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  • >> [MUSIC PLAYING]

  • >> [MUSIC PLAYING]

  • DAVID MALAN: All right.

  • This is CS50.

  • [MUSIC PLAYING Tritonal, Cash Cash, "Untouchable"]

  • [MUSIC PLAYING]

  • SPEAKER 1: I'm going to France, and you're going, too.

  • [MUSIC PLAYING]

  • DAVID MALAN: This is CS50, Harvard University's introduction

  • to the intellectual enterprises of computer science

  • and the arts of program-- and for the first time in history,

  • Yale University's as well.

  • Indeed, whether you're here in Cambridge or in New Haven or Miami or St. Louis

  • or Amsterdam or anywhere around the world

  • taking CS50, computer science E50, CS50X, CS50 AP,

  • we are all one and the same.

  • Welcome to CS50.

  • >> What we have--

  • >> [APPLAUSE]

  • >> [LAUGHS]

  • >> [APPLAUSE]

  • >> So I made a mistake myself some time ago when I started off college.

  • And I got to college, and I decided to frankly, stick within my comfort zone.

  • I ended up declaring a concentration, or a major, of government.

  • Ant that was mostly a function of me being pretty familiar with government

  • or at least history or I really liked constitutional law in high school.

  • And so when I got here, I kind of gravitated toward things

  • with which I was already familiar.

  • Right?

  • God forbid I do poorly in the class.

  • I certainly wanted to stay within my comfort zone,

  • and it wasn't until sophomore year that I finally

  • got up the nerve to step foot in a classroom called CS50.

  • And at that point, did I finally realize that, my God, homework could actually

  • be fun.

  • >> Indeed, I was one of those kids that on Friday evenings when

  • the P-SETS would be released, I would go back to my room and dive

  • into the night's P-SETS.

  • And for me, that was a sign that this was a field for me.

  • But what was more important was the fact that I did get up this nerve

  • to explore waters unfamiliar to me and get beyond my own comfort zone

  • and frankly, I only was able to do that sophomore year by taking this class

  • pass/fail.

  • >> Indeed, it was the very last day that I finally switched over and finally

  • declared CS as my concentration, putting gov at that point behind me.

  • And so we're not setting out in this course to turn all of you

  • into CS majors or concentrators, but rather to give you an opportunity

  • to hopefully go beyond the world with which you're currently familiar

  • and bring back from this world skills and knowledge and savvy

  • that you can apply to your own world, whether that's

  • in the humanities, social sciences, natural sciences, or beyond.

  • >> Indeed, if you're feeling a little intrepid

  • about being in this room let alone in this class,

  • realize that if history is any indication, 72% of you

  • have never taken a CS course before.

  • So it is by all means not the case that the student sitting to the left

  • or to the right or in front or behind you knows far more about CS

  • or programming in particular than you.

  • That's not in fact the case.

  • And indeed, much of the support structure

  • that we've set up in this course over the past many years

  • has been for exactly that reason-- to provide an on ramp that still exits

  • just as rigorously and just as high as ever--

  • but the slope of which allow students less comfortable and more comfortable

  • alike to succeed irrespective of his or her prior background.

  • >> Indeed, what ultimately matters in this class is not

  • so much where you end up relative to your classmates

  • but where you in week 12 end up relative to yourself

  • in week zero, which is where we are here today.

  • >> Indeed and this may very well and probably does look like Greek

  • to many of you.

  • But rest assured, that this and so much more

  • is going to be completely within your grasp in just a little bit of time.

  • >> But today, we focus on some of the higher level ideas

  • to give you a taste of CS50 and computer science

  • in a sense of what you're signing up for.

  • And indeed, computer science might be distilled more

  • simply as computational thinking-- thinking like a computer, if you will.

  • And there's so many different things ingredients that go into that,

  • but let's propose just three for today.

  • If the goal of the class ultimately is not to teach you programming,

  • is not to teach you C or PHP or SQL or any number of the words

  • and acronyms in the course's description,

  • but rather to teach you to solve problems more effectively

  • and to think more methodically and more algorithmically, so to speak.

  • Let's see what exactly this means.

  • >> So I would propose that thinking computationally boils down

  • to solving problems.

  • What do you need to solve a problem?

  • You need to input-- like the input to the problem--

  • you need an output, which is hopefully the solution,

  • and then you need a process by which to solve that problem, which

  • we'll call an algorithm-- a set of instructions for solving some problem.

  • >> But first, let's focus on the first and the last of these inputs and outputs.

  • Computers after all, apparently only understands zeros and ones.

  • But how can that possibly be?

  • Even if you're not familiar at all with what's underneath the hood,

  • you probably at least heard that computers understand binary--

  • just zeros and ones-- but how can you possibly do anything interesting?

  • >> Well, one of the themes of the class is going

  • to be this layering-- where today, we'll take a quick glance at the lowest level

  • details, but with each passing day, where we layer

  • or abstract on top of those details to actually solve higher level

  • problems of interest to us.

  • >> So here is what we might call binary-- with just an alphabet of 0 and 1.

  • But we humans are mostly familiar with decimal.

  • Dec meaning 10.

  • Bi meaning two.

  • And so in the decimal system, we have 10 digits

  • at our disposal-- of course, zero through nine.

  • So if you look at a number like this, most of you

  • intuitively just grasp that is 123.

  • There's nothing really hard about that.

  • But why is it 123?

  • Well, if you think back to grade school-- or at least

  • the way I learned this kind of world-- you

  • might recall that we treated these things in columns, or places.

  • >> So we have the ones place on the right.

  • The tens place in the middle.

  • The hundreds place on the left.

