Is Learning Python Still Worth It In 2024? | Professor's Take

Data Science Cross-Validated

25 Jul 202408:09

Summary

TLDRDespite the hype around new technologies like GPT and AI tools, learning Python remains valuable in 2024, especially for data science and machine learning. Its ease of learning, strong community support, and extensive libraries make it a powerful tool. Fundamental coding skills are still essential, and Python provides a solid foundation to leverage new tools effectively.

Takeaways

🤖 Despite the rise of AI tools, learning Python is still valuable due to its versatility and powerful applications, especially in data science and machine learning.
🧑‍🏫 The speaker, having experienced several tech hype cycles, suggests that the current AI hype might not be as transformative as it is portrayed.
🚗 Past predictions about autonomous vehicles, medical AI, and blockchain replacing traditional systems have often been overstated in terms of their immediate impact.
💻 Python is a general-purpose language, not the best for every task, but it excels in machine learning and deep learning, making it a required skill for many data jobs.
📚 Python's syntax is designed for readability and ease of use, making it an excellent first programming language to learn.
🤔 The speaker emphasizes that programming languages are tools, and the choice of language should be based on the problem being solved, not a lifelong commitment.
🔍 Python has a strong community support, with abundant tutorials, training materials, and well-documented packages, which are crucial for learning and debugging.
🚀 Python's performance issues, such as its weak runtime and lack of native parallelism, are being addressed through new developments like the Mojo programming language.
🌐 The speaker's personal experience with multiple programming languages illustrates that programmers often learn new languages to solve different problems more efficiently.
🛠️ New languages and tools are created to increase efficiency and solve specific problems, but they do not replace foundational coding skills; instead, they enhance them.
🌟 The fundamentals of coding and problem-solving will always be in demand, and learning Python provides a solid foundation to leverage new tools effectively.

Q & A

Why are people questioning the value of learning Python today?
-People are questioning the value of learning Python due to the rise of AI tools and opinions from prominent figures like Nvidia CEO Jensen Huang, who suggests that computing technology should evolve to the point where no one has to program.
What is the speaker's perspective on the hype around AI and its impact on programming?
-The speaker believes that the hype around AI is similar to previous tech hype cycles and that the impact is often less dramatic than anticipated. They argue that coding will change but will not become obsolete, and that AI tools are not replacements for foundational coding skills.
What is the speaker's view on the future of coding and AI tools?
-The speaker thinks that coding will evolve and change, and people will use different tools in the future. However, they emphasize that foundational coding skills are essential and that AI tools are enhancements rather than replacements for coding.
Why is Python considered a general-purpose language?
-Python is a general-purpose language because it has a variety of capabilities, though it is not the best tool for most tasks. It can be used for designing games, web and mobile apps, automating processes, but there are often better-suited tools and languages for these tasks.
What makes Python particularly useful in the field of machine learning and deep learning?
-Python is particularly useful in machine learning and deep learning due to its extensive libraries and packages like pandas, numpy, scikit-learn, TensorFlow, and PyTorch, which have no rivals or equivalents in other programming languages.
Why is Python's syntax considered advantageous for beginners?
-Python's syntax is advantageous for beginners because it focuses on readability and ease of use, making it a great first language to learn. It allows for quick achievement of tasks, providing positive feedback that motivates learners to continue.
What are the main drawbacks of Python according to the speaker?
-The main drawbacks of Python mentioned by the speaker are its weak performance compared to other languages and its lack of native parallelism. Optimizing Python code for runtime or memory performance requires a lot of effort and deep knowledge.
What is Mojo, and how does it aim to address Python's limitations?
-Mojo is a new programming language under development that aims to combine the usability of high-level languages like Python with the performance of low-level languages like C and C++. It is being developed to address Python's limitations in performance and parallelism.
How does the speaker's experience with multiple programming languages inform their perspective on learning new languages?
-The speaker's experience with multiple programming languages, including Pascal, Basic, C, IDL, Fortran, and Python, shows that one doesn't choose a programming language for life. Languages are tools chosen based on the problem at hand, and learning new languages becomes easier once you are familiar with one.
What is the speaker's final verdict on the relevance of learning Python in 2024?
-The speaker concludes that learning Python is still worth it in 2024. Despite the hype around new technologies, Python remains a valuable and powerful tool, especially in data science and machine learning, due to its ease of learning, strong community support, and extensive libraries and resources.

Outlines

00:00

🤖 The Hype and Reality of Python in Tech

This paragraph discusses the skepticism around the continued relevance of learning Python amidst the rise of AI tools and the opinions of tech leaders like Nvidia's CEO, Jensen Huang. The speaker, drawing from personal experience with multiple tech trends, suggests that the impact of new technologies is often less dramatic than the hype. They argue that while headlines suggest coding may become obsolete due to AI, this is unlikely. Python's adaptability and its role in machine learning and data science, supported by a strong community and extensive libraries, ensure its continued dominance and relevance.

