This two-part course builds upon the programming skills that you learned in our Introduction to Interactive Programming in Python course. We will augment those skills with both important programming practices and critical mathematical problem solving skills. These skills underlie larger scale computational problem solving and programming. The main focus of the class will be programming weekly mini-projects in Python that build upon the mathematical and programming principles that are taught in the class. To keep the class fun and engaging, many of the projects will involve working with strategy-based games. In part 1 of this course, the programming aspect of the class will focus on coding standards and testing. The mathematical portion of the class will focus on probability, combinatorics, and counting with an eye towards practical applications of these concepts in Computer Science. Recommended Background - Students should be comfortable writing small (100+ line) programs in Python using constructs such as lists, dictionaries and classes and also have a high-school math background that includes algebra and pre-calculus.
Principles of Computing
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來自 Rice University 的課程
Principles of Computing (Part 1)
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從本節課中
Required Python knowledge, coding standards, and machine grading
This week, we will introduce you to the structure and standards of the Principles of Computing courses.
與講師見面
Scott RixnerProfessor
Computer Science
Joe WarrenProfessor
Computer Science
Luay NakhlehAssociate Professor
Computer Science; Biochemistry and Cell Biology
[MUSIC].
Hi.
I'm Scott Ricksner and welcome to the principles of computing.
I'm here with my less serious colleague, Joe
Warren, and my more serious colleague Luay Nucklay.
And we are the instructors for this class.
The three of us teach the introductory curriculum here at
Rice University, and we are trying to take this curriculum online.
And this class here is the analog to a class
that I teach in the first semester of the Freshman year.
Now, first I would like to introduce ourselves a
bit, okay the Principles of Computing is a class that.
We have constructed to follow on to
our first offering, introduction to interactive programming in
Python, to start to dive a little bit
deeper into the principles that underlie computer science.
And with that, I'd like to let Joe Warren introduce himself now.
>> Thanks.
I'm Joe Warren.
I'm a professor here at Rice.
I along with Scott put together
an introduction to interactive programming in Python.
That class is based on a class here at
Rice, in which we teach students how to program.
With motivational aspect of building games.
A couple of years ago, we sat down and
kind of rebuilt this classroom from scratch, using Python.
And so what we have right now is a class that we teach on campus to Rice students.
It's about the, half a semester's worth of class.
And we have an online class that a lot of you have
taken, which kind of gives you really the same kind of material
in there.
>> And now let's hear from Luay.
>> Hi, I'm Luay Nakhleh.
I'm a faculty member here in the computer science department.
I teach an algorithmic thinking course which will be the third course
in the sequence as we all three of us will be teaching.
My main role will be basically to fix all the mistakes that these two guys make.
>> [LAUGH] We don't make mistakes.
Come on now.
>> And in, in algorithmic thinking, basically we
teach the students how to go all the
way from taking the problem in any domain
like biology or physics or chemistry or social sciences.
Go through algorithm design, reasoning about the algorithm and
then implementing it so that we solve the original problem.
I view algorithms as, as a central
component in computer science, and that will be
the focus in the course, which we have been teaching here at Rice for four years.
And we will adapt it for this online version of the course as well.
>> Thank you.
The principles of computing really sits between the
two courses that Joe and Luay talked about.
The idea here is to bridge the
gap between the motivational aspects of building games.
In which we taught you some of the
principles of how to construct larger programs in Python.
To really doing the algorithmic thinking that is going to occur in Luay's class.
So the idea here is to be able to give
you a more principled way of constructing complex programs so
that as you're doing the algorithmic thinking in the follow
on class the programming will not get in the way.
That you will have a foundation upon which you can build these complex programs.
I think now we'd like to talk a little
bit about our personal sort of experiences with computer science.
And so again I'm going to, I'm going to turn to Joe and
let him, you know, tell you why he's a computer scientist.
>> Why am I a computer scientist?
So I guess I went to high school in the late 70s.
And I came here to Rice in 79, I was a student here from 79 to 83.
And so at the time I had an option of being a math
student or being a, this new kind of new fangled computer science student.
And I decided that, you know, I do math but get paid
like a computer science person, because the pay was actually quite well there.
But, I kind of came to computer science because I
really enjoyed this interplay between
mathematical reasoning and building things.
