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3 Reasons Python Programming is So Popular

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Since its introduction in the ’90s, Python has rapidly become one of the world’s most popular programming languages. Most recently, we have seen Python even surpass other languages like Java. How has a humble language like Python managed to gain so much attention? Why is Python so popular?

Some estimates claim there were over 8 million active users of Python by the end of 2018. What has created the demand for this programming language compared to Java with 7.6 million, C# with 6.7 million, and JavaScript with 11.7 million active users at the end of 2018? One way to think about using a programming language is to think about its primary use case. In the case of JavaScript, the primary function is building software for the web or the cloud. Cloud infrastructure and web development are still very common business needs. For C# and Java, these use cases are more driven to desktop application development, which has started to fall off with the rise of the mobile-first mentality of end-users.

1. The rise of analytics and Python.

With Python, the use cases are shifting to data analysis and machine learning. As Clive Humby stated back in 2006, “Data is the new oil.” The bottom line is that data science has a high value. Companies have made data analytics and data science a priority due to their abilities to maximize profits and gain better insights on business. Because of well-developed resources like the data science workhorses of Pandas and Scikit-learn, Python easily does the heavy-lifting of machine learning algorithms.

Along with ready-made tools to do the work, Python is also an incredibly readable programming language. Its syntax was explicitly designed to remove a lot of unnecessary code and emphasize making it human-readable. Python makes the development of complex programs easier to write and easier to manage, which translates directly to the bottom line of the company.

2. Why is Python so popular? One word of many: Free.

The facts that drive Python’s booming popularity: it is an open source and free to use. Developers all over the world are writing and distributing software packages in Python that small companies or individual developers can use in their projects for free. Who wouldn’t want to be able to plug into a sophisticated image segmentation library developed by Google? At no cost! Just a few years ago, similar image analysis software cost thousands of dollars and was not nearly as user-friendly.

3. It takes a village.

Python programming is easy to learn, easy to write, cheap to build with, and massive followings of programmers worldwide. It’s no wonder Python is rapidly gaining in popularity. One of the worst feelings for new developers is not understanding why their program isn’t working, but with Python, the programming and data science communities are very active. Blog posts, answer sites like StackOverflow, and groups on LinkedIn have made getting feedback and solutions to your issues easier than ever. Getting hands-on help with issues quickly, learning, and picking up better development practices are no longer a daunting task.

The best way to learn any new language is to immerse yourself. Popular programming languages like Python are no different. The more time you interact with solving real-world problems with a new language, the faster you can become fluent. There are tons of resources like YouTube videos and blog posts, but I find that there really isn’t a better-suited way to learn than hands-on teaching. You need to raise your hand and ask an instructor attuned to the Python language, programming languages, Python code, data science, python developers, artificial intelligence, programming, and machine learning, and more.

General Assembly: the bridge to machine learning.

The immense rise of use cases and companies hiring developers, allows an increase in places to learn these new skills. General Assembly has a multitude of ways to get you started on the path to learning Python and becoming a Python developer. Informal and free introduction sessions at General Assembly aim to get you running code in just a couple of hours. Part-time classes take things up a notch by giving you focused hands-on lessons twice a week, over 10 weeks — artificial intelligence will have nothing on you. For those future Python developers that are ready to take the plunge, and want a deep-dive into all things machine learning, General Assembly also offers full-time Data Science Immersive programs every quarter to learn Python code, programming, nuances of artificial intelligence — and more.

Why is Python so popular? These reasons are a very good place to start!

Learn More About Our Python Offerings

Python: The Programming Language Everyone Needs to Learn

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What’s one thing that Bill Gates, Mark Zuckerberg, Sheryl Sandberg, will.i.am, Chris Bosh, Karlie Kloss, and I, a data science instructor at General Assembly, all have in common? We all think you should learn how to code.

There are countless reasons to learn how to code, even if you don’t want to become a full-time programmer:

  • Programming teaches you amazing problem-solving skills.
  • You’ll be better able to collaborate with engineers and developers if you can “speak their language.”
  • It enables you to help build the technologies of the future, including web applications, machine learning models, chatbots, and anything else you can imagine.

To most people, learning to program — or even choosing what language to learn — seems daunting. I’ll make it simple: Python is an excellent place to start.

