Are you thinking about working in software development? The tech industry continues to move toward greater dominance in every industry, and every part of the job market. There has never been a better time to launch a career in software development. Developers working in data science, artificial intelligence, and IoT applications are especially in demand, and Python is the preferred language for these types of projects.
If you’re like most people just starting out in an IT career path, you might find the learning curve a bit overwhelming. What areas of tech are most suited to your talents? What programming languages should you invest your time in learning? Where do you even begin in gaining the knowledge necessary to be successful? This guide on how to become a Python developer offers an answer to all of these questions.
Python programming is increasingly important in the software development industry today, and python developers can look forward to an exciting and lucrative career in the tech industry.
Ready to get started? Read on for a step-by-step guide to beginning your new career as a Python developer.
Understand what Python is
Python is a popular high-level programming language that can be implemented across a broad range of platforms. Python’s suitability for use in complex mathematical applications, data handling, and search functions make it a preferred language for artificial intelligence and IoT (Internet of Things) applications.
Python is used in many enterprise level environments where large scale data handling is important. According to this Wikipedia article (link to the article on Wikipedia), for example, the massive social news site Reddit is programmed entirely in Python.
With social networking, AI, and data science dominating the tech world these days, it’s easy to see why Python is so popular. Keep reading to see how you can learn this versatile and easy to use language in your career.
Learn what you can do with Python
Because it is an extensible programming language, there is virtually no limit to the types of applications that a Python programmer can build. That said, there are certain areas where Python programmers are in particularly high demand. The most popular uses of Python today revolve around complex mathematical computation, data science applications, and artificial intelligence. The following are a few of the many industries specializations where you can put your Python programming skills to use.
The range of things that can be accomplished using large scale data acquisition and analysis is seemingly limitless. From precision targeted marketing campaigns to adaptive healthcare applications to the construction and training of AI and neural networks, big data is the future of almost every industry you can think of.
Big data is big. Really big. We’re talking petabytes (1 billion megabytes) and exabytes (1 trillion megabytes) big. At this enormous scale, you need some seriously efficient methods for doing anything with all that data. In big data applications, the structure and even purpose of the data collection may not be known at the outset. The massive data acquisition carried out by companies like, for example, Google and Facebook are often akin to strip-mining: the data is raked in wholesale with little or no regard to its structure or type, and then sorting and processing algorithms are applied to organize it.
Python is a programming language that is particularly well-suited to handling unstructured data in a flexible and efficient way, and so it is the language of choice for organizing the data collected in this fashion.
Once you get all that data organized and stored safely in your database, you need to figure out what to do with it. This is where data science comes in.
Data scientists are tasked with searching for patterns in large sets of data and finding meaning in those patterns. This is a huge and rapidly developing task that often requires mid-project shifts in thinking about the very nature of the task at hand. As new and unexpected patterns emerge from the data, new methods must be employed to work with those patterns.
Python’s active user community, easy extensibility, and simple syntax make it ideal for such a rapidly evolving environment. In Python it is relatively easy to create and integrate new libraries to handle emerging opportunities.
IoT (Internet of things)
Talking about big data and data science in the abstract gives you an idea of the kind of inspiring, big picture achievements you can look forward to as a Python developer. But what about real world, tangible applications? How can you actually make some money with Python programming?
One of the big money makers in Python programming is the development of IoT applications.
The Internet of Things (IoT) describes a data network made up of all kinds of devices including cell phones, televisions, cars, and even your microwave oven. IoT promises to someday free internet-based communication from the tethers of cables, switching stations and all the other heavy infrastructure that currently makes the internet work. The IoT concept also allows for automation of pretty much every object on the planet.
Handling the traffic on IoT networks is a task that requires handling a large amount of unstructured data, which is what Python does best. Systems flexible enough to operate on a completely de-centralized network will be the bread and butter of software developers as IoT grows. Python programming will likely be the backbone of those flexible systems.
As the world moves toward a full implementation of IoT technologies, Python plays an increasingly significant role in IoT implementations. Already, we can see many examples of big industry shifting to an IoT mentality, and making big bucks because of it.
