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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!

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Three Big Reasons Why You Should Learn Python

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As a data scientist, my work is contingent on knowing and using Python. What I like about Python, and why I rely on it so much, is that it’s simple to read and understand, and it’s versatile. From cleaning, querying, and analyzing data, to developing models and visualizing results, I conduct all these activities using Python. 

I also teach data science in Python. My students learn Python to build machine learning models but I’m always excited to hear of the other ways they’ve leveraged the programming language. One of my students told me they used it to web-scrape online basketball statistics just so they could analyze the data to win an argument with friends. Another student decided to expand on her knowledge of Python by learning Django, a popular framework, which she uses to build web apps for small businesses. 

Before taking the plunge into data science, we all had fundamental questions (and concerns) about learning Python. If this sounds like you, don’t worry. Before I started learning Python, I spent several months convincing myself to start. Now that I’ve learned, my only regret was not starting sooner.

If you’re interested in learning Python, I want to share my biggest reasons for why you should. Two of these reasons are inherent to Python; one of them is a benefit of Python that I experienced first-hand, and some of the examples I discuss come from things I have researched. My goal is to give you enough information to help make an educated decision about learning Python, and I really hope that you choose to learn.

1. Python is easy to learn. 

Long before I learned Python, I struggled to learn another object-oriented programming language in high school: Java. From that experience, I realized that there’s a difference between learning to program, and learning a programming language. I felt like I was learning to program, but what made Java difficult to learn was how verbose it was: the syntax was difficult for me to memorize, and it requires a lot of code to be able to do anything.

Comparatively, Python was much easier to learn and is much simpler to code. Python is known as a readable programming language; its syntax was designed to be interpretable and concise, and has inspired many other coding languages. This bodes well for first-timers and those who are new to programming. And, since it typically requires fewer lines of code to perform the same operation in Python than in other languages, it’s much faster to write and complete scripts. In the long run, this saves developers time, which can then be used to further improve their Python. 

One observation I’ve made of Python is that it’s always improving. There have been noticeably more updates to the language in the last 5-10 years than in prior decades, and the updates have often been significant. For example, later versions of Python 3 typically benchmark faster completion times on common tasks than when carried out in Python 2. Every release in Python 3 has come with more built-in functions, meaning “base” Python is becoming more and more capable and versatile.

Learning is not an individual process; often you will end up learning a lot from “peers.” According to various sources, Python has one of the largest and most active online communities of learners and practitioners. It’s the most popular programming language to learn; it’s one of the most popular programming languages for current developers; and among data scientists, it’s the second most common language known and used. All of this translates into thousands of online posts, articles (like this one!), and resources to help you learn.

Speaking of online learning, Python is also tremendously convenient to learn. To learn the fundamentals of Python, there are a lot of learning tools out there — books, online tutorials, videos, bootcamps — I’ve tried them all. They each have their merits but ultimately having options makes it easier to learn. Once you start learning, the resources don’t stop. There are dozens of really good tutorials, code visualizers, infographics, podcasts, and even apps. With all of these resources at your disposal, there’s really no reason why you can’t learn!

2. Python is versatile.

Python’s popularity is also tied to its usability and versatility. According to O’Reilly, the technology and business training company, the most common use cases for python are data science, data analysis, and software engineering. Other use cases for Python include statistical computing, data visualization, web development, machine learning, deep learning, artificial intelligence, web scraping, data engineering, game and mobile app development, process automation, and IoT. 

To get into any of these use cases would require another post. Regardless, you might be wondering what allows Python to be such a versatile programming language? A lot of it has to do with the various frameworks and libraries that have been built for Python. 

Libraries are collections of functions and methods (reusable and executable code) with specific intents; and frameworks more or less are collections of libraries. If you ask any Python developer, they can name at least a half-dozen libraries they use. For example, I often use NumPy, Pandas, and Scikit-learn — the holy trinity for data scientists — to perform math and scientific operations, manipulate and analyze data, and build and train models, respectively. Many Python-based web developers will name Django as one of their preferred frameworks for building web applications.  

While it’s true that libraries are written for most programming languages and not just Python, Python’s usability, readability, and popularity encourage the development of more libraries, which in turn makes Python even more popular and user-friendly for existing developers and newcomers. When you learn Python, you won’t just be learning base Python, you’ll be learning to use at least a library or two.

