Is Python enough to get a Job?
Yes, gaining excellent skills in Python is enough to get a job, being a highly skilled Python developer opens up many doors of opportunities. You will be able to work on machine learning, web development, data science, app development, system administration, task automation, and more using Python skills.
You also need to be familiar with Data structures, and Algorithms to increase your chances of getting a job, especially in big tech companies. Having a portfolio of your Python projects will also be helpful to attract the attention of employers.
Python is a general-purpose programming language, this means that you can use Python to create different types of programs. But there are some areas where Python excels in its application.
Python is one of the most popular programming languages out there. According to a 2022 survey by Stack Overflow, Python is the 4th most used language by professional developers.
It also consistently ranks as one of the most loved programming languages. The same survey reported that Python is loved by 67.34% of developers versus 32.66% of developers who dreaded it.
This means that there are thousands of companies that use Python for a variety of different programs. Python is used by many companies such as Google, Meta, Microsoft, Netflix, Uber, Pinterest, Mozilla, Open Stack, and many others.
These companies and many others provide a lot of employment opportunities for many Python programmers to work on a variety of projects.
Having a solid Python programming understanding opens up windows of opportunities to work on world-class projects in different fields. Here are some of the opportunities and the types of jobs you can apply for if you have excellent Python skills.
MACHINE LEARNING ENGINEER
Python is the most popular programming language for machine learning. You can become a machine learning engineer by gaining a good understanding of Python and its machine learning libraries.
Python has a lot of resources and libraries that you can use for machine learning and artificial intelligence. Here are some of the popular ones.
Tensorflow is an open-source library for developing and training machine learning models. Tensorflow also helps developers to build and deploy machine learning-powered applications.
It is used by many companies such as PayPal, Bloomberg, eBay, Dropbox, IBM, Coca-Cola, Google, Airbnb, DeepMind, Uber, Snapchat, Qualcomm, Airbus, Intel, Twitter, and many others. All these companies are prospective employers of Python machine learning engineers.
Keras is an open-source, high-level, deep learning API developed by Google for implementing artificial neural networks. It can run on Tensorflow, Theano, Microsoft Cognitive Toolkit, and many other platforms.
Numpy is the most popular package for scientific computing with Python. It is used for machine learning, data science, visualization, Array libraries, image processing, signal processing, etc. Numpy also powers many other scientific and machine learning libraries.
Other Python-based machine learning libraries include SCIPY, SCIKIT-LEARN, PYTORCH, PANDAS, THEANO, MATPLOTLIB, NLTK, etc.
Gaining great skills in Python programming for machine learning makes you employable by many companies that use Python for machine learning. You can start your journey to become a machine learning engineer in 3 months with the Udacity machine learning program.
Machine Learning Engineers make an average base salary of $124 240 per year in the United States (indeed.com).
You can also become a web developer by having a good understanding of Python. Python is one of the most popular programming languages in web development. Python was used to build the Instagram backend.
Python is great for web development because Python’s standard library supports many Internet protocols such as HTML and XML, JSON, E-mail processing, Support for FTP, IMAP, and other Internet protocols. It also supports an easy-to-use socket interface.
You can use Python web frameworks such as Django, Flask, Pyramid, FastAPI, Web2Py, Bottle, Tornado, etc. You can use these frameworks to build web applications and APIs. By using these technologies, you can work on a wide range of projects.
There are many companies you can look up to for employment that use these technologies. Some of the popular ones include Meta, Pinterest, Microsoft, Uber, Open Stack, Mozilla, Netflix, National Geographic, Knight Foundation, Disqus, and many others.
If you have a good understanding of Python for app development, you can also get a job as an app developer. You can develop desktop and mobile applications for Windows, macOS, Linux, iOS, and Android.
You use Python platforms such as Kivy, Tkinter, PyQt, Pyside, wxPython, PyGObject, etc. these platforms and packages are used by many different companies to make Graphical User Interfaces (GUIs) for Windows, macOS, Linux, iOS, and Android.
Python programming skills can also help you to get a job as a system administrator. Python has many great automation platforms that make applications and systems easier to deploy and manage.
You can use platforms such as Ansible, Open Stack, Salt, Xonsh, and many others. These technologies are used by many companies for system administration. Having great skills in these platforms will open up many employment opportunities for Python programmers.
Python is also popular for building testing tools, business applications, and scientific computing.
It can be seen that there are a lot of opportunities in different fields for Python programmers. Python allows you to work on a wide array of projects. Ultimately, Python is enough to get a Job in many tech companies, as long as you can invest your time in enhancing your development skills.
As you develop your technical skills, you should also work on developing your soft skills such as communication, teamwork, organizational, time management, decision-making, critical thinking, etc.
You must also invest time to learn Data structures and Algorithms. Most, if not all major tech companies require a good understanding of data structures and algorithms. Python makes it easy to work with Data Structures and Algorithms.