In today’s highly competitive market, which is anticipated to intensify
further, the data science aspirants are left with no solution but to
up skill and upgrade themselves as per the industry demands. Prevailing
situation odes the mismatch between demand and supply ratio of data
scientists and other data professionals in the market, which makes up a
great age to grab better and progressive opportunities. The knowledge
and application of programming languages that better amplify the data
science industry, are must to have.
Therefore, here we have compiled the list of top data science
programming languages for 2020 that aspirants need to learn to improve
their career.
Top Programming Languages for Data Science
Python
R
SQL
MATLAB
Java
Scala
Julia
Perl
1. Python
Python is one of the best programming languages for data science because
of its capacity for statistical analysis, data modeling, and easy
readability. Another reason for this huge success of Python in Data
Science is its extensive library support for data science and analytics.
There are many Python libraries that contain a host of functions,
tools, and methods to manage and analyze data. Each of these libraries
has a particular focus with some libraries managing image and textual
data, data mining, neural networks, data visualization, and so on. For
example, Pandas is a free Python software library for data analysis and
data handling, NumPy for numerical computing, SciPy for scientific computing, Matplotlib for data visualization, etc.
2. R
R is a very unique language and has some really interesting features
which aren’t present in other languages. These features are very
important for data science applications. Being a vector language, R can
do many things at once, functions can be added to a single vector
without putting it in a loop. As the power of R is being realized, it is
finding use in a variety of other places, starting from financial
studies to genetics and biology and medicine.
3. SQL
SQL or Structured Query Language is a language specifically created for
managing and retrieving the data stored in a relational database
management system. This language is extremely important for data science
as it deals primarily with data. The main role of data scientists is to
convert the data into actionable insights and so they need SQL to
retrieve the data to and from the database when required. There are many
popular SQL databases that data scientists can use such as SQLite,
MySQL, Postgres, Oracle, and Microsoft SQL Server. BigQuery, in
particular, is a data warehouse that can manage data analysis over
petabytes of data and enable super fats SQL queries.
4. MATLAB
MATLAB is a very popular programming language for mathematical
operations which automatically makes it important for Data Science. And
that’s because Data Science also deals a lot in math. MATLAB is so
popular because it allows mathematical modeling, image processing, and
data analysis. It also has a lot of mathematical functions that are
useful in data science for linear algebra, statistics, optimization,
Fourier analysis, filtering, differential equations, numerical
integration, etc. In addition to all these, MATLAB also has built-in
graphics that can be used for creating data visualizations with a
variety of plots.
5. Java
Java is one of the oldest languages used for enterprise development.
Most of the popular Big Data frameworks/tools on the likes of Spark,
Flink, Hive, Spark and Hadoop are written in Java. It has a great number
of libraries and tools for Machine Learning and Data Science. Some of
them being, Weka, Java-ML, MLlib, and Deeplearning4j, to solve most of
your ML or data science problems. Also, Java 9 brings in the much-missed
REPL, that facilitates iterative development.
6. Scala
Scala is a programming language that is an extension of Java as it was
originally built on the Java Virtual Machine (JVM). So it can easily
integrate with Java. However, the real reason that Scala is so useful
for Data Science is that it can be used along with Apache Spark to
manage large amounts of data. So when it comes to big data, Scala is the
go-to language. Many of the data science frameworks that are created on
top of Hadoop actually use Scala or Java or are written in these
languages. However, one downside of Scala is that it is difficult to
learn and there are not as many online community support groups as it is
a niche language.
7. Julia
Julia is an open-source programming language that is also an accessible,
intuitive, and highly efficient base language with a speed that exceeds
R and Python. This makes Julia a formidable language for data science.
Along with speed and ease of use, it has more than 1900 packages
available. Julia can interface (either directly or through packages)
with libraries written in R, Python, Matlab, C, C++ or Fortran.
8. Perl
Perl can handle data queries very efficiently as compared to some other
programming languages as it uses lightweight arrays that don’t need a
high level of focus from the programmer. It is also quite similar to
Python and so is a useful programming language in Data Science. In fact,
Perl 6 is touted as the ‘big-data lite’ with many big companies such as
Boeing, Siemens, etc. experimenting with it for Data Science. Perl is
also very useful in quantitative fields such as finance, bioinformatics,
statistical analysis, etc.
You've provided quite good information here about Aws Training in Delhi. This is fantastic since it expands our knowledge and is also beneficial to us. Thank you for sharing this piece of writing.
This is additionally a generally excellent post which I truly delighted in perusing. It isn't each day that I have the likelihood to see something like this.. I am searching for and I love to post a remark that "The substance of your post is wonderful" Great work! data science course in chennai
Nice Article...Very interesting to read this article. I have learned some new information.thanks for sharing.
ReplyDeleteData Science Training in Hyderabad
Data Science course in Hyderabad
Data Science coaching in Hyderabad
Data Science Training institute in Hyderabad
Data Science institute in Hyderabad
You've provided quite good information here about Aws Training in Delhi. This is fantastic since it expands our knowledge and is also beneficial to us. Thank you for sharing this piece of writing.
ReplyDeleteThis is additionally a generally excellent post which I truly delighted in perusing. It isn't each day that I have the likelihood to see something like this..
ReplyDeleteI am searching for and I love to post a remark that "The substance of your post is wonderful" Great work! data science course in chennai