Week 20 - Can You Learn a Programming Language in 4 Days?
Summary
TLDRIn the 20th week of the MIT challenge, the presenter shares their experience learning Scheme, a functional programming language, for an artificial intelligence course. They successfully completed seven problem sets, including an automatic Sudoku solver and a simplified chess AI, in 4.5 days. The speaker emphasizes the importance of understanding the theoretical aspects of computer science over specific programming languages, as it provides a broader perspective for solving complex problems and enriches one's approach to future projects.
Takeaways
- 📚 The speaker is undertaking the MIT Challenge, aiming to learn computer science in 12 months without formal classes.
- 🔄 They are currently facing the challenge of learning Scheme, a new programming language with a functional programming paradigm.
- 🤖 The speaker is using Scheme to complete assignments for an artificial intelligence class, which involves problem sets like an automatic Sudoku solver and a simplified chess AI.
- 🎯 Despite the steep learning curve, the speaker successfully completed the problem sets with minor exceptions, taking slightly longer than anticipated.
- 🛠 Learning a new programming language, even one as different as Scheme, can be achieved in a few days for basic scripting and execution.
- 🧠 The focus of the speaker's challenge is on the theoretical aspects of computer science, which are language and technology independent.
- 🏛 The speaker argues that theoretical computer science provides a higher level of abstraction, allowing for the exploration of more interesting problems.
- 🤖 Theoretical knowledge can be applied to programming projects, offering new perspectives and problem-solving approaches.
- 🏆 The MIT Challenge is not just about learning to code, but also about gaining exposure to advanced concepts like AI and algorithms.
- 📈 The speaker emphasizes the importance of understanding higher-level theories, even if they are not immediately applicable in day-to-day programming.
- 🔄 The speaker will continue to update their progress on the MIT Challenge and provide self-education resources.
Q & A
What is the MIT challenge mentioned in the video about?
-The MIT challenge is about learning the MIT computer science curriculum in 12 months without taking any classes or being enrolled at MIT.
What programming language and paradigm was the speaker learning in the video?
-The speaker was learning Scheme, a functional programming language, which is a new paradigm compared to the object-oriented or procedural styles of Java or C++.
What was the challenge the speaker faced while learning Scheme?
-The challenge was learning a new programming language and paradigm, as well as new techniques for an artificial intelligence class, including problem sets like an automatic Sudoku solver and a simpler version of a chess AI.
How long did it take the speaker to complete the problem sets in the artificial intelligence class?
-It took the speaker 4 and a half days to complete all seven problem sets, which was half a day longer than anticipated.
Why does the speaker believe that learning a new programming language is not that remarkable?
-The speaker believes that learning the basics of a new programming language is not remarkable because it doesn't take much work, especially for someone with a lot of programming experience.
What is the speaker's focus in the computer science curriculum?
-The speaker's focus is on the theoretical aspects of computer science, which are language and technology independent, allowing for the study of more interesting types of problems and solutions.
What is the speaker's opinion on the practicality of higher-level computer science theories?
-The speaker believes that while higher-level theories might not always be directly applicable in everyday programming, they provide a broader perspective and can help uncover solutions to complex problems.
How does the speaker's approach to learning computer science differ from traditional academic programs?
-The speaker's approach focuses on the theoretical aspects of computer science rather than just the practical application, providing exposure to higher-level ideas like artificial intelligence and advanced algorithms.
What are some examples of the higher-level ideas the speaker is exposed to in the curriculum?
-Examples of higher-level ideas include artificial intelligence, advanced algorithms, calculus, differential equations, and advanced number theory.
What is the speaker's goal in updating the viewers about their progress in the MIT challenge?
-The speaker aims to share their progress, insights, and self-education resources with the viewers, providing updates on their journey through the computer science curriculum.
Outlines
📚 Overcoming the Challenge of Learning Scheme for AI
The speaker reflects on their progress in the MIT challenge, specifically focusing on learning the Scheme programming language and functional programming paradigm to complete the artificial intelligence design course. They successfully tackled seven problem sets, including an automatic Sudoku solver and a simplified chess AI, in slightly longer than expected. The speaker emphasizes that learning a new programming language is not as daunting as it seems and encourages focusing on the theoretical aspects of computer science, which are language and technology independent. They highlight the importance of understanding higher-level theories for solving complex problems in the future.
Mindmap
Keywords
💡MIT Challenge
💡Scheme
💡Functional Programming
💡Artificial Intelligence
💡Problem Sets
💡Computer Science Theory
💡Abstraction
💡Expert Practitioner
💡Self-Education
💡Higher-Level Ideas
💡Programming Projects
Highlights
Introduction to week 20 of the MIT challenge, aiming to learn MIT key subjects in 12 months without formal enrollment.
