Have you ever explored all of the things Python can do? If you plan a data-centered career, you’ll have to put Python at the top of your priority list. Data Analysts, Software Engineers, and Back End Developers all learn Python for everything from data visualization to building applications and websites.
Here, you’ll learn more about the types of careers that benefit from Python and how it can enhance your professional life. Regardless of your overall goals, learning Python is a valuable and impressive skill to add to your resume.
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 demand Python. 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?
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 household name 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 Uses for Python
Python’s versatility and ease of use make it a respected, universally-known programming language. Data science, software engineering, and web development pros all use Python for a host of tasks, both simple and complex. Anyone starting a data-focused career should consider Python’s importance.
Data Visualization With Python
Proficiency in Python sits atop many online lists of programming languages, but this essential language is one of many skills you’ll need. Whether you plan to work as a Data Scientist or a Financial Analyst, time invested in Python pays dividends year after year.
In Python’s Package Index, you’ll find dozens of data visualization libraries. Matplotlib may have a reputation as the most important of these, but also consider Pandas, NumPy, Seaborn, and Altair. Many data pros prefer NumPy and Pandas for extracting information.
Some libraries allow users to create graphs, while others render information in the form of images. Check out the top data visualization libraries to decide which ones are best for you.
Many users today know Python for machine learning or data visualization, but its popularity goes well beyond those uses. Data Scientists use Python to manage and analyze vast quantities of data, and the data science umbrella often includes leading-edge areas like machine learning and artificial intelligence.
Full Stack Developers and Back End Developers use Python with Django REST in their work, encompassing database technologies like MySQL and MongoDB. However, Python also gets points for developing applications. Python Developers may specialize in back end development or data analysis, but many work in product or app development. Developers can create applications quickly with Python. It’s useful for a variety of apps, including:
- Business apps
- Computer-Aided Design (CAD)
- Web scraping
- Embedded apps
- Desktop GUI (graphical user interface)
- Audio and video apps.
Write Complex Algorithms
If you’re writing computer programs, algorithms will be a crucial component of your skill set. When you master algorithms and data structures using Python, you’ll be on your way from a beginner to expert.
Python’s built-in data structures include lists, dictionaries, tuples, sets, stacks, and strings, to name a few. Problem-solving with Python typically involves algorithms. When you study Python, you’ll learn the differences among many algorithms, from the brute force type to the divide and conquer paradigm. Common in Python training, examples include searching algorithms like Linear Search, Binary Search, and Fibonacci Search, and sorting algorithms like Insertion Sort, Bubble Sort, and Merge Sort.
For those looking to learn Python as part of a more comprehensive curriculum, consider the Python Developer Certificate or Software Engineering Certificate programs from Noble Desktop.
Another significant benefit of Python is its capacity for task automation. As businesses get busier and tasks must be completed at lightning speed, automating repetitive tasks has grown ever more attractive to everyone, from sole proprietors to CEOs of multinational corporations.
With its easy syntax and readability, Python offers an ideal approach to task automation, even for companies outside the high-tech realm. Automation works well for reading and writing files, interacting with APIs, sending emails, and web scraping.
Not every task lends itself to automation, but software testing proves another area where Python can help companies save time and money. Some organizations use manual testing, others use automation, and others use some combination of the two. With Python’s testing libraries and frameworks, automated software testing can help avoid human error while finding bugs earlier in the development process. Top testing frameworks include PyTest, Robot, and Selenium.
How to Start Learning Python
Python beginners often find various ways to learn this essential programming language. While some professionals benefit from college or university programs, others get their training quickly in a matter of months or even weeks. Online or in-person courses, including bootcamps and certificate programs, have become one of the most popular methods to learn Python. And many novices start with free online resources like blog posts and video tutorials.
You can find a host of Python Training options either held in-person or live online through teleconferencing using Noble Desktop’s Classes Near Me tool. Here you’ll find everything from a Data Science Bootcamp and FinTech Bootcamp to machine learning (ML) classes and algorithmic training. Live online courses offer benefits similar to in-person training, but participants can learn from the comfort of home.
While not as popular as the intensive bootcamp model, learning Python through self-paced training has become a viable option thanks to the many courses available on-demand through providers like Noble Desktop. These programs often focus on an attendee’s level of learning, which may include beginner (“apprentice”), intermediate (“journeyman”), or advanced.
Many Python learners begin with free tutorials and videos. It makes sense that novices should learn a few things about their subject before committing to a paid program. Start with Noble Desktop’s YouTube channel, which offers an entire playlist of Python, data science, and SQL webinars and tutorials. Blog posts provide significant benefits for those who learn best by reading, and Noble’s Python Blog hosts valuable information as well.
Read the full guide on how to learn Python.
Learn Python with Hands-on Training at 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 areas like 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.
- Python is one of the most popular programming languages in the world. It’s an open-source language, which means users get free access to Python.
- Tech professionals who need Python skills include:
- Data Scientists
- Data Analysts
- Software Engineers
- Back End Developers
- Financial Analysts
- Cybersecurity Analysts
- Top uses for Python include: Data visualization, app creation, writing complex algorithms, and task automation.