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PROFESSOR: Good morning.

Try it again.

Good morning.

STUDENTS: Good morning.

PROFESSOR: Thank you.

This is 6.00, also known as Introduction to Computer

Science and Programming.

My name is Eric Grimson, I have together Professor John Guttag

over here, we're going to be lecturing the course this term.

I want to give you a heads up; you're getting some serious

firepower this term.

John was department head for ten years, felt like a century,

and in course six, I'm the current department

head in course six.

John's been lecturing for thirty years, roughly.

All right, I'm the young guy, I've only been lecturing

for twenty-five years.

You can tell, I have less grey hair than he does.

What I'm trying to say to you is, we take this

course really seriously.

We hope you do as well.

But we think it's really important for the department

to help everybody learn about computation, and that's

what this course is about.

What I want to do today is three things: I'm going to

start-- actually, I shouldn't say start, I'm going to do a

little bit of administrivia, the kinds of things you need

to know about how we're going to run the course.

I want to talk about the goal of the course, what it is

you'll be able to do at the end of this course when you get

through it, and then I want to begin talking about the

concepts and tools of computational thinking, which

is what we're primarily going to focus on here.

We're going to try and help you learn how to think like a

computer scientist, and we're going to begin talking about

that towards the end of this lecture and of course

throughout the rest of the lectures that carry on.

Right, let's start with the goals.

I'm going to give you goals in two levels.

The strategic goals are the following: we want to help

prepare freshmen and sophomores who are interested in majoring

in course six to get an easy entry into the department,

especially for those students who don't have a lot of prior

programming experience.

If you're in that category, don't panic, you're

going to get it.

We're going to help you ramp in and you'll certainly be able to

start the course six curriculum and do just fine and

still finish on target.

We don't expect everybody to be a course six major, contrary to

popular opinion, so for those are you not in that category,

the second thing we want to do is we want to help students who

don't plan to major in course six to feel justifiably

confident in their ability to write and read small

pieces of code.

For all students, what we want to do is we want to give you

an understanding of the role computation can and cannot play

in tackling technical problems.

So that you will come away with a sense of what you can do,

what you can't do, and what kinds of things you should use

to tackle complex problems.

And finally, we want to position all students so that

you can easily, if you like, compete for things like your

office and summer jobs.

Because you'll have an appropriate level of confidence

and competence in your ability to do computational

problem solving.

Those are the strategic goals.

Now, this course is primarily aimed at students who

have little or no prior programming experience.

As a consequence, we believe that no student here is

under-qualified for this course: you're all MIT

students, you're all qualified to be here.

But we also hope that there aren't any students here who

are over-qualified for this course.

And what do I mean by that?

If you've done a lot prior programming, this is probably

not the best course for you, and if you're in that category,

I would please encourage you to talk to John or I after class

about what your goals are, what kind of experience you have,

and how we might find you a course that better

meets your goals.

Second reason we don't want over-qualified students in the

class, it sounds a little nasty, but the second reason

is, an over-qualified student, somebody who's, I don't know,

programmed for Google for the last five years, is going to

have an easy time in this course, but we don't want

such a student accidentally intimidating the rest of you.

We don't want you to feel inadequate when you're

simply inexperienced.

And so, it really is a course aimed at students with little

or no prior programming experience.

And again, if you're not in that category, talk to John

or I after class, and we'll help you figure out where

you might want to go.

OK.

Those are the top-level goals of the course.

Let's talk sort of at a more tactical level, about what do

we want you to know in this course.

What we want you to be able to do by the time you

leave this course?

So here are the skills that we would like you to acquire.

Right, the first skill we want you to acquire, is we want you

to be able to use the basic tools of computational thinking

to write small scale programs.

I'm going to keep coming back to that idea, but I'm going to

call it computational thinking.

And that's so you can write small pieces of code.

And small is not derogatory here, by the way, it just says

the size of things you're going to be able to do.

Second skill we want you to have at the end of this course

is the ability to use a vocabulary of computational

tools in order to be able to understand programs

written by others.