  • And then how do we get from this pattern symbols--

  • 1 2 3-- to this higher level idea that we know as 123?

  • Well, it's just some simple arithmetic.

  • Right?

  • >> The one there is essentially means give us 100 times 1 plus 10 times

  • 2 plus 1 times 3.

  • And of course if we do out the math there, it's 100 plus 20

  • plus 3-- otherwise known as 123.

  • >> So if you're on the same page as that right

  • now and are comfortable with the so-called decimal system as a human,

  • it's actually well within your scope of comfort

  • to consider now the binary system.

  • Take a wild guess-- this represents, in the world of computers

  • in binary-- what number?

  • Zero.

  • >> But why is that?

  • Well, it turns out that the columns or places here-- they're not powers of 10.

  • 1, 10, 100, 1,000, and so forth.

  • They're instead, quite simply, powers of 2.

  • So, 1, 2, 4, 8, 16, 32, and so on.

  • And so now we of course get to 0 here simply because we have 4 times

  • 0 plus 2 times 0 plus 1 times 0, which of course gives us 0.

  • >> But how do I go about representing the number 1?

  • What's the pattern of zeros and ones to represent

  • the number we humans know as 1?

  • 001.

  • And 2?

  • 010.

  • >> And now the pattern starts to repeats.

  • Now it's 011.

  • And again, 0 fours, one 2, one 1.

  • So 2 plus 1.

  • That's 3.

  • >> And now to represent 4, we don't just change that 0 to a 1.

  • You sort of have to carry, so to speak, and the numbers

  • start flipping around just like in the decimal world.

  • >> So this is 4.

  • This is 5.

  • This is 6.

  • This is 7.

  • And so we've counted as high as 7.

  • >> Now all we just need is more a bits-- more zero's and one's.

  • And indeed "bits", if you've heard this term-- binary digit.

  • Bit is where that comes from.

  • And so if we want to represent bigger numbers, we need more bits.

  • But let's move away from slides now to something a little more real.

  • Suppose that we want to actually represent this thing.

  • >> Well let's take a look now at a little demonstration.

  • So this is a web based application that one of CS50's own, Michael G,

  • put together this summer to help us elucidate exactly this idea.

  • And would someone like to venture up on stage

  • in front of all his or her classmates?

  • Right there in front.

  • Come on up.

  • >> You have to be comfortable on camera and the internet.

  • Oh, right here.

  • OK.

  • We're OK.

  • All right.

  • Come on up.

  • What's your name?

  • Emily come on up.

  • So this is Emily.

  • What year are you?

  • >> Freshman.

  • >> Emily, nice to meet you.

  • David.

  • >> All right.

  • So up on the screen here, we have this touch screen

  • which is going to allow us to actually interact with this program,

  • and it's just a browser.

  • It's Chrome full screened at the moment, but it's

  • been programmed by Michael to respond in a way that allows

  • us to play around with binary digits.

  • >> So for instance, here we have not three but eight bits-- zeros and ones.

  • Right now, we're looking at the number 0.

  • And indeed, all eight zeros in decimal means zero.

  • So that's all that's being hinted at here.

  • >> So if you wanted to represent the number 8,

  • what's the pattern of zeros and ones that you want?

  • You can simply tap up or down or the numbers themselves.

  • All right.

  • So that of course is 8, as you can see up there.

  • And if we wanted to do 16, what do we do?

  • >> Yep, just touch it again.

  • 16.

  • All right.

  • So this is all fine and good, it's still very low level.

  • We need a way in the real world for Emily

  • of actually representing these things.

  • And so suppose that we turn these zeros and ones, which is very

  • conceptual, into actual light bulbs.

  • Right?

  • >> A computer is a physical, mechanical, electrical device.

  • And its input-- at least if you plug it in or charge it--

  • is to have battery power and electrons flowing in and out.

  • >> So now, why don't we stop thinking about bits as zeros and ones,

  • but something more physical like light bulbs here.

  • And if Dan Armendariz could join me for just a moment-- come on up--

  • we're going to queue up an application.

  • >> Come on over, Emily.

  • Sorry this is the most awkward demo for you ever.

  • Come on over here.

  • We're going to queue up with thanks to Dan

  • Armendariz, another member of our staff, an application known as binary bulb.

  • >> So what we have here is an iPad application

  • that has the following user interface on the screen for Emily.

  • It's just got the same exact UI essentially that's over there.

  • And if you now want to represent the number, say 8,

  • how would you go about doing this noticing at the right,

  • the light bulbs that we have here?

  • Ah-ha.

  • Magical.

  • So if we want to now turn this into something a little more challenging,

  • and let's go ahead and pick a random number like the number 50 here.

  • Input this.

  • And if you can now be challenged to come up with the number 50,

  • we'll have a fabulous prize for you.

  • >> EMILY: OK.

  • Oh my God.

  • DAVID MALAN: Arithmetic is indeed hard in front

  • of hundreds of your classmates.

  • But 50 has been the answer here.

  • >> [APPLAUSE]

  • >> And so now, this is meant to be demonstrative for Emily.

  • So, in here, is some light bulbs quite like these,

  • but it's actually the little magnetic strips.

  • And what's cool about these and the reason we use them in CS50

  • is that they support something called an API-- an application programming

  • interface, which is just a fancy way of saying that what one of our staff

  • did over the summer was create an iPad application here

  • that talks over the internet to the light bulbs over here,

  • which are wirelessly connected to another device.

  • But this is now an option for final projects.

  • And so Emily, if you would so like, at the end of the term,

  • you can adorn your dorm room in the meantime with those.

  • Thank you to Emily as well.

