Software impacts nearly all aspects of our lives today. If you woke up to an alarm on your mobile phone, ordered lunch via an app, or used technology to get your work done today, you can thank software developers. If you’re interested in improving your problem-solving and analytical skills to help solve challenges (whether that’s how lunch gets ordered or something bigger, like climate change), software engineering could be the next career for you.
If you are wondering how to land a software engineering job with no experience, you’ve come to the right place. At General Assembly, we help thousands of people change careers and get entry-level jobs in software engineering in months. No four-year computer science degree required. This quick start guide outlines five steps to take to launch your new career in software engineering, regardless of your background.
The tech industry is booming, and the demand for programmers is increasing every year. There are 26.9 million software developers globally, according to a recent Global Developer Population and Demographic Study. This number is projected to increase to 27.7 million in 2023 and 28.7 million in 2024.
The world is moving fast, and there are many job openings for coders in 2023. There are many reasons why coding powers the world. The main use cases of coding include software development, data analytics, data science, web development, mobile app development and big data.
If you want to get involved in this exciting field, it’s essential that you learn how to code. But with so many different programming languages out there, where should you start? This blog will look at the top five coding languages that are most widely used today and why they’re so important.
The tech industry experienced mass layoffs and budget cuts in 2022 that have many tech workers who were once flying high worried about job security. Despite the gloomy news, however, the labor market for tech talent continues to be strong. While big tech firms are making headlines for drastic cuts, tech talent remains in high demand across other industries.
For example, industries like finance, healthcare, government and automotive, all of which have yet to fully digitally transform, are hiring tech talent. The City of San Francisco—a verifiable tech hub that should, in theory, have unlimited access to tech talent—recently shared that its vacancy rate for IT workers is 21%.
For workers willing to look beyond big tech, well paid opportunities continue to abound. At General Assembly, we help people break into a career in tech so they can increase their wages and land a job with great benefits and working conditions—ultimately, improving their quality of life.
Despite today’s economic landscape, we still believe this is a path to prosperity and that opportunities abound for tech workers. In fact, not having a technical skill set could leave you less secure in your career going forward as everything goes digital.
Entrepreneurship is on the rise. The pandemic led to a startup boom in the United States, with applications for new businesses increasing by 24%. Then, The Great Resignation accelerated the trend, with applications increasing 55% from 2019 levels in 2021.
If you’re thinking about jumping on the entrepreneurship train, learning to code might not be the first thing that comes to mind. After all, computer science isn’t typically found in a business school curriculum.
However, aspiring entrepreneurs should consider learning to code for a few reasons. Learning to code can help you launch your business faster, make better technology decisions, improve your creative problem solving skills, and better understand how your business operates.
Are you thinking about a career in tech? If so, consider learning how to code. With the mass adoption of the digital era across all industries, businesses big and small are on the lookout for tech-savvy talent.
According to Forrester’s recent report, the global tech market will experience robust 6% growth in 2023 (significantly faster than pre-pandemic levels). With the tech industry thriving and companies hiring, consider learning in-demand hard skills like coding.
Software engineering is one of the fastest growing and highly paid careers, which means many people are vying for a position. Luckily, there’s more than one path to success.
At its core, software engineering is problem solving. While technical skills are important, technology is always changing. Even seasoned professionals are constantly learning how to do something new. As a result, software engineers come from many backgrounds. Some opt for the traditional route, majoring in computer science in college, while others switch mid-career.
We sat down with two engineers who work on the development team at our partner, Anaconda, Inc., to learn more about their individual journeys. Ken Odegard took the more traditional, academic route, while Bianca Henderson is self-taught and transitioned to software development later in her career.
Do you want to be a data scientist? Data Science and machine learning are rapidly becoming a vital discipline for all types of businesses. An ability to extract insight and meaning from a large pile of data is a skill set worth its weight in gold. Due to its versatility and ease of use, Python programming has become the programming language of choice for data scientists.
In this Python crash course, we will walk you through a couple of examples using two of the most-used data types: the list and the Pandas DataFrame. The list is self-explanatory; it’s a collection of values set in a one-dimensional array. A Pandas DataFrame is just like a tabular spreadsheet, it has data laid out in columns and rows.
Let’s take a look at a few neat things we can do with lists and DataFrames in Python! Get the PDF here.
BEGINNER’SPython Cheat Sheet
Let’s start this Python tutorial by creating lists. Create an empty list and use a for loop to append new values. What you need to do is:
#add two to each value my_list =  for x in range(1,11): my_list.append(x+2)
We can also do this in one step using list comprehension:
my_list = [x + 2 for x in range(1,11)]
Creating Lists with Conditionals
As above, we will create a list, but now we will only add 2 to the value if it is even.
#add two, but only if x is even my_list =  for x in range(1,11): if x % 2 == 0: my_list.append(x+2) else: my_list.append(x)
Using a list comp:
my_list = [x+2 if x % 2 == 0 else x \ for x in range(1,11)]
Selecting Elements and Basic Stats
Select elements by index.
#get the first/last element first_ele = my_list last_ele = my_list[-1]
Apply a custom function to every value in one of the DataFrame’s columns.
def fix_zipcode(x): ”’ make sure that zipcodes all have leading zeros ”’ return str(x).zfill(5) df[‘clean_zip’] = df[‘zip code’].apply(fix_zipcode)
Ready to take on the world of machine learning and data science? Now that you know what you can do with lists and DataFrames using Python language, check out our other Python beginner tutorials and learn about other important concepts of the Python programming language.