So you're going to be able to write, you're going

to be able to read.

This latter skill, by the way, is incredibly valuable.

Because you won't want to do everything from scratch

yourself, you want to be able to look at what is being

created by somebody else and understand what is inside of

there, whether it works correctly and how you

can build on it.

This is one of the few places where plagiarism

is an OK thing.

It's not bad to, if you like, learn from the skills of others

in order to create something you want to write.

Although we'll come back to plagiarism as a

bad thing later on.

Third thing we want you to do, is to understand the

fundamental both capabilities and limitations of

computations, and the costs associated with them.

And that latter statement sounds funny, you don't think

of computations having limits, but they do.

There're some things that cannot be computed.

We want you to understand where those limits are.

So you're going to be able to understand

abilities and limits.

And then, finally, the last tactical skill that you're

going to get out of this course is you're going to have the

ability to map scientific problems into a

computational frame.

So you're going to be able to take a description of

a problem and map it into something computational.

Now if you think about it, boy, it sounds like grammar school.

We're going to teach you to read, we're going to teach you

to write, we're going to teach you to understand what you can

and cannot do, and most importantly, we're going to try

and give you the start of an ability to take a description

of a problem from some other domain, and figure out how to

map it into that domain of computation so you can do

the reading and writing that you want to do.

OK, in a few minutes we're going to start talking then

about what is computation, how are we going to start building

those tools, but that's what you should take away, that's

what you're going to gain out of this course by the

time you're done.

Now, let me take a sidebar for about five minutes to talk

about course administration, the administrivia, things that

we're going to do in the course, just so you know

what the rules are.

Right, so, class is two hours of lecture a week.

You obviously know where and you know when,

because you're here.

Tuesdays and Thursdays at 11:00.

One hour of recitation a week, on Fridays, and we'll come back

in a second to how you're going to get set up for that.

And nine hours a week of outside-the-class work.

Those nine hours are going to be primarily working on problem

sets, and all the problems sets are going to involve

programming in Python, which is the language we're going

to be using this term.

Now, one of the things you're going to see is the first

problem sets are pretty easy.

Actually, that's probably wrong, John, right?

They're very easy.

And we're going to ramp up.

By the time you get to the end of the term, you're going to be

dealing with some fairly complex things, so one of the

things you're going to see is, we're going to make heavy use

of libraries, or code written by others.

It'll allow you to tackle interesting problems I'll have

you to write from scratch, but it does mean that this skill

here is going to be really valuable.

You need to be able to read that code and understand it,

as well as write your own.

OK.

Two quizzes.

During the term, the dates have already been scheduled.

John, I forgot to look them up, I think it's October 2nd and

November 4th, it'll be on the course website.

My point is, go check the course website, which by

the way is right there.

If you have, if you know you have a conflict with one of

those quiz dates now, please see John or I right away.

We'll arrange something ahead of time.

But if you-- The reason I'm saying that is, you know, you

know that you're getting married that day for example,

we will excuse you from the quiz to get married.

We'll expect you come right back to do the quiz by the way,

but the-- Boy, tough crowd.

All right.

If you have a conflict, please let us know.

Second thing is, if you have an MIT documented special need for

taking quizzes, please see John or I well in advance.

At least two weeks before the quiz.

Again, we'll arrange for this, but you need to give us

enough warning so that we can deal with that.

OK, the quizzes are open book.

This course is not about memory.

It's not how well you can memorize facts: in fact, I

think both John and I are a little sensitive to memory

tests, given our age, right John?

This is not about how you memorize things, it's

about how you think.

So they're open note, open book.

It's really going to test your ability to think.

The grades for the course will be assigned roughly, and I use

the word roughly because we reserve the right to move these

numbers around a little bit, but basically in the following

percentages: 55% of your grade comes from the problem sets,

the other 45% come from the quizzes.

And I should've said there's two quizzes and a final exam.

I forgot, that final exam during final period.

So the quiz percentages are 10%, 15%, and 20%.