  • >> [APPLAUSE]

  • >> But now, let's turn our attention to what

  • that message might have looked like, and it's a little something like this.

  • In fact, this is an example just as a teaser

  • of what's to come of what's called an API request.

  • And so what we have here is simply exactly the kinds of message

  • that after a few weeks time in CS50, you'll

  • be able to send to something fairly familiar like that to actually

  • turn them on and off.

  • But this is all fine and good.

  • Right?

  • We have the mental model hopefully for representing numbers with

  • zero's and one's.

  • And from zeros and ones, we can get to higher numbers like 50,

  • as Emily just did, or we can move up from that.

  • And I claim that we can represent things like letters as well.

  • Right?

  • >> Computers are far more interesting than just numbers.

  • And so how do you go about representing words

  • on the screen or emails or essays or the like?

  • Well, it turns out that computers simply abstract on top of these low level

  • details, and humans some time ago, came up with an arbitrary, but a consistent,

  • mapping of numbers to letters-- so that any time you see a capital letter

  • A on your computer screen, odds are what's

  • underneath the hood is a pattern of zeros and ones

  • that represent the number, per this chart, 65.

  • >> And more physically inside of your computer,

  • are millions of things called transistors-- these days-- which

  • are just switches if you will, things that can go on and off and so imagine.

  • Not eight of these large light bulbs but millions of these tiny little light

  • bulbs, or switches or transistors, that can turn on and off

  • based on how you program them.

  • And so now we have a way of representing letters as well.

  • >> In fact, if I were to use this mapping here and try to actually

  • spell something out, we might look at this pattern of decimal digits

  • right now.

  • So we're not going to even focus on binary anymore.

  • Let's just consider these as decimal number 72, 73, 33.

  • But what might this represent?

  • Anyone have a sufficiently photographic memory

  • to know what's spelled on the screen here?

  • Yeah a few.

  • So hi.

  • H-I and then an exclamation point, which was not actually on the screen.

  • But indeed there's a mapping for every letter to every number

  • that you might want to type on your keyboard.

  • >> But numbers don't have to represent just letters.

  • Right?

  • All of us know about images and photographs and audio files

  • and video files and the like.

  • So clearly we can represent higher level things still.

  • And so what a computer does is simply choose

  • to interpret patterns of zero ones differently based on the context.

  • >> If you double click a Microsoft Word icon,

  • you see words on the screen instead of colors and pictures

  • because word knows that this is an essay that you've actually typed.

  • If you instead double click on a JPEG or a GIF or a PNG,

  • it opens up and is an image because the .PNG or the .docx or whatever the file

  • extension is and whatever software you're using knows to interpret

  • a pattern of zeros and ones differently based on what its purpose in life is.

  • >> So for instance, this same sequence of numbers

  • might represent how much red do you want, how much green do you want,

  • and how much blue do you want.

  • And indeed, if you've ever heard RGB-- so just red green blue.

  • And so if I see numbers like, this give me 72 red, give me 73 green,

  • and 33 blue, this is how a computer using three bytes-- where

  • a byte is eight bits or 24 bits-- would represent a pretty nasty shade

  • of brown or yellow here.

  • And in different contexts, could those exact same patterns in zeros and ones

  • mean something completely different as well.

  • >> So we have now a way of representing information-- zeros and ones.

  • On top of that, we get letters.

  • On top of that, we might get colors.

  • And let's assume for today that we can get audio and video

  • and things so much more sophisticated than that.

  • >> But now let's consider how we use those inputs

  • and produce those outputs now that we have

  • a way of representing that information.

  • Well, we need something called an algorithm.

  • Again, a set of instructions for solving some problem

  • step by step-- and the more precise, the better.

  • >> And so an example with which humans are admittedly less familiar these days,

  • but nonetheless is still with us in software,

  • is the process of looking up someone in a phone book.

  • >> Now, fewer and fewer folks know each year what this relic actually is here.

  • But back in my day, this was a phone book

  • with thousands of pages and numbers and people's names from A through Z.

  • And even though we're kind of cheating a bit-- this is mostly yellow pages.

  • There were also white pages at the time, which

  • had all of those names and numbers of actual human beings.

  • >> And if I wanted to look someone up in a phone book like this today, of course,

  • I just type in the first few characters of his or her name,

  • and my phone finds that information.

  • But the process by which your iPhone or Android phone

  • or whatever is actually finding someone in your contacts list

  • is identical to what we humans probably have done for some time.

  • >> Now I could take this problem, if you will,

  • and the inputs here are not zeros and ones.

  • They're pages-- like, let's say 1,000 pages.

  • And if I wanted to look up someone like Mike Smith in this phone book,

  • I could start at the beginning and see that I'm in the A section

  • and then turn one page at a time, looking and looking

  • as I make to the B's and the C's and the D's and so forth for Mike Smith.

  • Smith starting with an S, I'll hopefully eventually find him.

  • >> Is this algorithm-- that process-- correct?

  • Yeah.

  • It's correct.

  • I will find Mike if he's in here, but what's the caveat that you might offer.

  • It's slow.

  • Right?

  • I know Mike S is sort of toward the latter half of the phone book.

  • Why the heck am I starting at the beginning

  • and going page by page by page.

  • So of course, I could flip it around and start from the back,

  • but that's going to get me there at the same rate,

  • if you willl-- page after page after page.

  • And it's not going to work if I want to search for someone else whose

  • name comes earlier in the alphabet.

  • >> So what if I do what I learned in grade school,

  • again, do things not by ones but by twos.

  • So 2, 4, 6, 8, 10, 12, and so forth.