Smart Home Devices
You might have heard of a little device called Alexa. In just a few years, Alexa has grown from a limited deployment of Amazon Echo devices to a global platform with over 100 million Alexa-enabled devices in use today.
Alexa is a perfect example of smart home applications for the IoT concept. Smart home technologies include context-aware lighting, stereos that automatically select music to suit your mood, refrigerators that alert you when you’re running low on ketchup… The list goes on.
Home automation systems are big business, and AI systems like Alexa serve as their central nervous system. Python developers will be increasingly in demand to develop new integrations for these systems, and to use data science to make sense of all the data being collected through their use.
Healthcare is one of the fastest growing industries today, and medical technology is at the forefront of innovation. IoT applications in medicine offer the possibility of automated home care, AI-driven robotic surgeries, and many other innovations that will make healthcare more affordable and effective.
According to the Bureau of Labor Statistics (https://www.bls.gov/ooh/healthcare/home.htm), the healthcare industry is projected to add 1.9 million jobs in the next 10 years. That’s a labor force increase of 14%. As the average age of the U.S. population increases, more patients will be entering the healthcare system, and the demand for efficient and responsive automation in medicine will continue to grow.
Self-driving cars, fully automated commuter rail networks, driverless bus systems, and air traffic control managed by AI. These are all made possible by IoT technology.
When you put computers in charge of something as potentially dangerous as a fast-driving car, you want to be sure that the network that supports it is robust. Ubiquitous IoT devices make a wireless network with zero dead zones possible. Integrating transportation systems with other devices on an IoT network also allows better adaptability and situational awareness for the vehicles, which leads to higher efficiency meaning less traffic congestion and pollution.
Handling the complex data management of traffic flow and load monitoring via IoT is a task that Python is extremely well-suited to handle.
Imagine a manufacturing plant with no workers. Material handling, assembly, and testing is all handled by robots without a single human touching the system. An AI driven factory with its components integrated via IoT can achieve this.
Automated manufacturing is on the rise, and IoT is an integral part of making it work. By enabling machines to communicate with one another and respond automatically to changes, manufacturing facilities are able to dramatically increase efficiency, reduce labor costs, and prevent errors. Integrating such an IoT network into a central management system might allow a factory to achieve near perfect efficiency by applying AI and machine learning techniques to improve the interaction of the different components of the factory.
As cost of labor increases around the world, demand for made things is increasing as well. Automated manufacturing will, therefore, continue to be a growing industry demanding Python-savvy IoT developers to create new and better integration systems.
Okay, is all this talk about AI and big data blowing your mind? There are more pragmatic uses for your Python programming skills that can still lead to a comfortable and reliable paycheck. One of these is development of server-side applications for the web.
Python is a great language for developing server-side applications because of its simple syntax, which makes it easy to learn for whoever might need to make changes to a web application through its whole life-cycle. Python also enjoys a number of great web frameworks that can be used to easily develop clean, well-documented applications.
When you begin developing large applications, especially in team development environments, testing becomes an essential step of the application development process. There are extensive testing resources available within Python’s standard library, and even more from the large community of Python developers.
Testing is a big part of working as a developer no matter what language you’re working in, and web testing is a viable career path all on its own. Python’s automated testing resources are invaluable when you start developing enterprise scale applications.
Be Prepared: What Do You Need to Know Before Learning Python
You might be thinking, “Motivation is a quality, not a skill.” In fact, staying motivated is one of the biggest challenges as you learn a new language. Self-motivation is very much a learnable skill, and there are countless philosophies and methodologies designed to help you get and stay motivated.
The most important thing as you begin your journey to becoming a Python developer is a clear understanding of your goals and expectations. Reading through the examples above of how you can use Python might help you think about your goals. Ultimately, though, your path is your own, and the sky’s the limit.
Understanding of Basic Mathematics Helps
So, now that you’re motivated, what do you really need to know before you start learning Python? Not much, really. If you can read and write, have access to a computer, and understand basic arithmetic, you have the fundamental skills needed to work in Python.