05:01

🛠 The Versatility and Limitations of Python

The speaker elaborates on Python's role as a general-purpose language, noting that while it has various capabilities, it is not the best tool for every task. They highlight Python's strengths in machine learning and data science, where it has become the de facto language due to its extensive libraries and packages. The paragraph also touches on Python's ease of learning and strong community support, which makes it an excellent first language for many. However, the speaker acknowledges Python's performance limitations compared to other languages and the challenges of optimizing Python code for performance. They also mention ongoing efforts to address these issues, such as the development of new programming languages like Mojo.

Mindmap

Keywords

💡Python

Python is a high-level, general-purpose programming language known for its readability and ease of use. In the context of the video, Python is highlighted as a valuable tool, especially in the fields of data science and machine learning. The script mentions Python's popularity and the wealth of libraries and resources that support it, making it a go-to language for many in the tech industry.

💡Jensen H

Jensen H refers to Jensen Huang, the CEO of Nvidia, who is quoted in the script discussing the future of computing technology. His statement about creating technology so that no one has to program suggests a vision where tools may automate coding tasks, which is a point of debate in the video regarding the necessity of learning to code.

💡Tech Hype

Tech Hype in the video refers to the exaggerated expectations and predictions about the impact of new technologies. The script uses past examples like self-driving cars, machine learning in radiology, and blockchain to illustrate how these technologies have been hyped but did not revolutionize their respective fields as quickly or as dramatically as predicted.

💡Machine Learning

Machine Learning is a subset of artificial intelligence that enables systems to learn and improve from experience without being explicitly programmed. The video discusses how machine learning models have been predicted to replace certain jobs, like radiologists, and how Python has become a required skill for many data-related jobs due to its strong ecosystem of machine learning libraries.

💡Readability

Readability in the context of programming refers to how easy it is to understand the code. Python's syntax is praised in the video for its focus on readability, which contributes to its popularity, especially for beginners. The script contrasts Python's ease of learning with the author's experience learning C, which was more challenging.

💡Community Support

Community Support denotes the availability of help and resources from a community of users and developers. The video emphasizes the strong community support for Python, with numerous tutorials, well-documented packages, and platforms like Stack Overflow that facilitate learning and problem-solving.

💡Performance

Performance in programming refers to how efficiently a language executes code. The script points out Python's弱点, such as its relatively weak performance compared to other languages and its lack of native parallelism, which means it can be slower and require more effort to optimize for speed and memory usage.

💡Mojo

Mojo is a new programming language mentioned in the script that aims to combine the usability of high-level languages like Python with the performance of lower-level languages like C and C++. This reflects the ongoing efforts to address the performance limitations of Python and the evolution of programming languages.

💡Problem Solving

Problem Solving is a fundamental skill in programming, emphasized in the video as a core competency that remains in demand regardless of the specific tools or languages used. The script suggests that the ability to code provides a solid foundation for leveraging new tools and technologies effectively.

💡GenI

GenI, likely a shorthand or brand name for generative AI tools mentioned in the script, represents the latest advancements in AI that can potentially automate coding tasks. The video discusses skepticism about the hype surrounding GenI and whether it will render coding obsolete, ultimately concluding that foundational coding skills are still essential.

Highlights

Debates on the value of learning Python persist due to the rise of AI tools and opinions from industry leaders like Nvidia's CEO, Jensen Huang.

The speaker, a 40-year-old experienced in multiple tech trends, doubts the current hype around AI tools replacing coding.

Historically, the impact of tech advancements has often been less dramatic than the hype suggests.

CEOs are tasked with selling visions of the future rather than delivering fully realized products.

Coding is unlikely to become obsolete; current headlines about AI writing code are just another passing hype.

Python is a general-purpose language with a variety of capabilities but not the best at most tasks.

Python excels in machine learning and deep learning, making it a required skill for many data jobs.

Python's syntax prioritizes readability and ease of use, making it an excellent first language to learn.

The speaker contrasts their difficult experience with C to the ease of learning Python.

Python's community support and extensive documentation make it an accessible language for learners.

Python's main drawbacks are its weak performance and lack of native parallelism.

New programming languages like Mojo are being developed to combine usability with high performance.

The speaker's experience with multiple programming languages illustrates the transient nature of tech tools.

Programming languages are tools chosen based on the problem at hand, not lifelong commitments.

Learning one programming language makes learning others easier due to the transferability of coding concepts.

The creation of new languages and tools is driven by the programmer's goal to increase efficiency.

AI and advanced tools are enhancements to coding, not replacements, and should be seen as aids to work smarter.

Despite technological evolution, the fundamentals of coding and problem-solving remain in high demand.

Python is still worth learning in 2024 for its value in data science and machine learning, ease of learning, and strong community support.