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 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. You can 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, but to get your foot in the door as a Data Analyst, it takes about 40-50 hours of studying and practicing — in my 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. With our focus being pulled in many directions at once, sometimes having some guided learning 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 Python? The answer is up to YOU.
Are you ready to start your next chapter?