Are you considering a career change and interested in acquiring Python training? To make an informed decision, it's essential to understand which fields or industries require Python and the diverse roles you could potentially fill upon mastering this versatile programming language.

Which Industries & Professions Use Python?

One essential aspect of receiving professional Python training to set yourself up for a career change is learning what fields or industries require such training. Each will have different requirements and expectations for prospective employees, and you should consider these when you start training. Students who have an idea of what kind of work they want to do and those who aren’t yet sure what path to take after learning Python skills can benefit equally.

What is Python?

Python is one of the fastest-growing programming languages on the planet. Data Scientists, Web Developers, and other tech professionals use Python for a range of tasks—from building websites to data analysis, automation, and machine learning. Like Java and Ruby, Python is mainly an object-oriented programming language (OOP), which means it organizes around data (objects) instead of functions or logic.

Thanks to its straightforward syntax, adaptability, and the urgent need for Python skills in today’s job market, this essential language ranks as the number one choice for those learning to code. The U.S. Bureau of Labor Statistics predicts the average growth rate for Web Developers will be 13% between 2020 and 2030, and many of these positions require Python expertise. Other fields requiring Python include cybersecurity, software engineering, and business analysis.

Read more about what Python is and why you should learn it.

What Can You Do with Python Skills?

Python is a versatile language with a host of applications, but the most well-known include:

• Data Science - Data science extends to numerous industries, and using Python to understand data is paramount. Python libraries like NumPy and Matplotlib enable Data Scientists and other professionals to use visualization to gain insights into data. Additional top Python libraries include TensorFlow, SciPy, Pandas, and Scikit-learn.
• Artificial Intelligence (AI) & Machine Learning (ML) - Machine Learning Engineers and Architects use Python to build models. At the same time, AI Engineers and Architects may need this essential programming language for everything from assessing AI solutions to advanced automation.
• Web Development - The use of Python in web development goes back to its beginnings. Frameworks like Django and Flask have famously provided web development for well-known companies like Instagram, Dropbox, and Pinterest. Tech pros, including Developers, report that Python is easy to integrate with other languages like C/C++ and Java. Other top frameworks include Bottle, CherryPy, and Dash.
• Game Development - Frameworks for game development include Pygame, PyKyra, and Panda3D, but there are numerous others. Python continues to support the gaming industry in meaningful ways.
• Enterprise Applications - Enterprise-grade apps built with Python include leading technology stacks like Netflix, Microsoft, and Spotify.

Common Industries That Use Python

As one of the most popular programming languages in the world, Python cuts across virtually every industry and sector. Colleges and universities, major multinational corporations, and governmental agencies are all examples of organizations that use Python.

While industry usage varies by region, some of the biggest industries rely on Python for numerous applications. The following are among the most reliant on this high-level programming language.

Data Science

The data science/data analysis field tops the list because Python is needed the most here. Essential tools for Data Scientists include Python, SQL, and popular libraries like NumPy and Pandas.

What's unique about data science and analysis is the level to which they extract meaning from large datasets. Job responsibilities can include everything from web scraping and developing algorithms to presenting data visualizations to C-suite executives.

The data science field will likely grow at a faster rate than perhaps any other discipline over the next decade. Predictions from the U.S. Bureau of Labor Statistics seem to bear this out. They project a stunning 36% growth rate for data science between 2021 and 2031. 

Whether you plan to work as a Data Analyst, Data Scientist, or Business Analyst, consider this field among the best employment options for the decade ahead.

Web Development

Like data science, web development covers a range of opportunities and responsibilities. Web Developers and Digital Designers work in virtually every sector, creating websites, applications, and navigation menus for clients of all types.

Web development professionals can hold many different positions with dissimilar titles. Among the most common are:

• Web Developer
• Full Stack Developer
• Front End Developer
• Back End Developer
• Python Developer
• Digital Designer

Responsibilities among these skilled professionals can differ widely, too. Whereas a Digital Designer might be responsible for layout, typography, and graphics, a Full Stack Developer may construct every part of a website's framework, from coding to online checkout tools.

Python programming is essential to many web development roles, but not all. The employment outlook for Digital Designers and other Web Developers looks almost as bright as that for Data Scientists: the Bureau of Labor Statistics projects a 23% growth rate over the next decade—much faster than the average position.

Artificial Intelligence

Artificial intelligence (AI) is one of the hottest fields in today's rapidly changing job market. While some fields may seem remote from our daily lives, AI affects us behind the scenes through one of its most essential subsets: machine learning (ML).