I could think mathematically but then have
the joy of actually constructing these mathematical creations.
And building those and seeing the tangible result of what I built.
>> And I'm guessing Luay has a different story about why he's a computer scientist.
>> So just to to start, I was born in the 70s.
You can tell the difference in age between me and these two guys sitting here.
I might look older than them, but that's because I am wiser.
>> [LAUGH]
>> So about my experience with computer science, it started
in ninth grade when I took a computer science course.
And for the entire year we did not touch a computer.
We did not see a computer at all.
It was actually about designing algorithms for doing something
simple, like for example, finding maximum element in a list.
And that immediately attracted me because I
could see how we can develop methods that
can solve problems from the simplest one, again
like finding the maximum element in a list.
To much more complicated problems.
So that's how it started with me with computer science.
When I finished high school, I applied to college for studying
either Physics or Computer Science and I was accepted to both.
I finished high school in 91, it was around the time
when Stephen Hawking's book, A Brief History of Time came out.
And everyone was talking about black holes and all these kinds of things.
I was intrigued by that.
But again as similar to Joe's story is that I thought about these two fields.
That they are both mathematical in principle.
But I thought that there would be more jobs for computer science.
And that actually tipped the, the balance for me towards computer science more.
>> Well I certainly have more gray hair than Luay
but I'm not sure that means I'm older than he is.
[LAUGH] Alright.
So my story is a little bit different I think.
When I was growing up you know, I was always fascinated by computers.
Computers were not so common, right?
I am old enough to not have had a computer in my house.
As I was growing up until I was much older and I was fascinated by how they worked.
And I continue to be fascinated by how
computers work so a lot of, of my excitement
about computer science is the interplay between hardware
and software and how the underlying systems actually work.
So I do enjoy math but I'm not
a mathematician the way these guys are mathematicians.
Okay?
Alright.
So now I'd like to talk a little bit
about you know, what our belief of computer science is.
And I'd like to let Joe start the discussion here, and
give us a straw man for what he believes computer science is.
>> So here, I'm going to pretend that Luay is a high school senior
coming to interview at Rice, because I get this question all the time.
Which is, they come and say.
I want to, I want to do computer science.
I've done all this programming in high school,
and I'm ready to be a computer scientist.
So, the thing that I would actually say about what is computer
science is to consider what does it mean to be a writer?
Think about your, in high school you've
taken some classes on writing grammatically correct English.
And you ask yourself, am I ready to be a writer now?
And the answer is, no you're not.
So, I think programming is very
similar to basically writing grammatically correct English.
You understand the kind of syntactic constructs of your programming
language, you kind of put it together to solve simple assignments.
But the reality is you're not ready to write a good novel yet.
So computer science is this idea of kind of studying computing,
and trying to understand how to basically build cool stuff with computers.
I think I've heard it described as how to tell a story.
And so for me, computer science is this
idea of understanding the great themes of computing.
What have people studied before, what do they know?
What can we leverage?
Adding new themes to those, going through and learning how to
use the skills that you've learned as a programmer, to solve problems.
To go out and build things that can change the world make the world
a better place, make you some money, but it's to do things with computers.
Is that okay Luay?
>> Sounds fine, I would actually, for me, my
view of computer science is influenced by how I
do research or what the research I work in
which is in applications of computer science to biology.
So there we look at the problem that
comes from biology without us being biologists ourselves.
And we think about how do we take
a problem that's described in English or any natural
language, whatever the language of the biologist is, and
how we thinking about to solve it using computers?
Of course the problem is not described
in, in a language that's amenable to algorithms.
So we have to go through an entire process.
Of, of, formalizing the problem, doing formal reasoning about
it, thinking about the algorithm and then implementing it.
So for me, I view computer science as
this discipline of reasoning about problems, designing solutions
for them, which includes the algorithm design as
well as the implementation to solve real world problems.
>> How important is it to be a good programmer?
>> Obviously it's not that important because I'm not a good programmer.
[LAUGH] I know that question was going to come at some point.
>> I want you to know that Luay is the best pseudo-programmer I have ever seen.
[LAUGH].
>> That was a serious question though.
How important is it to be a good
computer programmer to be a good computer scientist?
