Top 9 Reasons to learn Python to become Data Scientist & AI Expert

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Python – A language that by self-confession was not created for mass consumption is creating ripples all across the spectrum of programming languages, is being touted to be the future programming language.

How you ask?

Python grabbed the #1 spot as IEEE Spectrum 2017 #1 programming language toppling C, Java, and C++. TIOBE ranked Python as programming language of the year 2018!

In a recent survey conducted by Kaggle among nearly 24,000 data professionals, Python emerged as the most favourite with 83% using it on a day to day basis. Nearly three decades since its inception, companies heavily rely on Python, be it Google relying on Python to crawl webpages for keywords or Philips telling robots what steps to take. Any animated film buffs here? Pixar uses Python to craft your favourite animated movies.

HIGHLIGHTS OF THE ARTICLE

  • Python adjudged the programming language of the year 2018 by TIOBE
  • Top companies rely on Python for their programming, web development, IOT or Data Analysis needs
  • Three out of four data professionals recommend that aspiring data scientists learn Python first
  • A cool 28% job posts in the Silicon Valley listed Python
  • Going by user trends, will become the most universal AI programming language over the next twenty years.

Watch a free tutorial conducted by Ivy Professional School to get an idea of how Python is used in Data Science and Why it is important to make a career in Data Science.

Why should you learn the language experts are betting on to be the future??

 #1 Python is pretty easy

Python is simplistic and flexible. Even without expert programming skills, you can pick up the syntax quite easily but the system is robust

enough to handle almost any function, including AI.

Expect a shorter learning curve than other languages, say Java or C++, and understandable and readable syntax. Python on its part will automatically take care of things like garbage collection and even close files, opened via the ‘with’ statement, for you. People starting out may also find the use of indentation to signify the start and end of loops, functions, classes and code blocks easier than tracking down the traditional opening and closing curly braces.

The TIOBE index states that Python is one of the most preferred and popular languages in the world, featuring above Perl, Ruby and JavaScript by a wide margin.

 

#2 Python for Data Science

Interested to establish yourself as a Data Scientist? 3 out of 4 data professionals recommend that aspiring data scientists learn Python first considering that a code that takes three hours to write in Java takes just 30 minutes to write in Python.

Apart from its easy readability and code-friendly syntax, the libraries and framework Python offers e.g. SciPy, NumPy and PyMySQL on AI, PyBrain, DataScience, and Machine learning are one of that reason. There are over 145,000 custom-built software packages, many of which use ‘machine learning’ to crunch patterns in big data.

Python is much more versatile than R e.g. you can create scripts to automate stuff, go into web development and so much more.

IBM, Google, NASA, Mozilla, Facebook, Dropbox all use Python adding more ground to the idea that Python is here to stay.

#3 Popularity and Job opportunities

Career opportunities associated with the Python programming language have grown significantly.

A report compiled by Indeed (which ranked programming languages according to the percentage of job postings within the category) showed that Java topped the list, both in Silicon Valley (35 per cent of job postings listed the skill) and across the United States (30%) while Python came second in Silicon Valley (28% job postings).

A fresher Python developer in Bangalore takes home around Rs.5-6 LPA. (according to payscale.com and indeed.com in India)

 

 

#4 Python for Machine Learning

Machine learning has swiftly modified everything around us in the last couple of years. In its most basic form, it is a way to achieve AI.

It is basically training algorithms so that it can learn how to learn, the best examples include our virtual assistants. Siri, Alexa or even our cab-hailing app Uber which is totally driven by Algorithms. Checking Maps for traffic predictions is an everyday affair. How many times has Facebook instantly recognized that friend of yours in the pic you just uploaded or Google has refined the search results for you. According to IBM, Python is one of the most popular and the best languages for Machine Learning.

Enrol in a  Data Science, ML course to learn the best combination of theory and practical aspects of machine learning along with relevant case studies which provide learners with the best combination of theory and practical aspects of machine learning along with relevant case studies, making it a crisp and hands-on programme.

