How to Become a Python Developer
What Does a Python Developer Do?
A Python Developer is responsible for coding, designing, deploying, and debugging development projects, typically on the server-side (or back-end). They may, however, also help organizations with their technological framework.
A Python Developer’s role can span a wide variety of duties. You might be asked to create an application for your employer, design the framework for your code, build tools as necessary to get the job done, create websites, or publish new services. A Python Developer often works in close collaboration with data collection and analytics to create useful answers to questions and provide valuable insight.
Like most programming positions, the specifics of this job vary based on the needs of your employer. Some Python Developers work as independent contractors instead of being exclusive to one company.
Python is being used in web development, machine learning, AI, scientific computing, and academic research. Its popularity can be credited with the growing data science community embracing artificial intelligence and machine learning. Industries like education, healthcare, and finance are using machine-learning applications to innovate their organizations.
Python is also widely used by companies including Netflix, Google, Facebook, Reddit, YouTube, Instagram, and more. Specifically, Spotify uses Python within its back-end services, capturing user data to provide accurate recommendations and playlists. Dropbox, meanwhile, uses Python scripts to create its native applications on each platform (Windows, macOS, Linux, iOS, Android, etc.)
A Python Developer will likely also be responsible for creating integrable systems, but ultimately, the role depends on the industry and job description.
What Jobs Can You Get With Python?
A professional who specializes in Python can hold a number of job titles, including Python Developer, Data Scientist, and Machine Learning Engineer. The exact work you’ll be doing will depend on the industry, company, and scope of the role, but essentially you will be using code to create sites and applications, or work with data and AI.
Python is most commonly used in big data centers, as well as a "binder" language between other languages. Google, NASA, Industrial Light & Magic and id Software all use Python because of its capabilities and expandability. Python is frequently used by Game Developers as the glue between C/C++ modules, or you can use it with PyGame to make a full-blown game. It's also popular among Scientists and Statisticians with SciPy and Pandas.
Although there are many different jobs that require Python programming skills, they have one thing in common: they tend to pay very well. That’s probably because employers are having a hard time finding Python talent across a number of industries.
According to the Developer Survey by StackOverflow, Python was one of the most in-demand technologies of 2018, 2019, and 2020. As of 2020, it is ranked as the world’s fourth most popular programming language among professional Software Developers, as well as the first most-wanted programming language.
Web Developers typically specialize in either “front-end” (“client-side”) development or “back-end” (“server-side”) development, with the most sought-after development professionals, called “Full-Stack Developers,” working in both.
In addition to layout and server-side responsibilities, Web Developers keep sites current with fresh updates and new content. Web Developers typically work in a collaborative role, communicating with management and other programmers to ensure their website looks and functions as intended.
Python Developers often work server side, either writing logic or developing the platform. Typically, they are responsible for deploying applications and working with development and design teams to build websites or applications that suit the user’s needs.
Python Developers also support Front-End Developers by integrating their work with the Python application.
Software Engineers, like Developers, are responsible for writing, testing, and deploying code. As a Software Engineer, you’ll need to integrate applications, debug programs, and overall improve and maintain software.
Software Engineers’ day-to-day routines usually involve ensuring active programs run smoothly, updating programs, fixing bugs, and creating new programs. Software Engineers write for a wide variety of technologies and platforms, from smart home devices to virtual assistants.
Data analysts collect, organize, and interpret data to create actionable insights. To accomplish this, Data Analysts must collect large amounts of data, sift through it, and assemble key sets of data based on the organization’s desired metrics or goals.
A Data Analyst uses Python libraries to carry out data analysis, parse data, analyze datasets, and create visualizations to communicate findings in a way that’s helpful to the organization.
Data Scientists have a more complex skill set than Data Analysts, combining computer science, mathematics, statistics, and modeling with a strong understanding of their business and industry to unlock new opportunities and strategies.
Data Scientists are not only responsible for analyzing data but often also using machine learning, developing statistical models, and designing data structures for an organization.
Machine Learning Engineer
If you’re looking to go beyond data analysis, you can pursue machine learning, a subset of data science and artificial intelligence. Machine Learning Engineers perform statistical analysis and implement machine learning algorithms that can be used in AI.
Machine Learning Engineers are also responsible for taking theoretical data science models and helping scale them to production-level models capable of handling terabytes of real-time data.
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Recommended Courses for Python Developer
The Python certificate course provides individuals with fundamental Python programming skills to effectively work with data.
The Data Science bootcamp is an intensive course designed to launch students' careers in data.
Taught by data professionals working in the industry, the part-time Data Science course is built on a project-based learning model, which allows students to use data analysis, modeling, Python programming, and more to solve real analytical problems.
The part-time Data Analytics course was designed to introduce students to the fundamentals of data analysis.