>> I think it's very important to
have outstanding programmers in computer science but, I
don't think it is very easy to
be outstanding at every aspect of computer science.
Again as I mentioned, for me, I look at even
in the homework assignments that we give in algorithmic thinking.
We do, the homework assignments spans, spans the problem all the
way from the English description to the implementation and running the analysis.
And, in that part of that process is writing the program
and one has to be, very capable of writing the problem,
knowing the syntax of the language, knowing, you know, all sorts
of tricks and so on to implement the, to implement the program.
But there are many other skills that, that,
the computer scientists need to be aware of.
So many people, for example, are very good at designing
algorithms, and once they design the algorithm they figure it out,
that's where they stop and say someone else, let someone else
implement it, and I see a room for these things because.
It's not easy for everyone to claim that, I am good at
doing algorithms, I am good at, at coming up with the math.
And I'm the best also at doing the program,
because I am sure I can write the program
that implements my algorithm, but I am also sure
that there's someone who can optimize that code even better.
And make it even more usable.
>> Come on, you're being ni, you're being to nice here.
I'll, I'll shake it up, I'll get Scott inflamed here.
>> [LAUGH].
>> So, I've actually read this, and I subscribe to this little point
of view, that in some sense, programming
is actually probably the least important skill.
I kind of view that being the janitor of computer science.
And let me explain why the process of taking a well defined
description and turning it into code is actually a fairly straight forward thing.
The hard intellectual challenge is hearing a problem, thinking how to
formulate it, thinking about algorithms, data structures, how to solve it.
It's taking that high level problem and turning into a
specification and a program we can then turn into code.
And I mean you'll see this, for example outsourcing.
Outsource is going to take a lot of the
low end programming jobs and essentially kind of.
Kind of put them out to the world where they're really done by a low cost.
The people that are actually making the six
figure salaries in computer science are the problem
solvers, the one that a corporation can come
to and say hey, I have this computational problem
and I need you to take it and figure out how to solve it and build
me a description that I can then give
to some programmers and turn it into some code.
Now don't get me wrong, I don't think that programming is irrelevant.
I think it is very important to understand how
you actually implement these because it will influence your design.
But I think the role of programming is not as high as Scott might think.
>> So how important do you think it is to be disciplined in your approach
to doing this versus being a maverick and just going out there and doing it?
>> [LAUGH] So Scott was, so Scott and
I actually have many, many comments about this.
And I'll say in building IPP, I have learned the importance of discipline.
>> [LAUGH]
>> But I'll leave you a little background for what I do.
So for 25 years, I did basically computer graphics.
And so my kind of job was to solve problems in computer graphics.
And I had students that essentially translated my ideas into code.
And so a lot of code that they had built was kind of one-off code that
was used to demonstrate a concept or to
solve a problem and they weren't working in teams.
The thing that I've learned working with you
is that if you need to work with others,
and that's for most of the problems your
out there, you're going to have to work in teams.
Discipline is very important because the wild
hairy code that you write for one-off for
maybe a research paper is not the kind of code you want to have in say.
Maybe some kind of critical operating system
for a flight control system on an airplane.
So I definitely think that discipline is an important thing and
I, and I've kind of come around a little bit in principles
of computing where I think that it's important to train the students
to be more systematic about the kind of code that they write.
So, I'm coming around some.
>> [LAUGH] So actually, I have a
different perspective on computer science than these guys.
While they like to focus on how I use
a computer to solve sort of application level problems.
I actually enjoy the system.
I actually really enjoyed building Code Sculptor, for instance.
I like thinking about how the underlying
tools and the underlying computer actually works.
So I can provide facilities for other people to build
these kind of solutions that these guys are talking about.
And I think that, this shows that there's a diversity of things that you can do
in computer science and I think that's what
makes computer science great, at least from my perspective.
This is also why I think the three of us, perf
form a great teaching team for this course and follow-along courses.
That we each bring these
different perspectives about programming, about systems,
about applications, that hopefully will shine through in these courses, okay?
And we want you to see that, yes, programming is important.
These principles are important, algorithms are important.
And the way that you think about problems
and use computers to solve them are also important.
We're definitely excited about teaching these courses.
And I hope that you're going to be excited about taking them.
