English subtitles for clip: File:Course Overview (6.002x).webm

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SPEAKER 1: 6.002x, as I
mentioned earlier, is the

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first course in a typical
EE or EECS

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curriculum as it is at MIT.

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So before we start, I'd like to
spend some time discussing

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where exactly, such a circuits
and electronics course and the

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content that it teaches
fits within the

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grand scheme of things.

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We will start by trying
to understand, what is

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engineering?

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Well, engineering is the
purposeful use of science,

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where science, itself, is
the study of what is.

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In other words, it's the
study of nature.

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With engineering, we
are now focused on

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what we make of nature.

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It's what we build.

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It's how we can use science
to help humanity.

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So then, where does
6.002x fit in?

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6.002x is about the gainful
employment of Maxwell's

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equations, going all the way
from electrons to digital

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gates and op-amps.

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As I mentioned earlier, just
as engineering is the

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purposeful use of science or
nature, 6.002x is about the

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use of Maxwell's equations.

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Now, when you have nature,
that is what is.

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So you can study nature
and that is science.

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You're not allowed to
change anything.

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With engineering, you are
looking to build cool stuff,

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things that can help humanity.

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And in order to build such
stuff, we often abstract

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nature, or we abstract
what is into laws.

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And Maxwell's equations are laws
that govern the behavior

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of one part of nature.

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And 6.002x is about employing
Maxwell's equations to build

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cool systems that can
help humanity.

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Now, let's try to get a better
handle on exactly what we mean

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by looking at how
nature behaves.

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Or at least, nature
as described

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by Maxwell's equations.

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And let's see how that will lead
to building really useful

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systems that can
help humanity.

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So so let's put nature and what
is on the left-hand side.

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And on the right-hand side,
let's put down what are the

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kind of things that we
may want to build

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that will help humanity.

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So computer mice
are an example.

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Cool devices like your iPad or
your RAZR phone are useful

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devices, space shuttle,
stereo systems,

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sonar, even Angry Birds.

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So let's see, so how do we take
nature, what is available

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to us, and how do we build,
as engineers,

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really useful systems?

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So we start with nature.

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That's what we are given.

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So what we could do is look
at how nature behaves by

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performing sets of
experiments.

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So we could perform experiments

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and build some tables.

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So as one example, in the area
that we are concerned about,

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we can measure voltages
and currents.

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So for various voltages, I can
measure currents that arise

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from those voltages.

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So I could have 4 volts and
so on and so forth.

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I can apply voltages to some
material and measure the

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current that flows through
those materials.

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In the same manner, I can
collect tables and tables and

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reams and reams of data to
characterize all kinds of

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parts of nature, and have reams
and reams of this data.

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So I could take reams of this
data, and somehow try to build

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those systems based on all those
properties of nature.

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Now, that is clearly a
herculean, if anything,

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ludicrous task.

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So what do we do?

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This is just too hard.

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And nobody sits down with reams
of data looking at how

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nature behaves and
build systems.

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What do we do instead?

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What we do, as engineers, is we
start by building laws or

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abstractions that succinctly
describe how nature behaves.

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So, for example, I can take
these measurements that I made

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of voltages and currents,
and I can say, a-ha.

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I can describe certain
materials that behave

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according to certain laws, and
write an equation, such as v

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is equal to ri, which is Ohm's
Law, that governs certain

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types of devices.

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Other phenomena are described
by Maxwell's equations.

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And these equations now, whether
it's Maxwell's, Ohm's,

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or classes of other equations,
think of these as succinct

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expressions or learning from the
reams and reams and rooms

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and rooms of data.

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So here, these equations can be
thought of as abstractions

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for those tables of data.

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And just imagine a simple law
like Ohm's Law, v is equal to

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ri, which you've learned about
in your high school advanced

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physics courses.

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Now, in one little, simple
equation v equals ri, can

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describe reams and reams of data
that govern the behavior

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of a certain class of devices.

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So we have simplified our
lives quite a bit.

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But still, trying to use
Maxwell's equations to develop

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Angry Birds, or to develop
computers and so on, is just a

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mind-numbing task.

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Just can't be done.

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So what do we do instead?

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So remember, we have engineers,
and our goal is to

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build these systems at the end
that will help humanity.

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So what we will do is we will
make some assumptions that you

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will see in the rest
of this lecture.

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And by making certain classes of
assumptions, we will build

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what is called the lumped
circuit abstraction.

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Now, the lumped circuit
abstraction, we have a set of

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lumped elements, or discrete
elements, such as resistors,

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capacitors, voltage sources,
inductors, transistors like

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the MOSFET switches, and
so on and so forth.

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So now, other than using
equations and equations, we

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build some abstractions and
build some discrete devices

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that we shall use in
building systems.

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Now, we could take these simple
devices and go ahead

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and build computers.

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But nobody does it that way.