#5 Large supportive Community

Coding alone is a tedious task and can often get boring. But when you have a peer group(online /offline) you can discuss and talk out your experiences it is fun and has often proven to be a faster learning technique. Python has great dedicated online and offline resources you can refer to when in doubt. It is a community-supported language, where you could find a private community of peers in the form of Facebook groups or even slack channels. Which one gives the most authentic answers? Well, that would probably require some trial and error and your best judgement.

#6 Free & Open Source

Open Source was considered to be high risk till only a few years ago. Microsoft’s acquisition of GitHub (home of many open-source projects) or IBM acquiring Red Hat (Red Hat is the backbone of the Bombay Stock Exchange (BSE), National Stock Exchange (NSE), Aadhaar, GST, Life Insurance Corporation of India (LIC), SBI Insurance and most core banking services across India) just goes on to show that enterprises and governments alike are embracing OSS (open-source software).

Over the last couple of years with the rise of data sciences, Python has become the world’s most popular programming language in 2017-18, including in the financial markets. With its easy availability along with its hassle-free development and modifying capabilities, the transparent interface makes it a prominent choice of tech companies. The latest report from Forbes states that Python showed a 456-percent growth in 2017. Its vulnerability for being free software is ruled out and it is used for the highest levels of technical innovations. Experienced Python developers use its rich library and tools like Fabric, Ansible, Scikit-learn and Tensorflow to automate repetitive processes. Its versatile applications in data science, machine learning and other high tech developments make Python a leader in the market.

 #7 Easy Adaptability with other technologies: 

Python is well integrated with the Windows platforms. Python programs can interact with COM and DCOM services, and can even implement new COM and DCOM services (which is not possible using Visual Basic!). Python can also be used as a scripting engine in Microsoft’s Active Scripting architecture.

The multiple implementations of Python as JPython (a blend of Python and Java for JVM), IronPython (Python with C#), CPython (Python and C) etc. ensure that the applications can interact with modules written in different languages. Python also supports third-party packages Python Package Index (PyPI) which ensures that the Python program communicates with those written in other languages.

#8 Web Development

I am sure you all are aware that python is used for web and mobile app development, so I went in and did a bit of surfing and guess what some of the world’s most popular websites are created using Python. The app development market just got “pythonized”.

#9 Python in AI

Going by user trends will become the most universal AI programming language over the next twenty years. That’s a pretty safe bet. The versatility of Python (easy readability and code friendly syntax) allows developers to perform multiple activities at one time combined with an abundance of libraries and frameworks that facilitate coding and save development time. There is of course the ease of testing algorithms provided by Python which makes it one of the best programming language among the other programming languages. With Python, writing and executing all codes is simpler. With minor tweaks in the source codes, applications can be up and running even on different operating systems.

Excerpt from an interview by Peter Norvig (director of research at Google):

“I found that Python was very nice for certain types of small problems, and had the libraries I needed to integrate with lots of other stuff, at Google and elsewhere on the net.”

The top companies around the world rely on Python. Netflix uses Python, IBM uses Python, and hundreds of other companies all use Python. Dropbox is also created in Python.

If you need a more lucid explanation for the techniques, you can opt for the Machine learning course from Ivy Professional School. Ivy’s expert faculty have been named among the Top 20 Analytics Academicians in the country in 2018. Check out Ivy Professional School’s new course, Machine Learning With Python

REFERENCES :

  1. http://customerthink.com/programming-languages-most-used-and-recommended-by-data-scientists/
  2. https://www.ibm.com/developerworks/community/blogs/jfp/entry/What_Language_Is_Best_For_Machine_Learning_And_Data_Science?lang=en
  3. https://opensourceforu.com/2018/07/building-next-generation-government-applications-using-open-source-technologies/
  4. https://economictimes.indiatimes.com/tech/software/from-railways-to-aadhaar-indias-key-systems-run-on-ibm-acquired-red-hat-software/articleshow/66425951.cms
  5. https://www.forbes.com/sites/jeffkauflin/2017/01/08/the-10-technical-skills-with-explosive-growth-in-job-demand/#28cb79364f5c
  6. https://spectrum.ieee.org/view-from-the-valley/computing/software/what-programming-language-skills-do-employers-want

 

 

Shromona Kahali, Content Strategist- Ivy Pro School


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