, and then 10 times 2, and 1 times 3,

which of course is just 100, and this is 20, and this is three.

And so if we add those together-- ah.

So therein lies the sort of reasoning behind why this set of symbols

means something real and numeric.

>> Well, computers do the exact same thing, but they only can count as high as one.

Whereas I was able to count as high as three.

And in fact, if I kept going I could go as high as nine in this system.

Computers only have zeros and ones in their alphabet.