Of course, Python developers typically work on projects that require deep understanding of math, logic, and information theory. So, while learning the actual language has no specific prerequisites, actually using it to solve problems might require further learning.
Having a solid foundation in mathematics including linear algebra and calculus will give you an edge as a Python developer in areas of engineering and data science.
A Logical Mindset
Software development is all about managing and organizing information. If you have a knack for organization, and you easily recognize patterns in information, then it’s just a matter of applying this mentality in a formalized way within your Python applications.
If you are not naturally gifted with logic, don’t worry. Most people struggle at first with complex logical reasoning, but it is a learnable skill just like any other. Consider taking an online course in logic, critical thinking, or information theory.
Learn to Code in Python
When learning anything new, especially something as complex as a new language, it is helpful to begin by creating a plan. Writing down a plan outlining a step-by-step path to learning Python will help you stay on track through the whole process. Your plan will serve as a reference to look at when you inevitably encounter challenges or feel like you’re not making progress. Use your plan to help identify major milestones and organize your strategy for gaining the knowledge and skills necessary to become a professional Python developer.
Where to Find Python Programming Courses
Okay, so you have your learning plan all figured out. Now, where do you go to do the actual learning? There are, of course, traditional avenues (like universities and coding bootcamps) for learning to code in Python. Unless you have a large amount of free time and some serious cash to burn, though, you probably aren’t looking forward to spending months or years in school to learn what you need to become a Python developer.
In terms of mechanics and syntax, Python is very simple and easy to learn. There are a number of great online options for learning to code in Python. Some of these will even take you through more advanced topics like multithreading and meta classes. Explore the offerings on these online learning outlets and you’ll be sure to find a course that fits your specific interest, learning style, and schedule.
Online courses on Udemy (link to the Udemy Review article)
Udemy is an online learning marketplace where anyone can submit a course for consideration to be offered on the platform. Offerings range from simple topic overviews to multi-week professional certification courses. The bulk of each class is a series of video lectures. The videos are supplemented by interactive quizzes and downloadable resources. The completely on-demand format of Udemy’s courses makes it super easy to study for a new topic while keeping your current job, or going to school.
Coursera (link to the Coursera Review article)
Coursera is an online learning platform developed by former Stanford University professors. It provides courses both in a classic scheduled format, and on-demand. Courses typically last 4-10 weeks and are taught by industry leading professionals and professors from accredited universities.
Coursera offers several different learning formats, including:
- Single courses
- Professional certifications
- Specialization programs
- Online degrees
Pluralsight (link to the Pluralsight Review article)
Pluralsight is an online training platform geared toward technology professionals. Its offerings are developed and delivered by industry professionals, and include a wide variety of courses. If you’re already a working IT professional, Pluralsight is a great option to learn a new technology fast without having to wade through the basic stuff. They provide some skill assessment functionality, as well, so you can advertise your newfound competency to potential employers.
Essential Knowledge to Begin a Career as a Python Developer
There are some basic principles that are common across all programming languages, and it is a good idea to begin your learning process by getting a solid grounding in these basic concepts. If you already understand, for example, what a function is, how variables work, and other basics of programming, your Python learning process will be that much easier.
Begin with Fundamentals of the Python Language
Before you can develop a bleeding edge AI application and change the world forever, you’ll need to understand some basic elements of Python syntax and functionality.
Gaining a deep understanding of these topics should prepare you for an entry-level position in Python programming:
- How to install and use Python
- Basics of variables and data types
- Lists, ranges and tuples in Python
- Python dictionaries and sets
- Controlling input and output (I/O)
- Modules and functions in Python
- Using Python as an object oriented programming language
Dig Deep Into Software Development Using Python
Once you have a solid understanding of basic syntax and you’re comfortable using Python to complete a wide array of computational tasks, it’s time to learn how to actually build a piece of software in the language.
