In its simplest form, Python is a high-level programming language that’s primarily used for app and web development. Python programming language is relatively simple, which makes it easy to learn as it needs a unique syntax that focuses on readability. Python code can be read and translated by developers much easily compared to other languages.
Python is an interpreted language that means the written code isn’t translated to a computer-readable format actually at runtime. On the other hand, most programming languages do it before the program is run. A large majority of web platforms and applications rely on Python programming language including YouTube, and Google’s search engine, among others.
For a successful career in data science, you are going to need to learn at least one programming language. Since two common languages are Python and R, a widespread question is “Which one should I learn? Python or R?” Historically, there has been a fairly even split between the two languages. While R was built with a focus on mathematics and statistics, Python is a much better choice when it comes to overall work due to its versatility.
What makes Python the preferred choice for data science?
To begin with, once you learn Python development, you would be able to transfer those Python skills more easily to other disciplines. Additionally, Python also comes with extensive support libraries. You’ll find that several high-use programming tasks have been already scripted into these libraries, which will reduce the length of code you need to write significantly, thus saving you a lot of time and effort.
Python has a comprehensive standard library which allows for easy programming of many common tasks in every step in the domain of data science without having to install additional libraries. Let’s examine what a typical data science project workflow may look like:
Step 1: Suppose you need to pull some specific data from your company database. You’ll write a query using Python and SQL to get what you need.
Step 2: To get the data ready for analysis, you’ll need to clean and sort it into a DataFrame (table) for which you’ll use the Pandas – an open-source Python library.
Step 3: You’ll typically use the Pandas and Matplotlib libraries to start data analysis, exploration, and visualization.
Step 4: Once you learn more about the data via data exploration, you can use the scikit-learn library to make a predictive model that forecasts potential outcomes for your company based on the data you’ve already pulled and analyzed.
In the final step, you’ll organize your model results and the final analysis into a suitable format, which you’ll need to share with your coworkers or team leaders.
Key reasons to learn Python programming
By reading till now, if you’re getting a feel that you should learn Python programming but aren’t confident enough to proceed, here’re some key reasons for which you should go ahead.
The biggest reason you should learn Python programming is that it’s a preferred language for data science. Apart from the libraries and frameworks offered by Python like NumPy, PyBrain etc, diversity is another reason why Python is becoming the preferred language for data science.
Python is able to handle a lot of hassles of data. Python also supports parallel computing where you can use it for Hadoop. There’re libraries present in this language for big data processing.
The emergence of machine learning in the recent years has made learning Python programming extremely crucial for those looking to work in this field. Python is the major programming language that makes it easy to play around machine learning.
This is the most important reason for beginners who want to learn Python programming. Essentially, everyone wants to start coding and programming with a language that comes with relatively easy syntax and rules. Python is simple, readable, and easy to set up.
Another great thing about Python is it’s not tied to one discipline only, unlike how R is for machine learning and data science only. Being proficient in Python programming means you can do many things – from creating web applications to performing data analysis to writing scripts to automate tasks and more.
Importance of community when it comes to learning something new simply cannot be overstated. If you ever encounter any problem related to Python, you can ask any of its thousands of communities and you’ll most likely get the answer.
If you’re just beginning your programming career, it’s always recommended to go for a growing programming language and this is where Python exactly fits in.
Developers proficient in Python programming are some of the highest paid ones, especially in the fields of data science and machine learning.
It’s also important to note that Python is an open source language, which means there’re people trying to improve it always, keeping it up to date with the present trends. So, it can be concluded that Python programming language is a complete solution for developers and its utility and importance will only grow in coming times.
Where can you learn Python programming?
Hopefully, by now, you’re convinced enough to learn Python programming. It’s time to check out the resources that you can use to learn it. Learning Python programming as a complete beginner may seem a little overwhelming.
Where should you learn it from? How do you know that you’re getting the best information possible? If these are the questions you’re thinking of right now, just keep on reading. Now, we’re going to discuss different avenues to learn Python programming and why attending a boot camp would be your best bet.
RESOURCES OTHER THAN A BOOTCAMP
There’re some books (both physical and digital), tools/utilities and courses that you can use to learn Python programming. All you need to do is some online research to find out both paid and free tutorials. Among free tutorials, Python.org comes with the official documentation of Python language. It helps both experienced programmers and beginners to learn about Python.