  • Is that correct?

  • No.

  • It's kind of correct.

  • But some of you who murmured no, where is the problem, or the bug,

  • the mistake so to speak.

  • Yeah.

  • >> STUDENT: You might skip over the right entry.

  • >> DAVID MALAN: Yeah.

  • I might skip over Mike Smith is because I've taken two pages at once

  • and he just happens to be sandwiched between those two pages.

  • I might realize that I'm on to the T section

  • not having found Mike Smith yet.

  • >> And so what might the fixed there be?

  • Well, if I do hit the Ts in the phone book,

  • I might need to double back one or so page.

  • So it's fixable, but it's not quite as simple

  • as just going by two to speed up my performance.

  • But what?

  • Come on.

  • What is what most humans are going to do with this kind of phone book?

  • You're given the phone book.

  • What do you do?

  • >> What's that?

  • Go to the middle.

  • So I heard go to the middle, and I find myself roughly in the M section,

  • so to speak.

  • And now what do I want to do?

  • Good job.

  • What's your name?

  • >> JAMES: James.

  • >> DAVID MALAN: James, all right.

  • What do I do next?

  • JAMES: You go in the half that has the S's.

  • DAVID MALAN: All right.

  • I'm going to go into the half that has the S's in it because, again,

  • a stipulation here was that this thing is sorted.

  • It's a pretty useless 1,000 pages if Verizon doesn't actually

  • sort these things for us A through Z.

  • So if I know Mike is probably in the latter half of the phone book,

  • I can now.

  • >> [LAUGHS]

  • >> Tear the problem in half.

  • >> [APPLAUSE]

  • Thank you.

  • Tear the problem in half.

  • That was actually real-- that struggle.

  • So tear the phone book in half, leaving myself

  • with fundamentally the same problem.

  • But of course, half as large.

  • And if I follow James's advice again, and I go here.

  • I say, oh now I'm in the T section.

  • >> And so of course, I can tear the phone book

  • in half one more time, leaving me with a problem that's

  • now a quarter of the size.

  • So I've gone from 1,000 to 500 to 250 to 125 and so forth.

  • It feels like I'm taking bigger bites out

  • of this problem with each iteration, or each step in it.

  • >> And indeed, the time I'm going to spend finding Mike Smith in this example

  • is so much less because eventually I'm going to whittle this pone book down

  • to just one lone page.

  • And if Mike is on that page, I'm going to go ahead and give him

  • a call having found him.

  • >> But just how much better is that algorithm--

  • that dare say intuitive algorithm-- than the ones we

  • started with which we're very linear-- left to right-- at a pace of 1 or 2x?

  • >> Well, let's plot this.

  • We don't have to worry too much about math or numbers in this case here.

  • We just look at a plot.

  • So on the x, or horizontal axis, is the size of the problem--

  • how many pages are there.

  • On the y, or the vertical axis, is how much time

  • is it going to take me to solve it.

  • And maybe that's how many page turns, how many seconds,

  • how many-- some unit of measures.

  • >> And I've drawn a red straight lines here because if each additional page

  • of the phone book, I require to make one additional step.

  • So if Verizon adds one more page next year,

  • I might have to flip one more page to find someone like Mike Smith.

  • >> Meanwhile, the second algorithm, which I went by twos, is the same shape.

  • It's still very linear, very left to right, taking equal bytes each time,

  • but the slope is a little lower.

  • >> For instance, if the size of the problem were roughly here

  • and I used my first algorithm, I might end up all the way

  • at the top of that red line.

  • But if I instead use to twosies approach,

  • the yellow line suggests because it's lower,

  • that it's going to take me less time the solve.

  • >> But what's the shape of the third algorithm-- again, arguably

  • the most intuitive algorithm?

  • Well, it looks a little something like this.

  • It's curved, or logarithmic, in shape.

  • And even though it never kind of flattens out,

  • it asymptotically inches up and up and up but terribly slowly

  • versus everything else.

  • And what's the take away?

  • Well, we call it log n.

  • But what does that actually mean?

  • Well if Verizon doubled the number of pages in the phone book

  • next year from 1,000 to 2,000.

  • How many more steps is my first algorithm going to take?

  • >> My first algorithm.

  • Maybe 1,000 more steps.

  • If they doubled the phone book, I'm going

  • to have to flip through another 1,000 pages to find Mike.

  • Of course, if the second algorithm, maybe 500 because I'm

  • going twice as fast.

  • >> But if Verizon doubles the number of pages between this year and next,

  • with my third algorithm-- the divide and conquer that James proposed,

  • going in half and half and half-- how many more steps will

  • it take me next year to have a phone book of a size 2,000?

  • Just one.

  • Because with one bite, I can take, out of that problem, half of the pages

  • away.

  • And if you think about this a little crazily now-- if the phone book doesn't

  • have 1,000 or 2000 page, but let's say 4 billion pages--

  • it's a big phone book-- how many times or how many steps

  • is it going to take me to find Mike Smith in the phone book

  • with 4 billion pages.

  • You can sort of start to do the math.

  • All right.

  • 4 billion divided by 2.

  • So that's 2 billion divided by 1.

  • That's 1 billion.

  • Then half a billion.

  • Then 250-- so you can do this again and again but not that many times before

  • you get to one page.

  • >> And indeed, even if the phone book is 4 billion pages long

  • or the database you're searching is 4 billion records long,

  • it's going to take you give or take 32 steps only to find Mike Smith.

  • And if you double the phone book next year from 4 billion to 8 billion,

  • 33 steps instead of just 32.

