Before going on to answer that question I would like to present just how much the data analytics professionals really love Python. A recent survey involving the developers has come up with some insightful figures. It says that 49% of developers use Python for data analytics, 42% of them use it for machine learning. As far as Python is concerned it can be used for virtually anything from developing machine learning algorithms to mobile games to graphic animations. However, it is the data science professionals and analysts who use it the most. The more specialized language for data science, R, has a fair share of its market to Python nevertheless R is still largely preferred for academic and research oriented analytics.
Analytics and the market
A lot of words have flown around the internet about the future of big data and the application data science and machine learning in the last few years. We can finally say that things have cooled down a little bit. That means data analytics and machine learning are becoming part and parcel of various industries. Take for example the pharmaceutical industry. It is using machine learning algorithms to perform protein tests on the medicinal prototypes. This way, the industry is saving tons of money and literally months.
Then again if you take a look at the e-commerce industry: it has always been among the flag bearers of data analytics. They depend even more heavily than before on AI driven advanced analytics for marketing and customer satisfaction. The point to be established here is that data analytics and its different exponents are ruling the industries and Python is one of the key tools behind it.
This question has been asked and answered thousand times over in various forums and articles, so, why not once more?
The first point to be noted is that Python comes with an easily comprehensible syntax which mostly follows the English language. If you want to start coding, start with Python.
It is incredibly efficient in executing the programmes which means increased speed and in turn enhanced suitability for machine learning.
Python has more than 70,000 libraries and growing. A significant number of libraries are dedicated towards data science. There are libraries suited for almost every data related task.
The vibrant community keeps this open source technology keeps developing. There is little scope for stagnancy or obsolescence.
Perks of getting Python training in Malaysia
The Malaysian government has shown utter keenness to grow as the centre of data analytics in South-East Asia. The nation has great scopes and most importantly it is capitalizing on those. The demand for data science professionals is incessant and there is hardly a better tool to get started than Python.
Learn to deal with data using Python and establish yourself as a worthy candidate for an analytics job.
Python is one of the very few tools which have not seen a downward curve in popularity in quite a few years. It is a consistent and constantly developing tool. And learning Python can help you climb the ladder with great speed.