Python is a popular computer programming language that has many versatile applications, but it is particularly revered by data scientists around the world. It doesn’t take much time to learn and is simply written.
Python is also useful for data scientists because it allows for easier automation of important but repetitive tasks. This enables professionals to focus more on creative thinking and problem solving the more difficult aspects of their jobs. Python also boasts a growing community of users and libraries of pre-written code so users can feel supported when using the language. Because of its popularity and the continually-growing job opportunities in the field, those who learn Python can rest assured that careers will be in-demand for years to come. Let’s learn more about why Python is the preferred language for data science.
Basics of Data Science
Before diving into how Python and data science work together, it may be helpful to give a brief overview of what a data scientist does. Data science is all about discovery. In simple terms, a data scientist uses the raw data produced by an organization to answer questions and improve processes. They are able to locate the data relevant to whatever problems need solving, then synthesize the data and communicate their findings to relevant stakeholders so the team can make informed decisions about next steps to drive business forward.
Data scientists generally work with data that can be categorized in one of two ways: Public and private. Public data is readily available to anybody who would like to access it. This information can come from places like social media pages, job postings, and press releases. Private data is only accessed with permission and usually contains sensitive information like social security numbers and banking information. For these reasons, data scientists usually have skills in cybersecurity as well.
Data science has applications in nearly every industry and is used to make crucial decisions that impact entire communities. For example, data science software is often used to predict the likelihood of recidivism in violent criminal offenders. It can also be used to predict and track the spread of communicable diseases, and more tools are being developed to help identify more aggressive types of cancer in their earlier stages.
Why do Data Scientists Love Python?
Now that you understand more about the complex problems that data scientists are often tasked with solving, you can better understand why Python is the ideal tool. It is readable and understandable, even to those who are not experts in coding. It has many functions and capabilities, and it continues to grow in popularity.
Python was created with simplicity and accessibility in mind; the syntax is primarily made up of uncomplicated English words that directly illustrate commands and operations. For data scientists with more experience in statistics than coding, it is easier to learn and understand than other programming languages. Python is also an open-source language, meaning it is free to use and constantly being updated for maximum efficiency.
Python is the fourth most popular programming language among developers today. Because it is so common to work with, Python offers a rich community of resources to its millions of users. This community hosts conferences and can help new users with tutorials and other troubleshooting tips. More users also means that there are many powerful libraries available for Python, especially for those who use it for data science. Libraries contain selections of specific code to assist with common projects, which allows users to learn new ideas from each other. Libraries also help to simplify more complex tasks without sacrificing accuracy.
All signs point to Python continuing to grow in popularity with data scientists for the next decade at least. As more users discover its many uses, the libraries available will continue to advance and the community of users will become more knowledgeable.
Learn Python with Career Centers
If you want to learn more about how Python can enhance your data science career, check out the Python and Data Science courses available through Noble Desktop, a partner program with Career Centers. Noble Desktop offers a unique combination of expert instruction with small class sizes so no student gets left behind. The school offers a 12-hour Intro to Python Programming course which was designed specifically for beginners.
Those looking for something a little more intensive can consider enrolling in the Python Programming Bootcamp. This course is also open to beginners, but it covers more than an introductory course would. For a fully immersive experience in Python, you can take a 90-hour Python Developer Certificate course. This course is offered on a full-time or part-time schedule and gives you all the essential skills to become a well-rounded Python developer.
Noble Desktop also has several data science courses to choose from. Noble offers a 30-hour Python for Data Science Bootcamp which is open to beginners and provides a solid foundation for those who want to learn how to analyze data and create visualizations. If you’re able to make a more lengthy time commitment, the Data Analytics Certificate and/or the Data Science Certificate might be of interest to you. Both of these courses last for several weeks, but students can gain vital knowledge to begin a data science career in a relatively short period.