Why is it the right time to pursue a career in Machine Learning?

Siddharth Chaturvedi 

 Information Technology has revolutionised human interaction with machines. One of the most important skills to learn is Machine Learning which has the capacity to automate most of human actions. Machine learning (ML) has been a revolutionary force, crucial in leading the fourth industrial revolution. From driverless cars to recommendations on digital services, our world is immersed in Machine Learning applications now. According to a report by Machine Learning Market in India, the global machine learning market will reach a Rs 543 billion valuation by 2023.

ML also structures the industries that depend on vast amounts of data and require a framework to analyse it to enhance outcomes. Currently, ML models learn to identify patterns and make decisions with little intervention from humans. These machines amplify accuracy and reduce the possibility of human error. 

 Being an ML engineer can provide financial benefits and a chance to make actual contributions to future technology. There is a high possibility that career opportunities will continue to advance as the industry does. Many training institutes provide in-depth machine learning courses worldwide to cater to the high demand for Machine Learning professionals. Learners need to be aware that the broad scope of this technology is here to stay for many more years. As the ML domain in India is still in its infancy stage, there is a vast chasm that still needs to be explored.

 Initially, learners need to have detailed background knowledge on the subject before starting a career in Machine Learning. In order to do that, learners can look out for free learning resources for machine learning, gather insights through interviews, and have a comprehensive understanding of the ML domain.

Anybody wanting to have a career in machine learning engineering should research algorithms, deep learning techniques, and new data methods used in adaptive systems. Apart from that, learners require a strong understanding of mathematics, including calculus, linear algebra, and probability to create a standard model. 

Computer science and powerful data science tools are the other topics that would be required to access information and make informed decisions. 

 In the Machine Learning ecosystem, we can power programmes that can be smoothly updated and modified to adapt to the new environment and its tasks. Here are a few reasons why it is the right time to pursue a career in Machine Learning:

●       Skill of the future: Despite the expanding growth in machine learning, the field faces a shortage of skills. If the learners can meet the demand of large companies by gaining the requisite skill and knowledge in ML, they will have a secure career in this rising technology. 

 ●       Learners would work on real challenges: Organizations and businesses in the digital age face several issues that Machine Learning can quickly solve. As an ML engineer, learners will work on challenges practically and develop solutions that impact how businesses and people thrive. This job allows one to work as well as solve a real-world struggle which eventually gives high satisfaction.

 ● Opportunity to grow early on: As ML is on the boom, entering the field early just in time can help learners witness and create trends first-hand. It will also help increase the learners' relevance in the marketplace, thus augmenting one's value to the employer. As the technology matures and moves forward, learners can acquire the expertise to have a steadily rising career graph and approach their ideal employers.

 ●       Build a profitable career: The average salary of a Machine Learning engineer is one of the prime reasons why ML seems a lucrative career for many people. As the AI/ML industry is on the rise, this figure is expected to flourish further with passing years. 

 ●       Access to data science: Machine learning skills aid in the expansion of avenues in one’s career trajectory. ML skills can equip a learner with two hats — the other of a data scientist. Learners can become a resource by procuring expertise in both fields simultaneously and commence on a journey infused with opportunities, knowledge, and challenges. 

Pursuing a career in Machine Learning can help learners play an active part in the digital revolution in sectors ranging from healthcare to logistics. And the present learners can also have the advantage of being an early bird. This way, they will find skills that are in high demand and will be able to secure a career path that’s constantly growing.  

The writer is Executive Vice President, AISECT Group

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