Published17 September 2020at12:14, updated on10 October 2022at16:14
Spoiler alert: Artificial Intelligence is the future of work. Or at least part of it. This is not to say that everyone will become an AI engineer. But in just a few years from now, a large part of job positions will require or reward AI skills that help employees be more efficient and dedicate themselves to higher-level tasks. Especially in areas like IT, where human error can have dire consequences. So what online AI courses are best to get you up-to-speed with this booming discipline?
AI has experienced a major explosion in popularity in recent years, becoming one of the fastest-growing roles in job markets across the world. Just at the beginning of the year, a LinkedIn report identified AI-related skills as the fourth most in-demand skills group among employers. And that was before the pandemic set in.
The increased need for automation and the budgetary constraints brought about by Covid-19 are likely to spur further spikes in AI adoption, with recent Indeed data from the Indian market suggesting job searches in artificial intelligence might have grown as much as 106% from last year. AI-related job searches experienced a 20% uptick since March alone.
Bottom line: believe the hype. It’s about time you put on your AI boots if you still haven’t done so. Here are five courses to get you started that touch upon some of today’s core AI skills.
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How comfortable would you feel explaining to someone the difference between AI, machine learning and deep learning? What comes to mind when you hear the words ‘neural network’?
If you are not quite sure, start with the fundamentals. This Coursera course by IBM provides a good introductory overview of artificial intelligence and its many aspects:
Python is to AI what English is to Shakespeare’s plays. This nimble yet powerful language is one of the most popular among programmers and engineers, and, if you haven’t gotten around it already, well – you should.
This course on Udemy kicks off with a Python crash course and then gets into its data science and machine learning applications, covering the most widely used Python libraries and tools for AI (NumPy, Pandas, Matplotlib…):
In essence, machine learning is the use of algorithms to process data, learn from it and then act according to these learnings. Machine learning allows computers to autonomously learn and improve processes and assessments through experience, without being explicitly programmed beforehand. It’s pretty much ubiquitous these days –from your phone’s predictive keyboard to web searches.
This course by Stanford is a good starting point:
Developed by Google Brain Team, TensorFlow is an open-source library for numerical computation with powerful AI capabilities. TensorFlow is Python-friendly and is currently one of the most in-demand AI skills.
This video offers a great hands-on introduction to building neural networks with TensorFlow:
The course requires previous Python literacy, so you should not jump into it before learning the language.
NPL is a branch of artificial intelligence that focuses on analysing, understanding and producing human language. It is an integral technology to many everyday features of the digital economy, from autocorrects to chatbots.
This Codecademy course provides a practical and project-based introduction to NPL:
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