Saturday, November 26, 2022
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Will I be stuck in the past if I miss out on AI and ML Courses?

AI & ML Courses suddenly became the leading destination to up skill with data science skills and grow in the career. But, this hasn’t happened overnight! It took sustained efforts and collective intelligence to reach where we are now with AI. 

Today, 90 percent of the analysts and data engineers consider AI certification as a gateway to future journeys. Is it really that important to have an AI ML certification today? What are the consequences of not getting the AI ML training? How far would one be left behind if these certifications are not added to your CV?

In this article, we will explore the benefits of AI & ML courses and what it takes to come out of the past challenges and aim for the future.

In 2010, the AI market was largely focused on detailing machine learning works for military and computer processing systems. The innovations were mostly happening in the fields of healthcare and financial data management where data was readily available from the offline medium. But, then Google, IBM, Facebook, and others dived into the world of Big Data and eureka! 

The big bang in the Artificial intelligence industry began with fervor. While a large part of AI development could be attributed to the ease at which data was produced, mined, and analyzed, the real jerk came with the stupendous success of a great AI innovation, called the chatbots. Chatbots are machine level interfaces that are trained to simulate human conversations without revealing their machine side! 

Here’s an archived story.

Did you know that it was only after a supercomputer fooled a panel of judges in the UK that marketers and sales professionals truly started believing in the truest potential of what AI based bots could achieve in the future? Yes, we are referring to the 2014 Turing Test challenge where a supercomputer called “Eugene Goostman” managed to deceive UK judges into believing that they were actually talking to a minor boy from a city in Ukraine!

 Since then, the world has moved on and we have witnessed how large organizations have begun to explore the AI space to bring in virtual assistants who could chat with humans, convert speech to text and vice versa, and also take human commands to control connected devices. You already know the world of Google Assistant, Alexa, Siri, and others that showcase the pinnacle of AI innovation in the fast moving world. It is not merely important to know about these devices and software but also to know the technology that runs these platforms. 

Fast forward from 2014 to 2022, we see how different business departments have emerged as the most prolific adopters of AI technologies. For example, Marketing teams use AI to fuel data driven analysis of various marketing campaigns and enhance their visibility and understanding of the product, price, people, and promotion (advertising). From customer data and relationship management to email marketing to social media, there is nothing left in the marketing department where AI algorithms haven’t been tried and tested. And, the results that have been achieved are beyond phenomenal. 

In marketing, you would find the complete portfolio of machine learning techniques being used. The rampant adoption of marketing specific algorithms such as Supervised Learning, Semi-supervised learning, Unsupervised learning, augmented and cognitive learning, reinforcement learning, and embedded AI are widely acknowledged. Like marketing, other departments from diverse industries and ecosystems now believe AI is the way forward. 

But, will these continue to be sustainable? 

The answer is 50-50 and depends on how quickly organizations are able to scale their AI infrastructure and hire great talent who can help companies scale their efforts. Many business leaders consider this evolution as part of the digital transformation journey. Without human effort and intelligence, the systems may not deliver reliable results.

On the contrary, without AI systems, human intelligence and efforts can’t be scaled either. So, what we need now is the seamless integration and orchestration of human and machine level intelligence that can help software and devices learn what results are expected in optimized setups.

Conclusion

So, after evaluating everything that AI & ML courses have to offer to us, it is evident that the non-learners would be always stuck to the past, and ill-prepared for the future challenges. Whether you are in a business role or pursuing your own dream company investments, AI’s role from a future perspective is very important for growth, success, and prosperity.