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When you build a computer,
such as a modern

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microprocessor, such a
microprocessor might have 10

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billion elements in it.

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There's no way we can sit around
dealing with resistors

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and MOSFETs in quantities of 10
billion, and individually

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build systems using that.

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So what we do is, again, apply
the process of abstraction.

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We abstract out the behavior of

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collections of these elements.

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And the next abstractions we
will make in this course is

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the simple amplified
abstraction.

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We learn a lot more about
this as we go on.

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This amplifier may have dozens,
if not hundreds of

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these lumped elements
inside them.

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But then we will go and continue
to work with those

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amplifiers, which are abstract
conglomerates of a lot of

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these elements.

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So at this point, life can take
a couple of turns once we

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build a simple amplifier
abstraction.

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So one thing we could do from
there is use that to build

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what we call the operational
amplifier abstraction.

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And then, using that, we can
build even more complex

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system, such as filters.

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Filters are able to process data
in various ways and give

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us a set of outputs that might
suit our purposes in

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engineering certain classes
of systems.

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Then we build the next level of
systems, analog subsystems,

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such as oscillators, modulators,
RF amplifiers,

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power supplies, and so on.

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And then, those would be used
in systems like the space

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shuttle, or phones, and
things like that.

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So that is one whole set of
directions that we can take.

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Think of that as the
analog direction.

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But we can take a second
direction, that is along the

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lines of the digital
abstraction.

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So in this world, we will
make a different set of

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assumptions.

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And you will see that what we
will do is rather than look at

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a continuous set of values,
analog values, we will simply

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look at dividing up all values
into two distinct

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quantities, 1 and 0.

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And by doing so, we will build
up what we call the digital

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abstraction.

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And the first set of components
we will build in

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the digital abstraction are
what are called gates.

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Following that, we will build
even more complex logic,

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combinational logic.

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And then, using combinational
logic, we will apply some time

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[? keeping ?] signals, like
clocks and so on, and build

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what we call clock digital
systems. And abstractly, these

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clock digital systems will be
used to build even more

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complicated and useful
systems, such as

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microprocessors.

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So, for example, there the
abstraction we make is called

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the instruction set abstraction,
or ISA, I-S-A.

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And the instructions of
abstraction will allow us to

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build an even more complicated
class of systems that are

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characterized by their
instruction sets.

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So we can have the MIPS
instruction set, we can have

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the Pentium instruction set,
and so on and so forth.

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Following that, we will build
another level of abstraction.

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Try to build systems using
instructions in the ISA of a

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microprocessor is just way
too complicated still.

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So we build higher
level languages.

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And I'm sure many of you are
familiar with languages such

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as Java, Python, CC++,
and so on.

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Following that, we build
software systems or hardware

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systems, such as operating
systems, and web browsers, and

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things of that sort.

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And then, we combine.

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We have the big combination
where we take the subsystems

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we put together both from the
analog dimension, such as

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power supplies and so on, and
pieces of computer hardware,

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such as oscillators.

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And then from the digital side,
we take both software

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systems and hardware systems
like microprocessors and

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combine them.

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And after we combine them, we
end up with very interesting

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systems like games and so on on
your handheld devices, or

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the space shuttle,
for instance.

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Now, what does 6.002 cover?

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So 6.002 will help you make the
transition from physics

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and take it all the way into
analog and digital subsystems.

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So 6.002x will take you from
physics laws, make the jump to

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engineering, where we will
abstract these physics laws

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and properties into lumped
devices, build the lumped

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circuit abstraction, and then
take the one path on the

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analog direction and build
analog subsystems. And then,

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we will also go down a fair bit
down a digital path and

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take you all the way to
primitive clock digital

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components.

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And the reason we cover this
amount of ground in 6.002x is

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really, really to emphasize the
point that the foundations

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of both the analog and the
digital world are the same.

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The foundations are the same
lumped circuit elements.

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And whose foundations are your
basic laws of physics, such as

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Maxwell's equation.

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And of course, the foundations
of those laws is

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nature as you see it.

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So there you have it.

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This should give you a sense
of the grand scheme

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of things in 6.002x.

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And for that matter, in pretty
much an entire EECS

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curriculum.

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So just to show you why this
large map here pretty much

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covers the typical EECS
curriculum, notice that a

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course at MIT such as 6.061
will cover power supplies.

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A course such as 6.004 or 6.846
will cover computer

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architecture and parallel
computing.

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A course such as 6.002 will
cover introduction to

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programming.

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A course such as 6.033 will
cover basic software systems.

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And there will be many, many,
many other more advanced

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courses that will cover the
further advanced components.

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Nowt o get a sense of many of
these follow-on courses, you

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can get a sneak peak of
the material at OCW,

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OpenCourseWare, or over the next
few semesters, we shall

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make many of these courses
available on MITX as well.