Intermediate courses in Python programming should take you through the use of packages for integrating other coders’ work into your own. It is extremely rare for an application to be developed entirely in isolation, so knowing how to access and use packages is a critical piece of knowledge for any professional Python developer.
You’ll also need to know how to use virtual environments. A virtual environment is a tool used to manage the functionality of different pieces of code as you integrate multiple developers’ work into a single application. Virtual environments are ubiquitous in software development, and knowing how to use them is a fundamental requirement for Python developers.
Along with your exploration of virtual environments and packages, this will be a great time to develop a deep knowledge of coding best practices and standard methodologies of team development. When you begin working with a development team, your ability to effectively collaborate and keep your work organized is almost as important as your coding knowledge.
Learn to Apply Your Knowledge in Real-World Applications
Once you’re totally comfortable with the mechanics of the language, your next step in becoming a Python developer is to be comfortable with full stack development. A full stack developer is one who has the diverse knowledge and skill to be comfortable building a software application from the ground up. If you’re a “full stack developer” you can start with a blank screen and create an entire software solution including front-end and back-end components, user interfaces, database design and implementation, and anything else required to make your application functional and usable.
Becoming a full stack developer will mean learning more than just how to use Python as a language. You’ll need to gain a solid understanding of information theory, database engineering, and other advanced topics.
Learning these advanced subjects will make you a valuable asset in any enterprise development scenario.
Essential Libraries and Kits for Python Developers
These are just a few of the vast array of libraries used in Python development. Learning to access and use libraries in your Python development projects is a foundational requirement in learning to become a Python developer.
NumPy is a Python library that provides support for handling large multi-dimensional arrays and matrices. It includes a large number of high-level mathematical functions that are used in many other, more specific libraries like the ones listed below.
This library features a variety of important functions for machine learning applications. It includes data clustering, classification and regression algorithms. Scikit-learning is based on NumPy and provides high-performance linear algebra operations and array handling.
TensorFlow is a symbolic math library developed for Python by Google. TensorFlow provides functions that support differentiable and dataflow programming paradigms. This library is useful in machine learning applications such as the construction of neural networks.
Another machine learning library, PyTorch focuses on natural language processing and computer vision. PyTorch is free and opensource, but its development has largely been driven by the Facebook AI Research lab. PyTorch is widely used in deep learning applications.
Develop Your Soft Skills
Learning to code is, obviously, an important step in your journey to become a Python developer, but coding knowledge is only valuable if you can use it in a real-world environment. Gaining a solid understanding of techniques and protocol for coding as part of a team is extremely important if you want to be a successful developer.
No amount of studying will make you an expert at teamwork. You need real-life experience to master the interpersonal communication skills necessary to function in harmony with a group of other coders. That said, it doesn’t hurt to get an overview of the existing project management frameworks in which most software development companies operate.
Project Management Basics
As you begin your career in software development, it will be extremely helpful to become familiar with current project management methodologies. Even if you don’t work in the corporate world you’ve probably heard something about Agile. This project management methodology is designed to make the management of large teams more easily organized and allow rapid development of big projects.
Agile is by the far the biggest buzzword in project management these days. More a top level category of project management strategies than a single approach, Agile project management enables software development teams to launch products more quickly than traditional methods. It’s based on self-organizing, cross-functional teams that contribute to the project in parallel. There are many different approaches to Agile development, but they all have in common this parallel, self-organizing, and collaborative core.
Taking an introductory course in Agile development is a great way to boost your value in the eyes of a hiring manager.
Are You Ready to Launch Your Career as a Python Developer
If you’re excited by the idea of learning a versatile language like Python, and you’re ready to work on exciting projects like IoT devices, artificial intelligence, and data science, then you are on the path to a lucrative and fulfilling career.
Big data companies, scientific research labs, IoT startups, and web development firms alike are all actively hiring for Python programming specialists. By using the information in this guide, you can become a valuable asset to any organization that’s working on complex data problems or artificial intelligence applications. As you learn Python, you will unlock virtually unlimited possibilities in manipulating complex data structures.