Machine Learning is the use of Artificial Intelligence to let machines learn how to do a task without being programmed to do that task specifically. (In short, machines learn on their own without any help from people!) This process starts with giving them good-quality data. The data is then used to build different machine-learning models and algorithms, which are used to train the machines. The type of data we have and the type of task we want to automate will determine which algorithms we use. Now that we know the basics of Machine Learning, let's look at how this knowledge can be used to build a career.
Machine Learning is very popular because it saves people a lot of work and makes machines work better by letting them learn independently. Because of this, there are many popular and well-paying jobs in Machine Learning, like Machine Learning Engineer, Data Scientist, NLP Scientist, etc.
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Data Scientist: A Data Scientist uses advanced analytics tools, such as Machine Learning and Predictive Modeling, to collect, analyse, and make sense of a lot of data in order to get insights that can be used to make decisions. The executives of the company then use these to decide how to run the business.
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Machine Learning Engineer: A Machine Learning Engineer is an engineer who uses programming languages like Python, Java, Scala, etc., along with the right machine learning libraries to run different machine learning experiments.
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NLP Scientist: "NLP" stands for "natural language processing," which is the process of making machines understand how people talk. This means that one day, machines will be able to talk to people in their own language. An NLP Scientist's job is to help make a machine that can learn how people talk and translate what they say into other languages.
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Business Intelligence Developer: A Business Intelligence Developer uses Data Analytics and Machine Learning to collect, analyse, and make sense of large amounts of data. They then turn this information into actionable insights that company executives can use to make business decisions. In simpler terms, it means using data to help businesses make better decisions.
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Human-Centered Machine Learning Designer: Human-Centered Machine Learning is about Machine Learning algorithms based on people. Video rental services like Netflix are a good example of this. They let their customers choose movies based on what they like, giving them a "smart" viewing experience. This means that a Human-Centered Machine Learning Designer builds different systems that can use information processing and pattern recognition to do Human-Centered Machine Learning. This lets the machine "learn" each person's preferences without having to use complicated programmes that have to be adjusted by hand for every possible user scenario.
All of the above five careers require some serious skills. These include Programming, Probability, Statistics, Data Modeling, Machine Learning Algorithms, System Design, etc. You can find free coursesabout many of them at Glow & Lovely Careers (formerly known as Fair & Lovely Career Foundation).