  • >> And this is testament to one of the ideas

  • that we might embrace in computer science more generally, which

  • is this computational thinking and approaching a problem

  • frankly using tools from your already familiar tool

  • kit-- your real world with which you're familiar,

  • but harnessing those ideas to actually solve problems.

  • >> But we need to formalize our solutions to these problems.

  • And so let me introduce for a moment something we might call pseudocode.

  • Much of the semester, we'll spend using actual code in languages like C and PHP

  • and JavaScript and SQL and the like.

  • >> But for now, let's just look at something fairly intuitive

  • like English.

  • I might distill that algorithm with which

  • I found Mike into steps like this.

  • >> Pick up the phone book

  • >> Open to middle of phone book

  • Look at the name's

  • If Mike is among the name's

  • Call Mike

  • Else if Smith is earlier in the book

  • Open to the middle of the left half of the book

  • Else go to line 3

  • Else if Smith is later in the book

  • Open to the middle of the right half of the book

  • Go to line three

  • Else

  • Give up

  • And there's a few characteristics now of this that are worth pointing out.

  • So one, all the lines I've highlighted in yellow

  • we're going to start calling statements or functions or procedures.

  • They're just actions do this, and there's not

  • all that much variability to it.

  • >> Next step here though, are these conditions-- if, else, else if, else.

  • And these are called conditions, or branches, and they're decision points.

  • And they allow us to do something conditionally.

  • >> And in fact, let's take a quick look at perhaps a familiar face--

  • we'll call him Bill-- and exactly what these conditions,

  • how these might be used.

  • >> BILL GATES: People make decisions every day.

  • For example, before you go outside you kind of have an if statement that says,

  • if it's raining, then I need to get my jacket.

  • >> And computers are amazing once you decide those kinds of statements

  • that they can reliably execute those things at unbelievable speed.

  • And so a computer program really is a little bit of math and some

  • if statements where the decision gets made.

  • >> DAVID MALAN: So now let's focus on a few different lines--

  • the ones I've highlighted in yellow here.

  • And it turns out there's different ways of expressing this idea.

  • But intuitively what our lines 8 and 11 that I've highlighted here telling you

  • to do?

  • Yes, go to line 3, but what behavior is that really inducing?

  • It's some kind of loop or cycle, and you can kind of see it.

  • Right?

  • If on line 8, you go back to line 3, and then you hit line 8 again,

  • you might go back to line 3, back to line 3, back to line 3.

  • There's this sort of cycle or loop.

  • And indeed, that's induced in line 11 potentially as well.

  • And this is a basic programming construct as well.

  • >> You might not want to just do something with a statement

  • or do something conditionally with a condition or branch.

  • You might want to do something cyclically with a loop.

  • And we'll have someone else with whom you might be familiar-- we'll call him

  • Mark-- explain this concept here.

  • MARK ZUCKERBERG: One thing that computers are

  • really good at is repeating commands.

  • As a person, you'd get really bored if you

  • had to do the same thing lots of times in a row,

  • but a computer can do the same thing millions or even billions of times

  • and not get bored and be able to carry that out really well.

  • >> So for example, if I want to wish everyone

  • on Facebook a happy birthday by sending them an email,

  • it might take me more than a century to actually write out

  • all of those emails to everyone.

  • But with just a few lines of code, I can have a system send an email to everyone

  • on Facebook wishing them a happy birthday.

  • >> So that's what loops are and why they're valuable and something

  • that computers can do very well.

  • >> DAVID MALAN: Many thanks to our friends at code.org for those two films.

  • And just last week, you might have seen that Mark Zuckerberg and Facebook

  • posted this announcement, which is that they just

  • have passed an important milestone for the first time ever.

  • 1 billion people used Facebook in a single day, specifically last Monday.

  • One in seven humans on Earth apparently logged into Facebook.

  • >> Well, this seems a good opportunity to look back on where Facebook began,

  • and we went through CS50's own archives because it turns out in 2005,

  • Mark gave a guest lecture in CS50.

  • You'll see that production values weren't quite the same back then

  • in terms of the technology available, and you'll also

  • see that the presence of this guest lecture

  • didn't necessarily pique the interest of the student body, your predecessors,

  • as much as it might have just a few years later.

  • >> So let's take a look at Science Center C.

  • SPEAKER 2: Please join me, and welcome.

  • [APPLAUSE]

  • MARK ZUCKERBERG: Yo.

  • All right.

  • Cool this is the first time I've ever have had to hold one of these things.

  • So I'm just going to attach it really quickly.

  • All right.

  • Can you hear it?

  • Is this good?

  • Is this amplified at all?

  • All right.

  • Sweet.

  • So, this is like one of the first times I've been to a lecture at Harvard,

  • but--

  • >> DAVID MALAN: So eventually the Science Center did zoom in on the video,

  • but not before capturing this excerpt where Mark's talking,

  • which he discussed his roommate, Dustin, who

  • wanted to lend a hand with this site called the Facebook.com

  • and realized that Mark is about to mention to programming languages--

  • one called Pearl, one called PHP-- as he discusses

  • the origins of Dustin's contribution.

  • MARK ZUCKERBERG: I started running the site

  • and launched it at Harvard in February, 2004.

  • So I guess almost two years ago now.

  • And within a couple of weeks, a few thousand people had signed up,

  • and we started getting some emails from people at other colleges asking

  • for us to launch it at their schools.

  • >> And I was taking 161 at the time.

  • So I don't know if you guys know the reputation of that course,

  • but it was kind of heavy.

  • It was a really fun course, but it didn't leave me with much time

  • to do anything else with Facebook.

  • So my roommate Dustin, who I guess had just finished CS50, was like, hey.

