5 reasons to learn Python for a successful career in Artificial Intelligence and Machine Learning

5 reasons to learn Python for a successful career in Artificial Intelligence and Machine Learning

Written by Experts at ISET

Fly overseas to Australia, Canada, or the USA. Escape that boring job in coding and software development.

Here’s why learning Python is the solution to have a fulfilling career in Machine Learning and Artificial Intelligence.

Artificial Intelligence (AI) and Machine Learning (ML) are all set to take over the future of software development.

According to Dataversity, by 2020 AI will create 2.3 million jobs and eliminate 1.8mn jobs. We will use AI Assistants for every day tasks.

AI finds use in solving problems in a lot of applications. AI helps businesses improve sales, detect fraud, improve customer experience, automate work processes and predict problems that are waiting to happen.

There has also been a rapid growth in technology companies based on Artificial Intelligence and Machine Learning. It is widely used in healthcare, automotive, financial services, and logistics industries.

As a software developer today you have two choices.

  1. Reap the opportunities for new work.
  2. Or become obsolete.

For the first option, getting certified in AI and ML is the way to go.

But how do you get started with learning AI and ML to get that dream job and lifestyle?

Start with Python.

Python has a large community of raving fans. Its popularity will continue skyrocketing until 2020, according to a report from Stack Overflow.

But that’s not the only reason you should be using Python to get started on AI and ML.

Here are 5 other good reasons.

#1 Python is easy to grasp

You’ve spent at least four years (or more) in learning and implementing various programming languages in your projects.

So, if you’re staying away from Python because you think it’ll take a long time to learn, think again.

Python’s is easily understandable by humans. It’s quite similar to English and you can work intuitively with the language. So, you can better focus on building Machine Learning models without spending time on learning the language itself.

BONUS: Python’s readability also helps you share algorithms and make changes to peers’ codes. Again, this saves time and helps your team make quick progress with projects.

In short, you can learn and scale up quickly in your job even if you’re just getting started with AI and ML.

#2 Has an extensive collection of libraries

A library is a collection of pre-written code that developers can use to solve common tasks. This saves loads of time because you don’t have to code everything from scratch.

Moreover, Python’s libraries are great for processing and analysing data to fish out meaningful information from it. This is especially useful for Machine Learning models since it requires continuous data processing.

Here are some of the most used libraries for AI and ML.

Sci-Kit, Keras, and TensorFlow: Helps in handling basic ML algorithms, assists in quick calculations, and helps you set up deep learning systems.

Pandas: Used for analysing data. Helps you work with data from external sources like Excel. You can also merge and filter data easily using Panda.

PyBrain: Contains algorithms for neural networks, reinforcement learning, unsupervised learning, and evolution. This is specifically built for entry level students.

Matplotlib: Matplotlib helps you create histograms, charts, etc, to help interpret your data easily.

For more information on Python libraries, visit PyPi.

#3 Easy to run on all platforms

Python is platform-independent. So, it can run on any system without using a Python Interpreter. Windows, OSX, Linux, and twenty-one other operating systems support Python.

This makes your work easier because you’ll only have to make fewer or no changes at all while importing code into another system.

You can also use your GPU to train your ML model instead of relying on Amazon and Google’s computing services. This saves a lot of time and money while testing out code for various platforms.

#4 Python is flexible and makes your life easier

You can combine Python with other programming languages like Java, C, and C++ etc to improve efficiency and develop better applications.

Python also helps you make changes to your program without having to recompile it again. Just another way that Python saves time and makes your life easier!

#5 You get great community and corporate support

Python is a popular open-source language. This means the internet is overflowing with resources to help you start and get used to Python. There are loads of forums that’ll help you debug your programs and find solutions whenever you hit a wall.

As for corporate support, tech giants such as Google and social media platforms like Facebook, Quora, and Instagram use Python.

In fact, Google was responsible for creating libraries like Keras, TensorFlow, etc.

Python is one of the most versatile and easiest programs to work with.

It’s great for building Machine Learning Models, Neural Networks, and other applications because:

  • It’s easy to learn
  • Has an extensive collection of libraries
  • Easy to run on all platforms
  • It is one of the most flexible programming languages
  • You get great community and corporate support
  • Are you keen on learning Python?

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