Apart from these, you can use a Python environment that runs in your web browser. With such an environment, there’s nothing to install and nothing to download; all you need to do is open your browser and start coding.
LEARNING PYTHON PROGRAMMING FROM A BOOTCAMP
Programming bootcamps are technical training programs that are usually 10 to 12 weeks in length and are ideal for learning the core elements of programming. You may wonder why a coding boot camp would be ideal for you to learn Python programming, especially when you’re just getting started.
Let’s have a look at the advantages of attending a coding boot camp.
It’s great for motivation
Coding isn’t easy and Python is no different. Like any subject, it generally starts off easy and then begins getting more complicated as you dive deeper, and that’s when aspirants begin to get discouraged and finally give up.
For many people looking to learn Python programming, it’s crucial to have a great support network that consists of like-minded people who share common passion and interests for what they’re learning. In reality, probably there’s no one better than your fellow boot camp participants who can motivate and encourage you to stay on track.
Most coding boot camps come with a duration of about 10 to 12 weeks. Compared to computer science courses and online courses that may take longer to complete, the curriculum of a coding boot camp focuses only on the relevant and important topics that participants would need to learn in order to develop apps on a professional level.
Their entire curriculum is strategically planned and eliminates any unnecessary requirement. In addition, instructors in these boot camps are generally coders themselves and highly experienced people who work in the particular field. It means everything they teach is up to date with the industry trend and highly relevant.
You get to learn better
While there’re lots of resources that can help you learn Python programming on your own, it can be an uphill task because of a huge amount of information available. When studying Python programming on your own, it’s quite easy to get confused, demotivated and overwhelmed. And if you’re unable to understand something or stuck somewhere, it can be difficult to figure things out on your own. Boot camps let you discuss the topics with fellow students and seek help from the instructors, if you need it.
Communities and networks play a crucial role in the development of any programmer. At coding boot camps, you get to meet a lot of different people coming from different backgrounds. If you are able to make right connections, it can help you get great opportunities.
One of the greatest obstacles to attending a full-time course to learn Python programming is having to give up your present employment. Coding boot camps often offer part-time programs to help participants uphold their responsibilities while learning to code.
You get to have a strong mentor
Having strong mentorship is one of the biggest contributors to the success of a student and this is something you cannot get by learning on your own. In boot camps, instructors take time to work with the students, answer emails after hours, and explain questions to the students. This type of access to high-quality instructors plays a huge role in your success.
Job search preparation
Another major benefit of attending coding boot camps is the job search preparation they offer. Most of these camps come with a hands-on focus and by the end of the program, participants have developed several web applications that serve as excellent initial content for a programmer portfolio. In addition, many boot camps offer a technical interview training aspect, where you get to practice difficult interview questions.
Huge success rate
An impressive number of successful participant outcomes is another key advantage of attending coding boot camps. In general, most of the boot camp students successfully find employment using their programming skills.
Why Magnimind Academy?
Learning Python development for data science is different from learning it for programming. For instance, if you want to learn Python for data-crunching tasks, you’ll need to focus on NumPy and Pandas. The former offers the support of extremely optimized multidimensional arrays, which are the most fundamental data structures of a majority of ML (Machine Learning) algorithms. When it comes to manipulating data, the most popular Python library you’ll use in your data scientist career is the Pandas. You should learn NumPy first and then the Pandas, because the latter is an extension of NumPy. Also, its underlying code extensively uses the NumPy library.
Magnimind Academy covers Python extensively in our Data Science program, our 15-week course that teaches you all the skills you need to start a career in data. This course allows you to learn and implement your Python skills in real-life scenarios to build domain expertise.
When you’re planning to attend a boot camp to learn Python programming, you should understand that there’re some that offer curricula which aren’t of much importance. So, it’s immensely crucial to choose the boot camp wisely. Wherever you sign up for, it should help you reach your professional and personal programming goals, empower you with the most relevant technical skills that you require, and must not be beyond your financial capabilities.
At boot camps offered by Magnimind Academy, you not only get to learn Python programming in an immersive environment, but can also enjoy after-course guidance and the option of becoming a member of Magnimind Network. And if you’re planning to learn Python programming in order to step into the data science field, Magnimind can greatly help you in that too. All you need to do is to enroll in its Data Science Prep Course to learn the fundamentals of data science and attend a 6-week boot camp after that to take your career to the next level.
Hopefully, now you’ve got a clear idea of the importance of learning Python programming. So, get enrolled in a boot camp today and start programming.