3. Python developers are in demand.

Many people learn to program to enhance their current capability; others to change their careers. I started off as one of the former but became the latter. Before data science, I built digital ad campaigns and a lot of my work was automatable. My only problem was that I didn’t know how to code. Although I eventually learned how, in the process of learning Python for my work, I was presented with different job opportunities where I could use Python, and learned about different companies who were looking for people experienced in Python. And so I made a switch.

There are a lot of Python-related roles in prominent industries. According to ActiveState, the industries with the most need for Python are insurance, retail banking, aerospace, finance, business services, hardware, healthcare, consulting services, info-tech (think: Google), and software development. From my own experience, I would add media, marketing, and advertising to that list.

Why so many? As these industries modernized, companies within them have been collecting and using data at an increasing rate. Their data needs have become more varied and sophisticated, and in turn, their need for people capable of managing, analyzing, and operationalizing data has increased. In the future, there will be very few roles that won’t be engaged in data, which is why learning Python now is more important than ever — it’s one way to bullet-proof your career and your job prospects.

A lot of top tech companies value Python programmers. For instance, to say that Google “uses” Python is an understatement. Among Google engineers, It’s a commonly used language for development and research, and Google’s even released their own Python style guide. Google engineers have developed several libraries for the benefit of the Python community including Tensorflow, a popular open-source machine learning library. YouTube uses Python to administer video, access data, and in various other ways. Python’s creator Guido van Rossum, a Dutch programmer, was hired by Google to improve their QA protocols. And most importantly, the organization continues to recruit and hire more people skilled in Python. Other notable tech companies who frequently hire for Python talent include Dropbox, Quora, Mozilla, Hewlett-Packard, Qualcomm, IBM, and Cisco. 

Lastly, with demand often comes reward. Companies looking to hire people skilled in Python often pay top dollar or the promise of increased salary potential. 

Conclusion

In summary, there are lots of reasons to learn Python. It’s easy to learn, there are many ways to learn it, and once you do, there’s a lot you can do with it. From my experience, Python programming is a rewarding skill that can benefit you in your current role, and will certainly benefit you in future ones. Even if Python doesn’t end up being the last programming language you learn, it should certainly be your first.

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How Long It Takes to Learn Python

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Python, an essential programming language, has taken the programming world by storm. Much of this attention has followed from the interest in machine learning and AI. Python has become the default programming language of Data Scientists and Machine Learning Engineers all over the world. Python’s versatility has also gained a loyal following not just in computer science but also amongst diverse fields like Bioinformatics, Astronomy, Gaming, and of course, Data Science.

But utility alone doesn’t explain why so many developers love using Python. From its humble beginnings in 1991, Python was designed by Guido van Rossum to be a programming language that emphasized code readability. Or in Guido’s words, “Computer Programming for Everybody.” This ease of human interpretability pairs with an open source ethos that makes it available to developers everywhere for free! So with a few short lines of code you can import packages and libraries that professional developers from companies like Facebook, Google, or AirBnB have spent thousands of hours building _(for free)_.

It’s low-entry cost and ease of reading programs has rightfully garnered Python an immense and passionate following.

1. Where there is talent, there is an opportunity, especially, in Python programming.

Python has rapidly become a deep learning skill that is in high demand within the job market. Jobs sites like Dice and Glassdoor have seen near-exponential growth in postings looking for candidates with Python skills over the last few years because making pivot tables and wrangling data in spreadsheets is no longer enough to get you noticed for data analyst positions. As the variety, velocity, and volume of data has exploded, developers have had to scale their analysis pipelines to match — this means that the people pouring over those numbers must develop a deeper skill set to deal with the enormous amounts of data piling up in their databases.

2. Speed and flexibility are the names of the game!

Python is ideal for handling the heavy-lifting required for today’s computationally intense data analyses used by most businesses today.

OK, so now that you’re sold on its value, how long does it take to learn Python? Like any language, practice and muscle memory are the name of the programming language game. The more time you can immerse yourself, the quicker you will see gains.

It also depends on how much you intend to learn during this process. You can figure out elementary Python and have a simple “Hello World” program running in a matter of minutes, i.e., _Seriously; it is only one line of code!_, etc. To get an understanding of deep learning, a subset of machine learning, or data scientist techniques may take months of focused study, pushing past basic concepts. But, to get your foot in the door as a Data Analyst, it takes about 40–50 hours of studying and practicing — in my computer programming experience.

