<p style="text-align: justify">Acquiring the right set of skills is vital for budding data scientists to succeed. There are a variety of tools, software platforms and programming languages in the market and it can be a tricky job to determine the most suitable tool and language a data scientist must learn. However, it can be safely said that Python is not only perfect for aspiring data scientists but also instrumental in building a career full of growth and opportunities.</p>
<p style="text-align: justify"><strong>Why Python is the perfect choice?</strong></p>
<p style="text-align: justify">With a gradual learning curve Python is one of the easiest high-level programming languages out there. You do not have to spend a lot of time on cramming complicated syntax which other languages require and in no time, you will start coding in Python efficiently.</p>
<p style="text-align: justify">Moreover, it is also an open source language which means it is free to use for whatever purpose you want to use it and there is a growing support community always there to help you. This is one of the main reasons that many select python as the first programming language to learn.</p>
<p style="text-align: justify">However, in the field of data science Python is not chosen by skilled professionals only because it is easy. It has lots of advantages when it comes to performing various data science related tasks owing to its over 72,000 dedicated libraries.</p>
<p style="text-align: justify">Let’s take a look at some of those—</p>
<p style="text-align: justify"><strong>NumPy</strong></p>
<p style="text-align: justify">Data scientists are required to operate on multiple arrays of homogenous data very frequently. NumPy is a Python extension module that supports n-dimensional arrays and boasts high level mathematical functions that allows data scientists to operate on multiple arrays easily.</p>
<p style="text-align: justify"><strong>SciPy</strong></p>
<p style="text-align: justify">When it comes to complex mathematical calculations that data scientists need to perform, SciPy is a great Python module which supports special functions like gradient optimization, ODE solvers, integration etc.</p>
<p style="text-align: justify"><strong>Pandas</strong></p>
<p style="text-align: justify">Pandas is another open-source Python library offering user friendly data structures and data analysis tools. Thus, it is great for data analysis and loved by data professionals all over the world.</p>
<p style="text-align: justify"><strong>Python libraries are also important in Natural Language Processing!</strong></p>
<p style="text-align: justify">The three most popular tools used for NLP are NLTK, Intel NLP architect and Gensim. And all the three are Python libraries used for topic modelling, document indexing and deep learning topologies.</p>
<p style="text-align: justify"><strong>Python certification course can be highly beneficial</strong></p>
<p style="text-align: justify">A <strong>Python certification</strong> course will enable you to learn Python easily and in no time, you will be proficient in all such data science libraries thereby increasing your employability several fold.</p>

Should you learn Python for data science?
