What skills do I need to succeed as a Python dev in 2020?
In more than 900 job specs for Python developers, scrapped from StackOverflow, AngelList, LinkedIn, and some fast-growing tech companies. We extracted the abilities which were mentioned the most frequently, and here they're.
In more than 900 job specs for Python developers, scrapped from StackOverflow, AngelList, LinkedIn, and some fast-growing tech companies. We extracted the abilities which were mentioned the most frequently, and here they're.
(The numbers refer to the number of mentions.)
Among the opposite frequently mentioned skills not highlighted during this chart were Unit Testing (32), Continuous Deployment (30), MongoDB (30), and OOP (30). If talking about the Machine Learning skills, the top commonly-mentioned ones were Pandas (29), NumPy (24), SciPy (15), and Scikit-Learn (11).
Surely, the need of those skills depends on how you use Python. If you’re a Machine Learning Engineer, you don’t have to know Django perfectly, and so on.Please note: This research shows the general tendencies within employment market, not the preferences of Python developers themselves. This rating may differ from the list of technologies most devs choose to use in their work. For some Python insights, address Python Developers Survey by Python Software Foundation, or Octoverse by GitHub.
To consolidate my skills, what resources should I work with?
To help you with this, I have gathered some resources respected by experienced developers from Python communities all over the world.
Python-related resources (web development included):
RealPython contains a set of Python tutorials: they also have a lot of videos on their YouTube channel, created by Dan Bader.
Python Weekly : A weekly newsletter that publishes several articles, publications, and jobs.
This website is filled of Python resources for professional developers, engineers, and scientists. Was Created by Kenneth Reitz.
Sentdex YouTube channel has many playlists about Django, ML, Python&Finance, and more.Collected by Harrison Kinsley.
Data Science, Machine Learning & AI:
Technical notes on implementing Data Science & AI. The topics covered also include AWS and Linux. (Made by Chris Albon.)
While Keras is one of the most popular neural network libraries for Python, it also includes a useful thematical blog.
A set of Scikit-learn tutorials for people who want to master scientific Python.A computer Vision (for artificial intelligence) and Deep Learning (machine learning) resource guide, by Adrian Rosebrock.
Practice makes perfect, so, create a list of skills you wish to practice or improve, and begin your road to the new heights. I hope this material will help you in boosting your IT career!
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