Some of the rudimentary skills from loading required packages, the underlying data structures, and some simple data manipulation take some effort to put into practice. Remember that learning anything takes motivation and attention, especially when learning a new programming language. With our focus being pulled in many directions at once, sometimes having some guided learning  as a programmer can be a huge help — especially with data analysis and data analysts.

How often have you had a problem you spent hours trying to solve by Googling every corner of the internet, only to have the solution explained to you in three seconds by an expert? You can have industry professionals help guide you through this exciting learning adventure to help make sure you are spending your effort in the right places rather than sift through all the YouTube videos, blogs, or StackOverflow posts.

3. General Assembly Python programming FTW!

Often you get back what you put in. So if you are thinking about getting started on your programming language journey of learning Python, General Assembly has several great ways to get you started.

Free Introduction to Python workshops are held regularly. The aim here is to get you set up to start learning and developing in a couple of hours.

There is a 10-week part-time Python course that give you all the programming language skills you need to start a new career as a Data Analyst or Python Developer for those that are ready for more structured and in-depth learning. These classes are held for two hours, twice a week, over 10 weeks.

For those who like to jump in and learn as much as possible in concentrated, full-time sessions every day, General Assembly offers a 13-week Data Science Immersive as well, which covers all the essentials of putting Python programming into good use for Machine Learning and Data Science.

4. Dive into Python programming + a Python course.

If you are on the fence about learning the programming language Python, I strongly suggest you dive in and don’t look back! I have found the transition from being a Data Analyst in a cancer research lab to becoming a Data Scientist at an InsureTech company, one of the best experiences of my life. All the nerdy things I loved, i.e.,  _(computers, stats, data visualization)_, all banded together in an amazing career path

How long does it take to learn the Python programming language? The answer is your learning path up to YOU. 

Are you ready to start your next chapter and boost your coding skills as a python programmer?

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Getting Started with Sublime Text 3: 25 Tips, Tricks, and Shortcuts

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Note: Sublime Text 4 has since been released and is available here.

Sublime Text 3 (ST3) is the former version of one of the most commonly used plain text editors by web developers, coders, and programmers. It is a source code editor that has a Python programming surface or API. It is able to support C++ and the Python programming language. Plus, functions can be added by any user with a plugin.

Make the most of ST3 with the 25 tips and tricks in this ultimate guide for web developers. Learn not only how to use Sublime Text 3, but also about must-have packages, useful keyboard shortcuts, and more.

1. User Preference Settings

By default, ST3 uses hard-tabs that are 4 characters long. This can result in hard-to-read code, as large tabular indents push your work to the right. I recommend all developers add this to their user settings (Sublime Text 3 => Preferences => Settings – User):

  {
    "draw_white_space": "all",
    "rulers": [80],
    "tab_size": 2,
    "translate_tabs_to_spaces": true
  }

This setting converts hard-tabs to spaces, makes indents only two characters long, puts a ruler at the 80 character mark (to remind you to keep your code concise), and adds white space markers. Here is a complete list of preference options if you wish to continue customizing your ST3 environment.
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7 Essential Skills You Need to be an Android Developer

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Android101_DripArt3

Building Android applications requires a deep understanding of programming and design. When approaching a new technology for the first time, it often helps to break it down into pieces. If you’re an experienced web developer, many of the concepts and technologies involved in Android app development will be analogous to things you already know – although building apps for mobile devices often requires mastery of a number of more nuanced concepts. Mobile devices have smaller screens, simpler processors, and – in the case of Android – many different manufacturers, meaning that developers need to keep code flexible and account for various user interface scenarios.

So what does it take to become an Android developer? We asked some of the brightest developers in our community – here’s what you need to know.

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5 Reasons You Should Learn to Code

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learning to code

Why learn to code? There’s no denying that full-stack web development is one of today’s most sought-after careers. With a median salary of more than $75,000 and demand expected to grow 27% from 2014-2024, according to the U.S. Bureau of Labor Statistics, full-stack web development is a smart career path for many individuals.

But even if you’re not planning on becoming a full-time programmer or coder, learning how to code and having that kind of knowledge and experience can have substantial benefits for your career and further job opportunities. In today’s competitive job market, the smartest workers are those who are able to leverage technology to their advantage — no matter their job title.

Not sure if you want to tackle the challenge? Here are five reasons and benefits of learning to code that will add serious value to your career.

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What Is Front-End Web Development?

