Artificial Intelligence (AI) and machine learning start up companies have received the maximum number of funding rounds in the last 5 years. These startups provide AI solutions and automation software to embed different kinds of AI and machine learning algorithms within their organizations. Organizations belonging to the manufacturing and logistical support/ supply chain management, retail and e-commerce, mobile marketing, digital entertainment, healthcare, automotive, and utility management industries use AI solutions to improve their functions and deliver the best experiences to their users. Despite so much happening in the AI world, the scope of further improvement and adoption hasn’t dwindled one bit. And, the enthusiasm among professionals joining top artificial intelligence courses in Bangalore reveals it all. Today, 9 out of 10 graduates from diverse backgrounds are enrolling in the top AI courses to learn how to program using machine learning algorithms and become data engineers or data scientists.
In this article, we will help you identify the basics of Python programming and why it is considered as one of the top AI programming languages that are hot favorites among the current generation of the data workforce.
Why is Python so popular?
Python is a very popular language due to its cross platform benefits. This allows Python projects to run on multiple operating systems such as Windows, iOS and more. It is also open source which means you can easily comprehend libraries in .NET platforms allowing real time analytics. This real time processing is what made it a reliable foundation for AI applications such as those in business intelligence, Robotic Processes Automation (RPA), Computer Vision, NLP, Neural Search, and Recommendation Engines (Social media intelligence).
Python remains the most used AI machine learning coding platform for a majority of recognizable brands. It is particularly used in building responsive and intuitive machine learning applications such as Chat bots, virtual intelligent assistants / voice assistants, neural networking, search, text analytics, and automation using robots.
How to start with Python for AI?
Python’s usefulness is undeniable in the AI world, and its easy interface attracts even the most novice of programmers into coding because you will find so much information online already where AI development teams post how they used Python. With AI projects mostly using big data and real time predictive intelligence, it becomes very important for Python programmers to ensure their coding is compatible in a cross platform ecosystem, with very user friendly debugging and scalability functions.
Courses specific to the use of Python in AI
Python is a very programmer-friendly coding platform with a lot of cross programming functions and libraries that can be directly deployed in any AI and machine learning project. In fact, the popularity of many of the current crop of programming languages for AI such as Python and R is due to the optimized operational effectiveness and scalability provided by a superlative platform like Python. As we find more and more new programmers taking admissions into Python and R AI courses Python’s prominence remains intact.
Here are the top course topics from the AI curriculum:
Python’s pre-templatised codes are very useful in AI projects. These frameworks can be directly applied to the projects with little or no adjustments. While you could easily find hundreds of Python frameworks when you start working on the projects, top AI courses identify the best that would help you learn and build AI applications very quickly. These are mostly related to AI frameworks such as Neuroph, Apache, Jenetics, and so on.
Python for chat bots building
Can we really build a chat bot using Python, or for that matter, just any single programming language?
With Python, it is a yes. With others, you might still have to add a touch of a bit of Python. In AI courses, AI ML tutorials in chat bot building deeply discuss how a machine learning application can be intelligently developed to simulate human conversations using a combination of NLP and NLU in advanced Artificial Intelligence Markup Language setup. From adding custom conversation identifiers to simple text or voice replies, Python’s setup is a very useful platform for testing and improving the current generation of single-line and multi-line command-based chat bots and virtual intelligent assistants such as Siri, Alexa, and Google Assistant.
To learn Python, it will take 6-8 months. In the best AI courses, this learning will be translated to great success in your business intelligence and product management projects based on AI ML.