While artificial intelligence (AI) is the broad science of mimicking human abilities, Machine Learning is a specific subset of AI that trains a machine how to learn. Although many Machine Learning algorithms have been around for a long time, the ability to automatically apply complex mathematical calculations to big data – over and over, faster and faster – is a recent development.
Machine Learning is the shining star of the moment. Its global market is projected to grow from US$7.3 billion in 2020 to US$30.6 billion in 2024, attaining a CAGR of 43%. It’s made possible the invention of self-driving cars, practical speech recognition, effective web search, and a much enhanced understanding of the human genome in the last decade. This technology is now so common that you probably use it dozens of times a day without even realising it.
Most industries working with large amounts of data have recognised the value of Machine Learning technology. By gleaning insights from this data – often in real time – organisations are able to work more efficiently or gain an advantage over competitors. Some of the industries that have adopted this technology include the public sector, e-commerce, healthcare, finance, oil and gas and so forth.
The most visible example of Machine Learning in action is arguably Facebook. The platform’s account holders are all too aware of the adverts that are aimed directly at them for everything they do. It’s not just on Facebook. You’ll soon see an ad for that item on your Facebook account if you buy something or even search for it on Amazon.
As big data continues to expand and grow, the demand for data scientists will increase. Studying Machine Learning opens a world of opportunities to develop cutting edge applications in various areas, such as cybersecurity, image recognition, medicine, and face recognition. If you are in search of the most in-demand and most-exciting career in the next few decades, a degree specialising in Machine Learning is a good start.
What you will learn
A degree in this field typically covers how to develop self-learning computer systems by combining algorithms and statistical models. Without accepting instructions from programmers, these computer systems do tasks based on data and self-generated feedback (trial and error).
Several programmes in Machine Learning take a generalist approach. This means that students are exposed to a variety of topics such as robotics, linguistics, natural language processing (NLP), computer vision, programming, software design, signal processing, speech recognition and more.
After completing the programme, you may apply for entry roles in positions such as Data Scientist, Computer Vision Engineer, Machine Learning Engineer, and NLP Engineer. According to SimplyHired.com, the average Machine Learning engineer annual salary is US$142,000 and an experienced machine learning engineer can earn up to US$195,752.