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Advanced-Front-End-Web-Development

Name: Nick Schaden (@nschaden)
Occupation: Web Designer/Developer

1. In 140 characters or less, what is front-end web development, from your experience?

A mix of programming and layout that powers the visuals, interactions, and usability of the web.

2. If a website were a house, front-end web development would be ______?

Front end development would be the pretty exterior that gives the house character, or the host that invites guests in and makes them feel at home.

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HTML for Web Development: Building the Bones of Your Website

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Hypertext Markup Language, or HTML, is a programming language used to describe the structure of information on a webpage. Together, HTML, CSS, and JavaScript make up the essential building blocks of websites worldwide, with CSS controlling a page’s appearance and JavaScript programming its functionality. You can think of the HTML document as providing the bones of a webpage, while CSS provides the skin, and JavaScript provides the brains.

A webpage can contain headings, paragraphs, images, videos, and many other types of data. Front-end developers use the HTML element to specify what kind of information each item on a webpage contains — for instance, the “p” HTML element indicates a paragraph. Developers also write HTML language code to specify how different items relate to one another in the page’s overall structure or document structure.

Every website you open in your web browser, from social networks to music services, uses HTML. A look under the hood of any website would reveal a basic HTML code page, written with an HTML structure editor, providing structure for all the page’s components, including its header element, footer element, main content, and other inline elements.

A look at the HTML code that structures General Assembly’s website.
A look at the HTML code that structures General Assembly’s website.

How HTML Works in a Webpage

The HTML file plays a couple of significant roles in a webpage. First, we use the structure created by our HTML code to reference, enhance, and manipulate elements on a web page using CSS and JavaScript. For instance, you could use HTML to mark all of the headings on a web browser page, then pick the size and color you want to apply to those headings to reflect your organization’s branding, or simply a visual design developed for the site.
Second, HTML text lets us indicate the roles of different structural elements to search engines and other services that index the content and summarize it for other users. For instance, marking the caption of an image with the “figcaption” element and enclosing the image and its caption in the “figure” meta element helps a search engine understand that these two pieces of content are related and that the caption describes the associated image.

Learning HTML at General Assembly

Whether you want to land a job as a front-end or full-stack web developer or just want to dip your toe into programming, HTML is a natural place to start. Learning HTML, along with CSS and basic JavaScript, provides you with the fundamental skills necessary to create your interactive single-page website.

In GA’s part-time courses in Front-End Web Development and HTML, CSS & Web Design, and our career-changing, full-time Web Development Immersive program, you’ll get hands-on practice coding your projects, from static personal and business websites to single-page applications like games and interactive photo galleries.

These projects give you practice using basic HTML tags and structuring pages with different components, including headers, footers, sidebars, and navigation. You’ll also code CSS and JavaScript and learn how to put all three together to build websites that implement modern standards and use best practices for front-end development.

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Meet Our Expert

Sasha Vodnik is a front-end web developer and author who teaches Front-End Web Development and JavaScript Development at General Assembly’s San Francisco campus. He also writes books on HTML, CSS, and JavaScript and creates video courses through Lynda.com.

“I love meeting students from a wide variety of industries, with a whole spectrum of goals, from all over the world. I’m continually inspired by the thoughtful, creative projects they build in the course that showcase their new skills and unique vision.”

– Sasha Vodnik, Front-End Web Development Instructor, General Assembly San Francisco

Preparing for an Immersive Coding Program? Don’t Stop at the Pre-Work.

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Over the years, we’ve spent a lot of time thinking about the onboarding experience for students entering our Software Engineering Immersive (SEI) program. SEI is a 12-week, full-time program that gives people the foundation and skills needed to become full-stack web developer.

From 9 am to 9 pm on weekdays, and all day Saturdays and Sundays, students are immersed in code. Because the program is so intense and the learning curve so steep, we, along with other coding immersives (also known as “bootcamps”), advise students to start preparing before they arrive on day one.

Pretty standard is the concept of “pre-work”: 50-100 hours of readings, tutorials, and exercises designed to give everyone a foundation in basic web development concepts, as well as level set the class. At GA, students cover Git, HTML, CSS, and Ruby before starting SEI.

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Learning to Code? 4 Reasons You Should Learn JavaScript First

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Browse any number of job postings for web developersfront-end, back-end, full-stack; it doesn’t matter — and every single job will require different expertise. From Adobe Creative Suite to Zero Day Exploits, you could spend an entire career attempting to become the ideal developer to meet any one of these job’s multiple requirements.

Or you could learn JavaScript instead. Continue reading