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

Scott Young
26 Feb 201204:11

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.
  • đŸ€– 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.
  • đŸ€– 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.

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Étiquettes Connexes
MIT ChallengeComputer ScienceSelf-LearningProgramming LanguagesScheme LanguageFunctional ProgrammingAI DesignProblem SolvingTheoretical CSEducational Resources
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