Python Certification Training in Sydney

why should a programmer learn Python?

• • Python is growing Ok, that’s great, but it doesn’t mean Java is going down or C++ is declining.
  • Well, I am a proud Java developer and it is my favorite programming language and always remain, but, that doesn’t stop us learning potential new tools and programming language which will make you a better programmer and Python fits that bill.
  • For beginners it’s simple, start with Python because it is easy to learn and powerful enough to build a web application and automate boring stuff.
  • Actually, a couple of years back, scripting was the main reason for learning Python and that was also the first and foremost reason I attracted to Python and preferred it over Perl, another popular scripting language of that time.
  • For experienced programmers or someone who already know Ruby, Java, or JavaScript, learning Python means acquiring a new and powerful tool in your arsenal and I have yet to come up with a programmer who says no to a tool and that’s the right way to look when you learn a new programming language.
  • As mentioned in the classical Automate the Boring Stuff with Python book, Python gives you the ability to automate trivial stuff, and let you focus on more exciting and useful things.

• • If you are thinking to learn Python but not sure why you should do that then here are 10 reasons which highlight the benefits of learning Python in 2020.
  • Though, the questions depend upon who is asking that i.e. for a beginner, learning Python makes sense because its simple and main reason for learning Python is simplicity.
  • Similarly, for an experienced programmer who is looking to go into Data Science and Machine learning, learning Python makes sense because it’s quickly becoming the most used programming language and there are powerful APIs and library available for AI, Data Science, and Machine learning.
  • The reason behind immense popularity of python programming language across the globe is the features it provides. Have a look at the features of python language.

• • Python is a multi paradigm programming language including features such as object oriented, imperative, procedural, functional, reflective etc.

• • Python has very extensive standard libraries and tools that enhance the overall functionality of python language and also helps python programmers to easily write codes. Some of the important python libraries and tools are listed below.
  • Built-in functions, constants, types and exceptions.
  • File formats, file and directory access, multimedia services.
  • GUI development tools such as tkInter.

• • This is what makes python a favourable choice for development purposes. If you are having problems writing python a program, you can post directly to python community and will get response with the solution of your problem. You will also find many new ideas regarding python technology and change in the versions.

• • Python provides a much better code readability as compared to another programming language. For example, it uses whitespace indentation in place of curly brackets for delimiting block of codes. Isn’t it awesome?

• • Codes written in python programming language complete in fewer lines thus reducing efforts of programmers. Let’s have a look on the following “Hello World” program written in C, C++, Java and Python.

• • Not convinced that Python is the right language for you? Well, it’s time to change your mind.

• • First and foremost, Python is one of the easiest programming languages to learn. You don’t need to have any programming experience to start performing data analysis in Python. Unlike R and MATLAB, two other popular languages in science and engineering, Python has very simple syntax and coding rules, making it the perfect language for beginners. And it’s also very easy to set it up and jump right in.

• • Fintech and traditional finance areas prefer Python to other languages because of its quick application development time. Owing to the myriad of open-source data analysis libraries, developing fintech applications in Python doesn’t take nearly as much time as it does with data analysis tools such as Microsoft Excel and R because you don’t have to waste time writing code from scratch.
  • Trying to decide between R and Python? Check out this article to learn more about these two competing languages.

• • The biggest challenge for beginner programmers is finding useful tutorials and resources. Fortunately, the official Python documentation unpacks everything you need to know about the language—and since Python is already simple enough as it is, picking up the language is fairly straightforward. But if you’re looking for more hands-on experience and guidance, you can also look into taking some affordable introductory Python courses from data experts.

• • The R programming language, Python’s biggest competitor in data science, is credited with providing excellent data visualization libraries. But Python is quickly catching up—with data science packages like plotly, ggplot, and pandas, you can create professional plots and other forms of data display.

• • A full-fledged scientific computing library for performing linear algebra and high-level math in Python, allowing you to work with matrices and other data structures. If you’re familiar with MATLAB, you’ll feel right at home with NumPy.
  • Building on top of NumPy, SciPy is an excellent library for data scientists and engineers that allows you to work with N-dimensional arrays and perform a variety of optimization and linear algebra operations.
  • If you’re into machine learning, this is the library for you. scikit-learn implements a variety of popular machine learning algorithms. And if you’ve already picked up NumPy and SciPy, you’ll be happy to know that scikit-learn was designed to work with these two packages!
  • Need to create histograms, pie charts, line graphs, or other professional data visualizations for your work? No problem. There’s really no limit to what you can do with matplotlib. You can alo export all your graphics to popular formats for publication.
  • pandas is an excellent open-source library for data manipulation and analysis. If you’re familiar with data frames in R and the syntax of SQL, you’ll find that pandas combines the best of both of these worlds in a nice little Python library.
  • If you’re looking to review your knowledge of the pandas and Matplotlib libraries, check out this Introduction to Python for Data Science course.
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• Octave and MATLAB, step aside. Python is not just for casual programming-it’s being used by leading companies in a variety of fintech fields. For example, Bank of America’s Quartz and J.P. Morgan’s Athena platforms both use Python, and big companies like Google, Facebook, Instagram, and Spotify also use Python in their development. Many other companies like Citigroup also now require their data analysts to master Python and take training classes for the language.