Machine learning algorithms drive many modern technologies, from facial recognition programs to search recommendations from Netflix and Amazon. Job responsibilities for ML vary, but these experienced pros typically hold titles like:

• Machine Learning Engineer
• Deep Learning Engineer
• Data Scientist
• NLP Scientist (Natural Language Processing)
• Business Intelligence (BI) Developer
• Research Information Scientist

Though not quite as impressive as the job outlook for web development and data science proper, artificial intelligence and ML engineering growth projections look bright for the next decade. The BLS projects a 21% growth rate over the next decade for Computer and Information Research Scientists, a category that includes AI and ML.

Learn Python Skills with Noble Desktop

Noble Desktop offers multiple ways to learn Python, both in-person and online, through teleconferencing. They provide Python training as an essential component of data science and analytics, FinTech, cybersecurity, and web development. Their Python Programming Bootcamp offers hands-on Python training in an immersive environment. Beginners learn Python fundamentals in this 30-hour bootcamp, where participants develop project-based coding portfolios. Graduates receive a verified Certificate of Completion and can retake the course for up to a year at no additional charge.

Students can save by taking the Python Programming Bootcamp as part of Noble’s Python Developer Certificate program. The curriculum for this certificate includes a 60-hour unit on Python Web Development with Django. In this intensive course, you’ll learn about URL dispatchers and automation, along with GitHub and SQL. Attendees should have some experience with HTML and CSS before enrolling.

Additional courses featuring Python include Noble Desktop’s Python for Data Science Bootcamp, FinTech Bootcamp, and Data Science Certificate program. Students planning careers in data science, data analytics, cybersecurity, or financial analysis should consider enrolling in one of these programs to get comprehensive Python training.

Key Takeaways

• Python training requirements differ among professionals, depending on their field or industry.

• Like Java and Ruby, Python is an object-oriented programming language (OOP), which means Python organizes around objects rather than functions.

• Between 2020 and 2030, the Bureau of Labor Statistics (BLS) projects a 13% growth rate for Web Developers, a category that includes Python Developers.

• Top industries that use Python include:

• Data Science
• Web Development
• Artificial Intelligence (AI) and Machine Learning (ML)

• Top roles for Python development pros include:

• Web Developer
• Full Stack Developer
• Front End Developer
• Back End Developer
• Python Developer
• Digital Designer

• You can receive comprehensive Python training through Noble Desktop, either in person or online. Top courses include:

• Python Developer Certificate
• Python for Data Science Bootcamp
• Python Programming Bootcamp

Comparison of Python Training Formats

Once you’ve decided to learn Python, the next important question is deciding how you plan to learn these skills. Most students report that guided training provides the best outcomes. There is no shortage of available options for students to receive guidance in their Python training. Read on to learn more about different Python training options and what advantages and disadvantages they carry with them.

What is Python?

Python is one of the fastest-growing programming languages on the planet. Data Scientists, Web Developers, and other tech professionals use Python for a range of tasks—from building websites to data analysis, automation, and machine learning. Like Java and Ruby, Python is mainly an object-oriented programming language (OOP), which means it organizes around data (objects) instead of functions or logic.

Thanks to its straightforward syntax, adaptability, and the urgent need for Python skills in today’s job market, this essential language ranks as the number one choice for those learning to code. The U.S. Bureau of Labor Statistics predicts the average growth rate for Web Developers will be 13% between 2020 and 2030, and many of these positions require Python expertise. Other fields requiring Python include cybersecurity, software engineering, and business analysis.

Read more about what Python is and why you should learn it.

What Can You Do with Python Skills?

Python is a versatile language with a host of applications, but the most well-known include:

• Data Science - Data science extends to numerous industries, and using Python to understand data is paramount. Python libraries like NumPy and Matplotlib enable Data Scientists and other professionals to use visualization to gain insights into data. Additional top Python libraries include TensorFlow, SciPy, Pandas, and Scikit-learn.
• Artificial Intelligence (AI) & Machine Learning (ML) - Machine Learning Engineers and Architects use Python to build models. At the same time, AI Engineers and Architects may need this essential programming language for everything from assessing AI solutions to advanced automation.
• Web Development - The use of Python in web development goes back to its beginnings. Frameworks like Django and Flask have famously provided web development for well-known companies like Instagram, Dropbox, and Pinterest. Tech pros, including Developers, report that Python is easy to integrate with other languages like C/C++ and Java. Other top frameworks include Bottle, CherryPy, and Dash.
• Game Development - Frameworks for game development include Pygame, PyKyra, and Panda3D, but there are numerous others. Python continues to support the gaming industry in meaningful ways.
• Enterprise Applications - Enterprise-grade apps built with Python include leading technology stacks like Netflix, Microsoft, and Spotify.