Python is an immensely popular programming language commonly used by data analystsdata scientists, and software engineers. In addition to being one of the most popular — it’s used by companies like Google, SpaceX, and Instagram to do a huge variety different things including data cleaning, build AI models, building web apps, and more — Python stands out for being very simple to read and write, while offering extreme flexibility and having an active community.

Here’s a cool example of just how simple Python is: Here is code that tells the computer to print the words “Hello World”:

In Python:

print ("Hello World")

Yup, that’s really all it takes! For context, let’s compare that to another popular programming language, Java, which has a steeper learning curve (though is still a highly desirable skill set in the job market).

public class HelloWorld {   public static void main(String[] args) {      System.out.println("Hello, World");   } }

Clearly, Python requires much less code.

Experiencing Python in Everyday Life

Let’s talk about some of the ways in which Python is used today, including automating a process, building the functionality of an application, or delving into machine learning.

Here are some fascinating examples of how Python is shaping the world we live in:

  • Hollywood special effects: Remember that summer blockbuster with the huge explosions? A lot of companies, including Lucasfilm’s Industrial Light & Magic (ILM), use Python to help program those awesome special effects. By using Python, companies like ILM have been able to develop standard toolkits that they can reuse across productions, while still retaining the flexibility to build custom effects in less time than ever before.
  • File-sharing applications: When Dropbox was created in 2007, it used Python to build the desktop applications and server infrastructure responsible for actually sharing the files. After more than a decade, Python is still powering the company’s desktop applications. In other words, Dropbox was able to write a single application for both Macs and PCs that still works after more than a decade!
  • Web applications: Python is used to run various parts of some of today’s most popular websites, including Pinterest, Instagram, Spotify, and YouTube. In fact, Pinterest has used Python in some form since it was founded (e.g., to power its web app, build and maintain data pipelines, and perform analyses).
  • Artificial intelligence: Python is especially popular in the artificial intelligence community, again for its ease of use and flexibility. For example, in just a few hours, a business could build a basic chatbot that answers some of the most common questions from its customers. To do this, programmers could use Python to scrape the contents of all of the email exchanges with the company’s customers, identify common themes in these exchanges with visualizations, and then build a predictive model that can be used by the chatbot application to give appropriate responses.

Python at General Assembly

General Assembly focuses on building practical experience when learning new technical skills. We want students to walk away from our data science courses and bootcamps equipped to tackle the challenges they’re facing in their own lives and careers.

Python at General Assembly section, change the second graf to:

Many of our courses are designed to teach folks with limited exposure to Python to use it to answer real business questions. Dive into fundamental concepts and techniques, and build your own custom web or data application in our part-time Python Programming course. Or learn to leverage the language as part of our full-time Data Science Immersive program, part-time Data Science course, or a one-day Python bootcamp. Projects students have tackled include visualizing SAT scores from across the country, scraping data from public websites, identifying causes of airplane delays, and predicting Netflix ratings based on viewer sentiment and information from IMDB.

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Meet Our Expert

Michael Larner is a passionate leader in the analytics space who specializes in using techniques like predictive modeling and machine learning to deliver data-driven impact. A Los Angeles native, he has spent the last decade consulting with hundreds of clients, including 50-plus Fortune 500 companies, to answer some of their most challenging business questions. Additionally, Michael empowers others to become successful analysts by leading trainings and workshops for corporate clients and universities, including General Assembly’s part-time Data Analytics course and SQL/Excel workshops in Los Angeles.

“GA provides an amazing community of colleagues, peers, and fellow learners that serve as a wonderful resource as you continue to build your career. GA exposes students to real-world analyses to gain practical experience.”

Michael Larner, Data Analytics Instructor, General Assembly Los Angeles

The Skills and Tools Every Data Scientist Must Master

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women of color in tech

Photo by WOC in Tech.

“Data scientist” is one of today’s hottest jobs.

In fact, Glassdoor calls it the best job of 2017, with a median base salary of $110,000. This fact shouldn’t be big news. In 2011, McKinsey predicted there would be a shortage of 1.5 million managers and analysts “with the know-how to use the analysis of big data to make effective decisions.” Today, there are more than 38,000 data scientist positions listed on Glassdoor.com.

It makes perfect sense that this job is both new and popular, since every move you make online is actively creating data somewhere for something. Someone has to make sense of that data and discover trends in the data to see if the data is useful. That is the job of the data scientist. But how does the data scientist go about the job? Here are the three skills and three tools that every data scientist should master.

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