4 Important Reasons Why You Should Study Machine Learning Now

Machine learning has inserted itself into the fiber of our everyday lives – even without us noticing. Machine learning algorithms have been powering the world around us, and this includes product recommendations at Walmart, fraud detection at various top-notch financial institutions, surge pricing at Uber, as well as content used by LinkedIn, Facebook, Instagram, and Twitter on users’ feeds, and these are just a few examples, grounded directly in the daily lives we live.

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This being said, it goes without saying that the future is already here – and machine learning plays a significant role in the way our contemporary imagination visualises it. Mark Cuban, for instance, has said: “Artificial Intelligence, deep learning, machine learning — whatever you’re doing if you don’t understand it — learn it. Because otherwise you’re going to be a dinosaur within 3 years.”

Such is the urgency of machine learning. And if you want to take your career to the next level, it is the right tool to set up a platform for yourself. Whether you have been asking yourself how to start learning machine learning or the best way to learn machine learning, look no further than this blog!

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What are the advantages of a machine learning course?

  • Better Career Opportunities and Growth

A report by TMR notes that MLaaS (Machine learning as a Service) is predicted to grow from to $19.9 billion by the end of 2025, from a mere $1.07 billion in 2016. This is a staggering amount of growth, both in absolute terms, as well as year-on-year. 

Machine learning makes a mockery of anything that can be called “important” – both at a financial as well as a global scale. If you are looking to take your career to another level, Machine Learning can do that for you. If you are looking to involve yourself in something that will make you part of something that is global as well as contemporary relevance, Machine Learning can do that for you as well.

Machine learning covers significant ground in various verticals – including image recognition, medicine, cyber security, facial recognition, and more. As an increasing amount of businesses are realising that business intelligence is profoundly impacted by machine learning, and thus are choosing to invest in it.

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Netflix, to take just one example, announced a prize worth $1 million to the first person who could sharpen its ML algorithm by increasing its accuracy by 10%. This is sureshot evidence that even a slight enhancement in ML algorithms is immensely profitable for the companies that use them, and thus, so are the people behind them. And with ML, you can be one of them!

  • Better Salaries

The best machine learning engineers these days are paid as much as immensely popular sports personalities! And that’s no exaggeration! According to, the average machine learning engineer salary is 8 lakhs per annum – and that’s just at the starting of one’s career! An experienced machine learning engineer takes home anywhere between 15 to 23 lakhs per annum. 

If you’ve ever wondered who can learn machine learning, the answer is – you can! And if you’ve asked yourself where to learn machine learning, here’s your answer:  upGrad offers a course in Machine Learning and AI, and it teaches you, among other things, NLP, Deep Learning, Reinforcement Learning and Graphical Models. Moreover, it also provides you a solid foundation in Predictive Analytics and Statistics as well.

It is designed for working professionals and offers one-on-one interactions with Industry Mentors, practical hands-on workshops, as well as 12 case studies and assignments to be done in real life! Thus, you get to experience not only the theoretical realm of things, but also get to witness its practical side! Click here to find out more about the course.

Join the Artificial Intelligence Course online from the World’s top Universities – Masters, Executive Post Graduate Programs, and Advanced Certificate Program in ML & AI to fast-track your career.

  • Lack of Machine Learning Skills is Plaguing Corporations

Given the rapid rate at which technological leaps have been made, a lot of corporations have been left playing catch up. Digital transformation is a huge industry, and the truth of the matter is that there are simply not enough machine learning professional to cater to new industry demands.


A New York Times report released in October 2017 surmised that the total number of people qualified for AI and Machine learning-related jobs were less than 10,000 people in the world. 

This number is likely to have both increased – due to the number of jobs that have been created – and decreased, due to the fact that people are getting skilled in ML everyday. But the matter still remains, that the supply far exceeds the demand, in this scenario. Moreover, it is also true that it does not require an exceptional set of qualifications to be eligible for jobs in the ML arena – it only requires a specific set of skills and abilities, all of which you can learn from upGrad’s course in Machine Learning and AI!

  • Machine learning and Data Science are intricately linked 

If religion ruled the masses for entire centuries before modernity, it is now true that Data Science rules the masses, due to its all-explaining nature and commercial as well as innovative viability.

And Machine Learning is just a shadow of Data Science. To take your career as high as you can’t even imagine, you can become competent in both these fields, which will enable you to analyse a frightening amount of data, and then proceed to extract value and provide insight on the data.

Moreover, in many organisations, ML engineers and Data Scientists work together on products, so it is likely that you will be exposed to the Data Scientists’ perspective if you’ve already become an ML engineer. 

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So you have all the data now – who can learn machine learning, where to learn machine learning, how to start learning machine learning, as well as the best way to learn machine learning. It is up to you now to make the best of this data, and take you career to the next level!

Can someone be good at machine learning while being bad at math?

Statistics, linear algebra, probability, and calculus are the four essential ideas that drive machine learning. While statistical ideas are essential to all models, calculus allows us to understand and optimize them. You don't have to be an expert in mathematics to be good at machine learning. You cannot escape math when you want to be good at machine learning, but at the same time, you don’t have to be a pro at it. All you need to know are the fundamentals of arithmetic for machine learning, and you're good to go.

What skills are required to become a machine learning engineer?

The skills necessary to become a machine learning engineer vary depending on the domain. However, necessary skills for machine learning engineers include data science, computer vision, natural language processing (NLP), Python, deep learning, and machine learning. Seasoned machine learning specialists with 4-9 years of expertise earn competitive wages. To develop and manage machine learning models efficiently, the applicant must have an in-depth understanding of the machine learning lifecycle, tools, and newest advances. They should be able to lead a team of freshmen and junior engineers to fulfill the organization's machine learning goals.

What is the future scope of machine learning?

Artificial intelligence has given way to machine learning. Its goal is to make the difficult process of obtaining outputs from software applications more precise, which is extremely valuable to all businesses throughout the world. Making the outputs even more precise will undoubtedly be favored in the near future. Machine learning is used by every sector, from healthcare to entertainment, to improve their performance. As a result, the future of machine learning seems promising, with a wide range of applications.

What is the salary of a machine learning developer?

Salaries for Machine Learning Developers vary widely depending on a number of factors. These factors include the company the developer is employed by and the developing country. However, according to a survey conducted by Stack Overflow, the average salary for a Machine Learning Developer is $90,000 in the United States. The average salary of a machine learning developer in India is 9-10 lakhs per year. Machine learning developer salary depends on the experience, skill and the company. Salary of machine learning developers in India is increasing day by day because this skill is in high demand.

What skills are required to become a machine learning engineer?

As a machine learning engineer, you need to have a strong background in linear algebra, probability, statistics and calculus. A machine learning engineer needs to know how to work with huge amounts of data. So, he has to be comfortable with basic databases and data manipulation. He should also be proficient with programming languages like R, Python, Scala, C++, etc. Machine learning engineer needs to be a keen observer and have a good knowledge of statistics. Besides, he should be creative and have a knack for problem solving.


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