Python is one of the fastest growing programming languages in the world, widely used in fields such as data science, machine learning, and AI. With the rapid rise of AI over the past year, python’s dominance in this field remains uncontested. That said, the question of should you even be learning a programming language in 2024 still exists. Chatbots and Large Language Models will eventually phase out the typical coding job. AI programming tools like GitHub Copilot have already proven their capabilities.
That said, learning programming still remains as a critical skill. If you want to fully leverage what AI has to offer, a basic understanding of how to effectively communicate with a computer is still required. Furthermore, with the simplicity of a programming language like python, the time commitment to achieving 90% of its potential is not as much as you would think. A couple afternoons working through a basic course on python can get you all the fundamentals you need to start creating AI tools of your own.
How you should learn Python
The biggest difference between learning any programming language now versus ten years ago is how to approach learning. Ten years ago, you would want to learn every detail of the syntax all the way to the best practices for structuring code. Now, the approach you want to take is by getting a fundamental understanding of what Python is and how it works, then immediately diving into practical applications. This approach allows you to quickly get hands-on experience and see the results of your work, which is more engaging and motivating.
Here’s a structured approach to learning Python in 2024:
1. Understand the Basics:
Syntax and Semantics: Learn the basic syntax and semantics of Python. Understand how to write simple scripts, use variables, control flow structures (if-else, loops), and functions.
Data Structures: Get familiar with basic data structures like lists, dictionaries, sets, and tuples.
2. Practical Application:
Projects: Start small projects that interest you. This could be anything from a simple calculator to a web scraper or a basic game. The key is to apply what you’ve learned in a practical context.
Libraries and Frameworks: Familiarize yourself with popular Python libraries and frameworks like NumPy for numerical computations, pandas for data manipulation, and Flask or Django for web development.
3. Utilize AI and Tools:
AI Assistance: Use AI tools like GitHub Copilot to assist you in writing code. These tools can help you learn by providing suggestions and explanations as you code.
Interactive Learning Platforms: Use platforms like Codecademy, Coursera, and edX that offer interactive Python courses. These platforms often include hands-on projects and real-time feedback.
4. Advanced Topics:
Data Science and Machine Learning: Once you have a good grasp of the basics, delve into data science and machine learning with Python. Use libraries like scikit-learn, TensorFlow, and PyTorch.
AI and Automation: Explore how Python can be used for automation and AI. Build your own AI tools or automate repetitive tasks to improve productivity.
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