It’s possible to learn Pythonfast. How fast depends on what you’d like to accomplish with it and how much time you can allocate to study and practice Python on a regular basis. Before we dive in further, I’d like to establish some assumptions I’ve made about you and your reasons for reading this article:
You have little to no prior experience learning Python programming.
You have no Python programming background or coding experience.
First, I’ll address how quickly you should be able to learn Python. If you’re interested in learning the fundamentals of Python programming, it could take you as little as two weeks to learn, with routine practice.
If you’re interested in mastering Python in order to complete complex tasks or projects or spur a career change, then it’s going to take much longer. In this article, I’ll provide tips and resources geared toward helping you gain Python programming knowledge in a short timeframe.
If you’re wondering how much it’s going to cost to learn Python, the answer there is also, “it depends”. There is a large selection of free resources available online, not to mention the various books, courses, and platforms that have been published for beginners.
Another question you might have is, “how hard is it going to be to learn Python?” That also depends. If you have any experience programming in another language such as R, Java, or C++, it’ll probably be easier to learn Python fast than someone who hasn’t programmed before.
But learning a programming language like Python is similar to learning a natural language, and everyone’s done that before. You’ll start by memorizing basic vocabulary and learning the rules of the language. Over time, you’ll add new words to your repertoire and test out new ways to use them. Learning Python is no different.
By now you’re thinking, “Okay, this is great. I can learn Python fast, cheap, and easily. Just tell me what to read and point me on my way.” Not so fast. There’s a fourth thing you need to consider and that’s how to learn Python.
Research on learning has identified that not all people learn the same way. Some learn best by reading, while others learn best by seeing and hearing. Some people enjoy learning through games rather than courses or lectures. As you review the curated list of resources below, consider your own learning preferences as you evaluate options.
What do the most in-demand 2021 jobs and promising careers of the future have in common? Coding skills. At the same time, new applications of coding are making their way into existing roles, expanding job requirements in traditional fields like banking and marketing. Even for non-tech roles, coding skills are seen as a valuable bonus that can give job candidates an edge.
Our digital world buzzes with software code we use every day, from products and services in the form of websites to mobile applications to games and on and on.
Computer programmer, developer, engineer, analyst — these are just some of the titles rapidly populating the job boards of Fortune 500 companies, and coding skills are essential requirements in all of them. Arwa Lokhandwala, who teaches our popular Full-Stack Web Development course, breaks down the various titles and what they really mean.
“Most of these terms are used synonymously, but there is some slight difference between them. A computer programmer, for instance, includes anyone who uses a programming language to produce some digital output — this technically includes everyone who codes. A developer uses a wide array of technical abilities, from writing code and creating technical documentation to testing and debugging. An engineer, on the other hand, is a person who has a strong educational background in software engineering, computer science, and mathematics and can apply these concepts to solve or create digital solutions. Finally, the analyst’s main job is to analyze different metrics, understand data captured by these digital solutions, and derive useful insights from them that are beneficial for the business.”
Additional jobs for coding professionals include web designer, software engineer, and chief technology officer (CTO); myriad roles in the fields of web development, technical project management, and quality assurance; plus, almost every founder of a successful startup has a background in coding.
So, what does a typical career path look like? “You can either start out as a software engineer, software developer, or quality analyst. As you progress, you can become lead developer then either go towards becoming an engineering manager, solution architect or product manager,” Lokhandwala advises.
You don’t always have to make a big move to flex your coding muscles. Often newfound coding skills can help you to advance in your existing job. If you’re curious about how this may pertain to you, Lokhandwala suggests offering to solve a particular problem at your company that you think can be automated with coding and see how that affects your role. The next step would be to take a course in a programming language like Python or fast-track your career with a coding bootcamp like our Software Engineering Immersive. Whether you stay at your job or accept a better offer elsewhere, you’ll gain a distinct advantage in the job market and increase your earning potential.
The practical applications for coding language are vast and growing every day. From medical coding to building websites, freelance to full-time, the jobs that use hard coding skills are varied enough to fit every personality and lifestyle.
Lokhandwala sees many exciting new uses of coding on the horizon, all on the cutting edge of computer science. “Some of the most interesting are in the realms of augmented reality and virtual reality. Using artificial intelligence and machine learning to identify the early onset of diseases has huge implications.”
In this case, first, console.log(“1”) is executed, then setTimeout() is executed; after the specified delay (in this case, 0ms), the callback function is added to Message Queue. Now the main thread only picks up items from the message queue once the current execution is done. So, the main thread first evaluates the console.log(“3”) statement post. Then, it picks up the callback() from the Queue and executes the console.log(“2”) statement. Hence, the above output.
5. The Difference between arrow functions and regular functions?
Arrow functions are new ES6 syntax for defining functions. It looks like this:
const add = (a,b) => a+b
add(2,3) // 5
The main difference between the arrow function and the regular function is the value of this keyword.
In the case of arrow functions, the keyword assigns a value lexically. What this means is unlike regular functions, arrow functions never create their own execution context. They, by default, take the execution context of the enclosing function, aka, parent.
Here is another great article explaining this in-depth.