Update on the challenge of learning a new programming language, Scheme, which uses a functional programming paradigm.
Comparison of learning Scheme to object-oriented or procedural programming paradigms like Java or C++.
Successful completion of seven problem sets for the artificial intelligence class, including an automatic Sudoku solver and a simplified chess AI.
The project took 4 and 1/2 days, slightly longer than anticipated.
Discussion on the general idea of learning a new programming language quickly.
Expert programmers often find learning a new programming language's basics within a few days to be unremarkable.
Focus on the theoretical aspects of computer science, which are independent of specific programming languages or technologies.
Critique of academic programs for their theoretical content's practical application.
The importance of higher-level theory in solving complex problems that may not be apparent in everyday programming practice.
The enjoyment of being exposed to higher-level ideas like artificial intelligence and advanced algorithms.
How the MIT challenge provides exposure to advanced computer science concepts.
The benefit of having a broad knowledge base in computer science for approaching future programming projects.
Anticipation of future updates on the MIT challenge and self-education resources.
Transcripts
hey guys welcome back to week 20 of the
MIT challenge which is to learn MIT keys
for your computer science curriculum in
12 months
don't take any classes or even being
enrolled at MIT and I wanted to update
you guys on my last week's video where I
wrote about how I was currently facing
the challenge of learning a new
programming language scheme which also
uses a new programming paradigm so a new
way of thinking about writing programs
which is a functional programming
paradigm as opposed to Java or C++ which
are mostly object-oriented or procedural
style programming paradigms and I was
using this in order to learn and
complete the artificial intelligence
design Mis which were one of the classes
that I'm taking in this computer science
challenge so I was learning a new
language a new programming paradigm and
learning new techniques which was the
content of this artificial intelligence
class in order to solve these problem
sets now I was successful I was able to
complete all seven problem sets with two
minor exceptions and this involves doing
problems such as an automatic Sudoku
solver and a program that is an AI to
solve a simpler version of chess and
these kind of assignments in these kind
of problems I was able to work through
in just a half day longer than I
anticipated so I wanted to spend four
days working on it and it took me 4 and
1/2 days to get all of the work finished
for these classes so I wanted to talk a
little bit about just this general idea
that learning a programming language so
in this case was scheme and it was a
very different language I didn't have a
lot that I could rely on as opposed to
if you're learning Ruby from Python
there's a lot of similarities there's
fewer similarities this is a more alien
kind of language if you're not used to
functional programming languages but the
truth in general is that learning a
programming language learning a new
programming language in just a few days
is not that remarkable and a lot of
expert programmers if you've done a lot
of programming probably won't be
surprised by that if you want to learn a
new programming language at least the
basics not to become an expert at it not
to be an expert practitioner know all
the courts and ins and outs of the
language but to be able to execute some
basic program and basic scripting it
doesn't take that much work and that is
the big reason that I'm focusing on the
more theoretical aspects of computer
science to speak
is the theory of computer science so
this this is language independent its
technology independent it doesn't matter
whether you're using Python or Java or
C++ or Mac or Linux or Windows if you're
focused on the computer science part
which is an abstraction a level above
the programming of it then you can focus
on some more interesting types of
problems and really learn solutions and
theories for solving problems that you
may not have uncovered just in the
practice of going through your
programming problems so a common
criticism a lot of academic programs get
is that well when will you ever use
these ideas in real life and so if you
are a computer programmer you might say
to yourself well you know I know how to
do a lot of computer programming when am
I ever going to need to use calculus or
differential equations or advanced
number theory and the truth is you might
not need it you might not come across in
your general practice that these
examples are coming up where you need to
use this specific higher-level theory
but the converse is also true if one of
the problems you're encountering could
be solved there could be thought of as
an example of some abstract or
higher-level theory you're very unlikely
to uncover that just as a matter of fact
and that's one of the reasons I've
enjoyed doing this program and doing
this curriculum in this way is it is
giving me an exposure to a lot of higher
level ideas like artificial intelligence
or advanced algorithms and it's giving
me exposure to these ideas independent
of a specific programming problem that
I'm working on so when I do go and work
on my own programming projects in the
future or I want to work on specific
problems that are of interest to me that
are independent of this whole I'm like
to challenge having this knowledge of
all these different ideas will allow me
to look at those problems in a different
way and help solve them better so thanks
for following the MIT challenge I'll be
updating you guys next week with more
progress on the challenge and updates
for more self education resources Thanks
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