  • I want to help out.

  • I want to do the expansion and help you figure out how to do the stuff.

  • >> So I was like, that's pretty cool, dude.

  • But you don't really know any PHP or anything like that.

  • So that weekend he went home, bought the book Pearl for Dummies,

  • came back and was like, all right.

  • I'm ready to go.

  • >> I was like, dude, the site's written in PHP not Pearl, but that's cool.

  • >> So he picked up PHP over like a few days because I

  • promise that if you have a good background in C,

  • PHP is a very simple thing to pick up.

  • And he just kind of went to work.

  • >> Before we take a look now at where the course is going,

  • allow me to invite just some of SC50's staff up on to stage.

  • Some of them are shopping their own courses.

  • But if those TFs and CAs and course heads who are here could come on up

  • and join me for a quick hello.

  • >> Allow me to introduce in particular, Hanna, Maria, Daven, and Rob,

  • CS50's course heads here in Cambridge.

  • >> [APPLAUSE]

  • >> DAVID MALAN: Indeed, testament to the support structure that the course has

  • built out over the past many years, CS50 staff this year numbers nearly 100,

  • and that's here in Cambridge alone.

  • Meanwhile, in New Haven, are there some 40 TFs and CAs and staff members there

  • to run the course as well.

  • >> Allow us to introduce first, Rob Bowden.

  • ROB BOWDEN: Hi.

  • I'm Rob.

  • This is my sixth year TFing in the course.

  • So, all the way back in my freshman year, I did not take CS50.

  • Your freshman fall-- you might be familiar

  • that you can only take four courses and there are so many courses today.

  • So I'm like, eh.

  • I took AP CS my senior year of high school it was horrible.

  • So, I'm like, eh.

  • Computer science is not for me.

  • >> So then it was over the course of my freshman

  • fall, that I had a friend in CS50, and I think I attended one lecture with her.

  • It's like, oh, this is kind of better than what I had in high school.

  • >> And over the course of the year, I had my own problem sets

  • in the courses I was actually taking.

  • But I found that whenever I wanted to procrastinate on those,

  • I would go back to CS50 and look at some of that stuff.

  • So, yeah.

  • I'm cool.

  • I procrastination with coding.

  • So then it's at the end of the fall that I realize, hey,

  • computer science is pretty cool.

  • I end up taking CS51.

  • In the next semester, I end up taking CS61.

  • And it all from there, then I end up declaring

  • computer science, which I had absolutely no intention of doing

  • when I came into college.

  • And now I'm here.

  • So the course is what you make of it.

  • I hope you enjoy it.

  • >> [APPLAUSE]

  • DAVID MALAN: Thank you to Rob.

  • >> And now Maria, our head course assistant.

  • >> MARIA: Hey guys.

  • My name is Maria.

  • I'm a sophomore in Cabot House, coming from Bulgaria,

  • and I'm super excited to be part of the staff this year.

  • I took CS50 as a freshman last year, and I never even

  • thought about CS beforehand.

  • So I absolutely love the course, and I hope you all love it as much as I did.

  • And, yeah.

  • Welcome to CS50.

  • DAVID MALAN: Thank you to Maria.

  • [APPLAUSE]

  • Now Hanna, our head teaching fellow.

  • HANNA: Hi, I'm Hanna.

  • I'm a senior in Cabot studying computer science.

  • I took CS50 as a freshman and had been TFing-- this'll be my third year.

  • So I will be happily involved in CS50 for all four years,

  • and I'm looking forward to working with you all.

  • DAVID MALAN: Thank you to Hanna.

  • [APPLAUSE]

  • And lastly, Daven, our precepter.

  • DAVEN: Hey guys.

  • I'm a precept over in computer science here.

  • This'll be my fourth year teaching.

  • I also help manage the course.

  • So I'm sure you'll see me around, especially at office hours.

  • I'm always at office hours.

  • So if you see me walking around, definitely come say hi.

  • I love to meet everybody.

  • Otherwise, have fun, and I'll see you around.

  • >> DAVID MALAN: Thank you to Daven as well.

  • So you'll meet all of these folks before long.

  • But without further ado, if you guys would

  • like to resume your seats from earlier.

  • Allow me to introduce from afar now some of our friends from New Haven,

  • in particular the course's heads who'll be overseeing CS50 there-- Professor

  • Brian Scassellati, Jason, and Andi, who just-- so that we didn't tempt fate

  • with any FaceTime or the like-- have just sent us minutes

  • ago the following video in which they say hello from lecture hall

  • at Yale, in which lecture is being streamed right now.

  • >> So our friends from Yale.

  • BRIAN SCASSELLATI: Hi, David.

  • Hi, everyone at Harvard.

  • We are so excited to be bringing CS50 to Yale this semester.

  • My name is Brian Scassellati, but everyone just calls me Scas.

  • And I'm here today to introduce to you the CS50 staff.

  • >> [CHEERING]

  • >> And more importantly, I'm here to introduce as well

  • all of the students at Yale who as of this morning

  • have made this the most popular course at Yale the CS50 students.

  • >> [CHEERING]

  • >> So we're very excited to be seeing you here

  • on Friday and on Saturday for Puzzle Day and have a great lecture.

  • Bye.

  • >> [APPLAUSE]

  • >> DAVID MALAN: On the screen here is the names of the some of 140 staff

  • members who await you over the course of the semester-- some of them

  • here in Cambridge, some of them here in New Haven.

  • And indeed you'll have an opportunity this Saturday,

  • as Scas notes, to attend CS50 Puzzle Day.

  • You might have seen little puzzle pieces slipped under your doorways recently.

