Week 20 - Can You Learn a Programming Language in 4 Days?

Summary

In 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

00:00

📚 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.

Keywords

💡MIT Challenge

The MIT Challenge refers to the ambitious goal of learning the computer science curriculum of the Massachusetts Institute of Technology (MIT) in a self-directed manner within a year, without enrolling in any classes at the institute. In the video, the creator discusses their progress and experiences with this challenge, highlighting the learning of new programming languages and paradigms as part of the curriculum.

💡Scheme

Scheme is a programming language that is part of the Lisp family and is known for its use of the functional programming paradigm. In the video, the creator mentions learning Scheme as a new language, which is a departure from the object-oriented or procedural styles of programming they were previously familiar with, such as Java or C++.

💡Functional Programming

Functional programming is a programming paradigm that treats computation as the evaluation of mathematical functions and avoids changing-state and mutable data. It is contrasted with the object-oriented and procedural paradigms mentioned in the script. The creator discusses the challenge of adopting this new way of thinking in programming while learning Scheme.

💡Artificial Intelligence

Artificial Intelligence (AI) is the field of computer science that aims to create machines capable of intelligent behavior. The video script mentions the creator learning AI as part of their computer science challenge, including problem sets that involve creating an AI for solving a simplified version of chess.

💡Problem Sets

Problem sets are collections of tasks or exercises that are designed to test and reinforce learning in an educational context. In the script, the creator talks about completing seven problem sets in the AI class, which included creating an automatic Sudoku solver and an AI for chess.

💡Computer Science Theory

Computer science theory involves the study of the fundamental properties and concepts of computation, independent of any specific programming language or technology. The creator emphasizes the importance of focusing on the theoretical aspects of computer science, which are language and technology agnostic, to understand and solve complex problems.

💡Abstraction

Abstraction in computer science refers to the process of reducing complexity by hiding unnecessary details and focusing on essential features. The script discusses the importance of abstraction in understanding computer science theory and solving problems at a higher level, rather than getting bogged down in the specifics of programming languages.

💡Expert Practitioner

An expert practitioner is someone who has a deep understanding and mastery of a particular field or skill. The video mentions that while learning the basics of a new programming language can be done quickly, becoming an expert practitioner requires more extensive knowledge and experience.

💡Self-Education

Self-education is the process of acquiring knowledge or skills without formal instruction. The creator of the video is engaging in self-education by undertaking the MIT Challenge, learning new programming languages, and exploring computer science theory on their own.

💡Higher-Level Ideas

Higher-level ideas refer to advanced concepts or theories that are not necessarily immediately applicable but provide a deeper understanding of a subject. In the context of the video, the creator discusses the value of learning higher-level ideas in computer science, such as AI and advanced algorithms, to approach problems from a new perspective.

💡Programming Projects

Programming projects are tasks or initiatives that involve writing code to create software or solve specific problems. The script mentions that the creator's knowledge of various computer science theories and concepts will be beneficial when working on their own programming projects in the future.

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