Do you want to become a data scientist?
What are the top programming languages for data science in 2020?
Because businesses are constantly generating a huge amount of data than ever before, the demand for data science professionals is at an all time high.
In fact, according to an IBM report published on Forbes, data science has been ranked the best job in tech for the last 3 years.
But in order to be able to assess and analyze the data gathered, you need the best data science tools and skills.
In order to bring together statistics and data analysis to understand data, you need both thorough mathematical skills and an in depth understanding of a data science programming language.
So in this article, we are going to look at the best programming language for data science that you should learn in 2020.
These are the top programming languages for data science that are mostly used by other data scientists and that employers are constantly looking.
Even though there are hundreds of programming languages that could potentially be used for data science…
… in this article, we’ll narrow down to a few appropriate and most used ones.
I hope that by the end of this article of the top programming languages for data science, you’ll be ready to pick one language and get started with your data science career.
If you are ready to get started learning data science, check out my other article where I review the best data science courses online to get you started.
Through these courses you’ll not only learn the basics, but you’ll also acquire advanced skills in some of the top data science programming languages.
Here are the 7 best data science programming languages to learn in 2020.
Python is a high level interpreted object oriented programming language created by Guido van Rossum and first released in 1991.
It is one of the top programming languages for data science and is used by more than half of data scientists.
What makes Python the top programming language for data science is because it’s easy to learn and has a ton of useful libraries for deriving value from data.
The Python syntax is also very easy to read which also makes it popular among data scientists as they find it much easier to understand.
Here are some Python tutorials to help you quickly get a grasp of this data science programming language.
Some of the popular Python libraries for solving data science problems like data analysis, visualization and predictions include Pandas, Numphy, Matplotlib etc.
It also enables you to improve its data processing capacities by interfacing with more complex and efficient algorithms written in languages like C or Fortran.
R is an open source, object oriented programming language that is commonly used for statistical computing and graphics.
Even though it is one of the best programming languages for data science in 2020, it presents a rather steep learning curve as compared to Python.
Despite not being easy to learn, it is one of the most demanded skills by employers in data science and machine learning.
By learning R through these online R programming tutorials, you’ll be able to pick up these skills faster as you’ll be learning from expert R programmers.
It is the data science programming language of choice for diving deeper into data analytics and statistics.
While being able to well handle complex algebra, it has a collection of over 10k packages that cater for all your statistical analysis and neural networks needs.
Thanks to the lapply function, R is able to perform high iteration operations faster than Python.
Some argue that the drawback to R is that it’s not general purpose and is specific to the statistics…
… but this could also explain why its packages, being more statistical analysis oriented are able to outperform Python in certain instances.
SQL, also known as Structured Query Language, is the language used to create, read, update and delete data stored in relational databases like MySQL, SQLite, Microsoft SQL Server among others.
It is one of the most popular data science languages used by data scientists for updating, querying and manipulating databases.
Because of its fast processing time, SQL is particularly used for managing large databases since it reduces the turnaround time for online requests.
In depth knowledge of SQL is a must have if you are serious about a career is data science.
I also put together a list of the best SQL courses online that will take you from a beginner to advanced SQL programmer.
Apart from the fact that almost all data science recruiters require skills in SQL, it is very easy to learn because of its highly readable declarative syntax.
So having above average SQL skills is your biggest asset as a machine learning and data science professional.
SQL is similar to Hadoop in that it manage data, but they way the data is stored is different… as you’ll discover by the SQL tutorials above.
Scala, short form for scalable language, is an open source multi-paradigm concurrent programming language developed by Martin Odersky in 2003.
It is one of the top data science programming languages because it is stable, fast, flexible and scalable.
Scala runs on the JVM (Java Virtual Machine) and features both object oriented and functional programming capabilities.
The reason Scala is popular in data science is because you can use it with Spark, a big data platform that is ideal when dealing with big volumes of data.
If you are already familiar with other languages like Java, C++ or Python, you’ll find Scala pretty easy to learn.
However, if you are a complete beginner, you’ll experience a steep learning curve because its syntax is harder to pick.
In order to quickly pick up skills in Scala programming, you need a simple and straightforward tutorial that’s targeted for beginners.
This list is of the best Scala tutorials for beginners will provide you with clear straightforward videos tutorials to get you started.
Apart from allowing interoperability with Java, it’s also able to facilitate parallel processing on a large scale.
There are also many other popular, high performance data science frameworks written on top of Hadoop to be used in Scala or Java.
So Scala is one of the best data science languages for you if you are doing machine learning at large scale or building complex high-level algorithms.
This list of the top programming languages for data science cannot be complete without the mention of the Julia programming language.
It is an open source, modern and high performance programming language mostly applied for data manipulations and scientific calculations.
Created by a group of MIT mathematicians and computer scientists, Julia has gained a lot of popularity in the data science and machine learning world.
Julia’s fast speed makes it one of the best programming languages for data science and machine learning in 2020.
So while being simple and easy to learn, just like Python, it has the lightning fast performance of the C language.
This has made it a top data science programming language because it can solve complex mathematical operations at a very high speed.
In fact, recent performance benchmarks have shown Julia to run 30x faster than Python when handling massive data sets.
Just like Scala, it is one of the best data science languages that facilitate parallel processing focused on numerical computing.
Even though it’s still much less popular than Python, a number of banks already use it for risk analytics.
Java is a general purpose cross platform object oriented programming language and is common among web, desktop, mobile and embedded applications.
While it might not appear like an obvious language for data science, it is one of the top programming languages for data science thanks to data science frameworks like Hadoop that run on the JVM.
Hadoop is a popular data science framework for managing data processing and storage for big data applications.
Because of its ability to handle virtually limitless tasks at once, Hadoop enables storage and processing of massive amount of data.
Java also has a huge number of libraries and tools for machine learning and data science.
So Java is one of the best data science programming languages to learn if you want to enjoy the capabilities of the Hadoop framework.
Matlab, short form for matrix laboratory, is a multi-paradigm numerical computing language developed by Mathworks for use in numerical computations.
It is also one of the top programming languages for data science because it’s quick, stable and ensures solid algorithms for numerical computing used in academia and the industry.
While it’s considered the go to language for mathematicians and scientists for solving complex mathematical problems, it finds its way into data science through its use in statistical analysis.
Some of its amazing applications involve fourier transforms, signal processing, image processing and matrix algebra.
Even though less popular compared to Python, I would consider Matlab a must learn skill for anyone serious about a career in data science.
Data science brings together theories and techniques from other fields like statistics, mathematics, computer science and information science to analyze and make sense of big data.
But the baseline is that in order to become a professional data scientist you must be proficient in a data science programming language.
From my experience, though, most data science professionals always know more than one data science language.
Your best approach is to pick one data science programming language, learn it inside out and then move to the next.
I hope that this article of the top programming languages for data science has helped you narrow down on the best data science programming language to learn in 2020.
The data science field is evolving fast, though, and new tools for extracting value from data are developed daily.
So, while learning any of the best programming languages for data science I mentioned above with help you launch you data science career, if you are a complete beginner your best bet is to start with Python… then R.
The great thing about learning Python for data science is that it has a great collection of resources to get you started…
In fact I put together I review of the best Python tutorials for data science.
By taking these tutorials, you’ll not only learn the basics of Python programming, but you’ll also look into some of the most popular Python tools and libraries for data science.
Have you tried to learn data science before?
What is your favorite programming language for data science in 2020?
Please share your thoughts in the comments below.