  • We have a few extras here later on when you exist.

  • If you assemble all four puzzle pieces and merge forces with rooms

  • nearby yours in your house or dorm, they'll

  • assemble into a QR code-- or a two dimensional bar code, that

  • once assembled and scanned with your phone will lead you

  • to some fabulous prize or-- I suppose you could just photograph this now

  • as well.

  • >> But find those puzzle pieces nonetheless in order to win that fabulous prize.

  • And indeed one of the traditions in SC50-- ah, too slow.

  • One of the traditions in CS50 is to serve cake after the first lecture.

  • >> And so indeed, in a few minutes from now,

  • there will be cake served outside both here and New Haven as well.

  • >> But first-- we decorated them ourselves.

  • But first-- and hopefully there'll be enough.

  • >> But first, a quick look.

  • So lectures is indeed will be produced mostly here in Cambridge.

  • But each month, we'll hop down to Yale with CS50's production team and stream

  • the course in the reverse direction as well so

  • as to bring these two campuses truly for the first time in history

  • as close together as possible as one in the same course.

  • >> In terms of the support structure that's been stood up here in Cambridge as well

  • as in New Haven, are sections.

  • Indeed, as some of you may know, we have different tracks

  • within the course for those less comfortable, more comfortable,

  • and somewhere in between so that irrespective of your prior background,

  • can you ultimately succeed in the class.

  • >> Office hours meanwhile, are an opportunity on Mondays and Tuesdays

  • and Thursday evenings to work both here and in New Haven on our course's

  • problem sets with dozens of the course's staff near you.

  • >> Problem sets meanwhile, are supported by things we call

  • walkthroughs, which are video based tutorials that truly answering FAQ

  • of where to begin a week's challenge.

  • And postmortems walk you through possible solutions

  • so that the end of the problem set too, you

  • know exactly what you could have done differently or altogether otherwise.

  • >> The problem sets themselves come in two editions, a standard edition

  • that we expect and invite most of the class-- some 90% plus to do--

  • and a so-called hacker edition on which every page is emblazoned

  • hacker edition, hacker edition, hacker edition,

  • so that you have that karma if you will, for diving

  • into more advanced versions of the course's problem sets

  • that cover ostensibly the same material but with a more sophisticated approach

  • and with additional background sometimes introduced.

  • >> Meanwhile, are there nine late days that you can apply to the course's problem

  • sets as well as the lowest score, which we drop at the terms end.

  • >> But what awaits?

  • Well, a taste of the problem sets at hand on Friday

  • and next week where we dabble for just a few days in something

  • called Scratch, a graphical programming language developed by our friends

  • at MIT's Media Lab that allows you to program either for the first time

  • or in a new environment altogether using a drag and drop type environment.

  • Whereby puzzle pieces only interlock together

  • if it makes logical sense to do so.

  • >> Meanwhile in problem set two last year for instance,

  • did we introduce the class to the world of cryptography,

  • the art of encrypting or scrambling information.

  • Indeed, this text here if decrypted, will actually

  • lead you to some fun destination.

  • And in the problem set, what we had students

  • do is implement exactly those kinds of things-- an algorithm,

  • or set of instructions for scrambling and scrambling information.

  • >> And in the hacker edition of that same problem set,

  • did we challenge students to take a encrypted file from a typical computer

  • system with lots of usernames and encrypted passwords

  • and to crack those passwords-- actually figure out

  • what they were without knowing anything a priori about those actual passwords.

  • Meanwhile, do we transition in the problem

  • sets to then looking at the world of graphics.

  • And in fact, you might imagine now that this could perhaps

  • be the simplest way to represent a black and white image.

  • >> A white pixel, or square, as at top right there,

  • might be represented with a 1 and a black square

  • might be represented with a 0.

  • And just by using more bits like we proposed earlier with 72 and 73 and 33,

  • could we represent color pixels as well.

  • And what we do during this problem set is

  • generally take a stroll around campus with a digital camera,

  • take photographs of people, places, and things.

  • Then somehow every semester, we seem to accidentally

  • deleted or corrupt the memory card on which all of those photos are,

  • and so you are challenged to then write software

  • with which to recover those JPEGs from a copy of our camera's card.

  • >> Meanwhile, do we hand you later in the term a dictionary of English words

  • that have 143,000 words, and you need to come up

  • with a smart way of loading them into memory,

  • or RAM so to speak, to answer queries of the form: is this a word,

  • is this a word, implementing the fastest spell checker that you can,

  • even pinning yourself potentially against classmates

  • to see which of you uses the least amount of time

  • when running your code and even the least amount of memory.

  • >> Later in term do you actually implement your own web server.

  • So not just a website in a language called HTML and more,

  • but a web server that actually listens to requests on the internet

  • and responds to them.

  • And indeed, this is how we bridge our world of C with which you'll

  • become familiar next week and PHP and HTML and JavaScript

  • and CSS and the like.

  • >> Because one of the first web based project we do later in the term

  • is historically CS50 Finance.

  • Etrade.com style a website that allows you to buy and sell stocks virtually

  • while also writing code to talk to Yahoo Finance getting semi real time stock

  • quotes in order to update your own portfolio.

  • >> But lastly of course, is the final project--

  • an opportunity to do most anything of interest to you to solve a problem here

  • or beyond of interest to you that's somehow inspired

  • by the lessons learned in the class.

  • >> And the class, as you may know, culminates in so-called CS50 Hackathon

  • and CS50 Fair and any number of other cultural events

  • throughout the semester that allow you to engage

  • with each other and the course's staff.

  • >> For instance, at Fire and Ice in Sitar this year, well, on Friday afternoons,

  • we invite some 50 students to lunch, whoever

  • would like to join us, myself, and the staff,

  • and our friends from industry and alums to chat about life in the real world

  • and beyond while enjoying a good lunch.

  • At the Hackathon will you see such images

  • as these, including plenty of candy-- and as of 2014 for the first time--

  • vegetables.

  • >> [APPLAUSE]

  • >> But by 5:00 AM, does the scene usually look a little something like this.

  • And then just a week or so later, is the CS50 Fair

  • to which some 2000 plus students and staff and faculty

  • members from across campus and across campuses this year

  • come to see and delight in the accomplishments of CS50 students, which

  • is now you.

  • >> And indeed, while this year we'll be inviting and busing anyone

  • at at Yale who would like to come up to Cambridge this Saturday for CS50 Puzzle

  • Day, and we'll do the exact same thing in December for the CS50 Hackathon

  • so that Harvard and Yale students alike partake in both of these events.

  • >> We will also hold CS50 fairs in Cambridge and in New Haven this year

  • so that students on both campuses and staff and faculty

  • can see each respective campus's accomplishment.

  • And those accomplishments will induce such memory

  • as this and this and ultimately this, in which all of you

  • exit the class wearing a little something in which you were hopefully

  • happy or proud to say that I took CS50.

  • >> But before that and before we serve cake,

  • we've put together-- thanks to CS50's production team and a certain self

  • stick, the one occasion that we use such things for-- when we sent it

  • not only here to Cambridge but also to New Haven

  • to gather a few hellos from the course's staff and all of the folks

  • you will meet both here and in New Haven over the following months.

  • >> Allow me to introduce a few more of CS50's staff.

  • MARK ZUCKERBERG: Did that make it go?

  • Oh, it's going.

  • It's going.

  • Ooh.

  • Yarr!

  • >> [MUSIC PLAYING ANDY GRAMMER, "HONEY, I'M GOOD"]

  • >> MARY: This is Caitlin.

  • That's Jay, and I'm Mary.

  • SATO: Hi, guys.

  • I'm Sato.

  • MICHAEL G.: Hi.

  • My name is Michael, G.

  • DOUG LLOYD: I'm not.

  • No.

  • I'm Doug Lloyd.

  • I can't believe that I'm holding a selfie stick right now.

  • SPEAKER 4: Hi.

  • SPEAKER 5: Hi.

  • SPEAKER 6: Hello.

  • SPEAKER 7: Hi.

  • SPEAKER 8: Hey.

  • We're hanging out at Yale.

  • We're really excited for this semester because it's

  • the first time it's coming to Yale.

  • It's going to be awesome!

  • >> [MUSIC PLAYING]

  • >> JACOB SCHERBA: My name is Jacob Scherba.

  • I'm excited to teach CS50 because I think

  • it bring computer science to people in and approachable way.

  • SPEAKER 9: I'm really excited to teach CS50

  • because I took the class last year, and it's one of the best classes.

  • SPEAKER 10: Yeah.

  • My advice is you should take CS50.

  • JACOB SCHERBA: I chose CS because I think it's a fun and creative way

  • to solve problems in an analytical way.

  • SPEAKER 11: Back when I was a little freshman and afraid of computer science

  • and afraid of doing engineering and stuff,

  • it was the first hard class I took, and it was also my favorite class ever.

  • DOUG LLOYD: This is my ninth year teaching CS50.

  • That makes me sound so old!

  • There's always something new.

  • There's always something exciting.

  • There's always new challenges faced by new students, and it's fun to help them

  • and to experience those challenges with them

  • and help them solve their problems.

  • >> SPEAKER 12: When I first learned how to do CS,

  • it was like learning a super power.

  • And to see that in other students and to help them through that process

  • is one of the most rewarding things I've ever.

  • >> SPEAKER 7: I chose CS because in the beginning, I was a math concentrator

  • and I took CS50 and fell in love with it.

  • I also felt that with CS, I could build things.

  • And that, I thought, was a really cool aspect.

  • >> SPEAKER 13: Some advice for new students is go to office hours

  • and hang out with the awesome TFs.

  • SPEAKER 14: Start your P-SETs early, go to office hours,

  • become frends with your TF.

  • SPEAKER 15: Yeah.

  • Everything she said.

  • SPEAKER 16: Don't be afraid to ask for help.

  • SPEAKER 17: Yeah.

  • SPEAKER 18: Start your P-SETs early.

  • SPEAKER 19: It's a big social experience.

  • Make a lot of friends this way.

  • SPEAKER 14: Go to section It's fun.

  • SPEAKER 11: I mean, go for it.

  • It's really hard.

  • You'll get out of it what you put into it,

  • but it's a really fun class especially if you're

  • willing to put the time into it, but it helps if you put time into it.

  • You'll get a lot more out of it later on.

  • MIKE: I'm Mike.

  • CAMILLE: I'm Camille.

  • HANYA: I'm Hanya.

  • MATT: I'm Matt.

  • PETER: I am Peter.

  • PHILLIP: I'm Phillip.

  • PATRICK: I'm Patrick.

  • ROB BOWDEN: I'm Rob Bowden.

  • BRIAN SCASSELLATI: My name is Scas, and this--

  • ALL: --is CS50.

  • SPEAKER 20: At Yale.

  • SPEAKER 21: At Yale.

  • [LAUGHING]

  • DAVID MALAN: That's it for CS50.

  • We will see you from Yale on Friday, Puzzle Day on Saturday.

  • Cake is now served.

  • This is CS50.

  • >> [MUSIC PLAYING]

>> [MUSIC PLAYING]

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