Speedy Mentors       2 yrs ago

Machine learning has come a long way from being a tech buzzword to a critical solution to many of the world’s pressing issues. Due to that, people with machine learning expertise are becoming more and more in demand across industries. That makes machine learning an excellent career path to take. However, to get ahead of the competition and secure a job where you can work with artificial intelligence or smart machines, you need to set yourself up with the right skills. This article will tell you how to do that.

Understanding Machine Learning

Before discussing how you can start building your machine learning expertise, it is good to understand what the field is all about.

Machine learning is critical to the development of artificial intelligence. Through the discipline, the algorithms used to make smart machines are created. Those algorithms process large volumes and complex data, identify patterns and make decisions with minimal human intervention. Popular machine learning samples include image and speech recognition, virtual personal assistants, self-driving vehicles, traffic predictions, and email spam and malware filtering. 

Due to the numerous applications of machine learning, it is now adopted by several companies into their operations to help them make better business decisions. That includes tech giants like Google, Apple, Netflix, eBay, and Facebook. Also, recent research has shown that 80% of companies using machine learning and AI have reported a significant increase in their revenue. That proves the discipline’s effectiveness in addressing a wide range of problems.

Machine Learning Careers and Outlook

With the tremendous interest of companies in machine learning comes the increased need for people knowledgeable and skilled in the discipline. As such, there are plenty of opportunities for those interested in algorithms, data, and automation. That includes roles such as: 

• Data scientists

• Machine learning engineers 

• Machine learning specialists

• Computational linguists

• NLP scientists

• Software developers 

• Business intelligence developers

Demand for machine learning experts is driving salaries in the sector to the roof. Even entry-level machine learning engineers are being offered top-notch salaries. Payscale noted that, on average, entry-level machine learning engineers could make as much as $93,575 annually, with some companies even paying well up to $100,000. On the other hand, more experienced machine learning engineers receive about $155,000 - $200,000 a year.

Irrespective of the role, the career outlook in the machine learning field is bright. The World Economic Forum noted that AI, Machine Learning, and Automation will enable the development of 97 million jobs worldwide by 2025. With that, it is safe to say that there is no better time to start a career in machine learning than today.

Building Machine Learning Expertise

An essential requirement that can help you land a job in machine learning is a background in computer programming, software engineering, computer science, deep learning or robotics. Beyond the commendable academic experience, you also need to know how to gather data, create and use algorithms to process data, interpret results, and use those results to bring value to companies. Bringing all these skills together requires time and a lot of work on your part. Here are some things you can do today to build your machine learning expertise and position yourself effectively for a machine learning career.

Develop an in-depth understanding of machine learning

Although this one might be obvious, it is still a point worth mentioning. Knowing the fundamentals of machine learning, especially the mathematics, principles, and tools behind it, will be a good foundation for understanding the discipline’s more complex topics. With that, you will know how it works and how you can apply that technical understanding to real business problems.

Brush up on your programming skills

Programming is the cornerstone of machine learning. Algorithms developed through the discipline are implemented, monitored, and optimised through programming. It is a must that you demonstrate proficiency in various programming languages, particularly Python, C++, and Java which are widely used in machine learning. 

Other programming languages such as R, SQL, Scala, Julia, and MATLAB are also important, especially when dealing with volumes of data, complex math operations, and manipulating databases. If you are already familiar with some of these, it is a good idea to polish up on your skills to understand the inner workings of a product, collaborate across different teams, and identify problems in data as soon as they arise.

Work on personal machine learning projects

One of the best ways to build your machine learning expertise is to create real-world projects. Doing so will allow you to translate your theoretical and technical knowledge into practical experiences, giving you more insights into the discipline and your capabilities. 

Scikit-learn, Awesome Machine Learning, PredictionIO and other similar resources are great places to find basic projects you can recreate and review. Once you know how to apply machine learning concepts and practices, you can take things a notch by conceptualising the projects you can add to your portfolio. Some project ideas you can try include stock price prediction, object detection, sales forecasting, and movie recommendations.

It is good to start with simple data sets and algorithms when working on a project. That way, you will work on things according to your pace. At the same time, you can build a solid foundation that will effectively support your development as you work on more extensive and more complicated projects.

Seek work experience opportunities

Although personal projects are great additions to your resume, they are not enough to develop machine learning skills and experience that employers want. To gain that, look for work experience opportunities, such as internships or volunteer work. Many companies these days are opening up machine learning roles for entry-level candidates, especially those in the fields of tech, healthcare, finance, and more. However, you have to be prepared for the challenging application process, as many other candidates are likely vying for the same opportunities you are targeting.

If you find it challenging to look for internships and volunteer work, you might want to consider participating in bootcamps as an alternative. These are short yet intense training sessions designed to prepare you for the realities of machine learning. The beauty of bootcamps is that many of them are a complete package, offering a combination of training, work experience, and job search support. With those features under one roof, you can build your theoretical knowledge, access opportunities for gaining relevant experiences, and receive support to land a role in the industry.

Get a mentor

Nothing beats learning from someone with professional experience in machine learning. So if you can, find a machine learning expert who can act as your mentor. A mentor can help focus your efforts on the right areas by assisting you in setting goals, pointing you to the right resources, and giving you constructive feedback. They can give you specific insights and information about the industry and the roles you can pursue since they have already experienced the realities of machine learning. On top of that, the best mentors have built extensive networks and strong relationships with other professionals in the industry. That means they know exactly what employers want in candidates and can even connect you with people who can help move your career forward. 

If you are ready to work with a machine learning mentor but do not know where to find and how to approach one, we encourage you to join Speedy Mentors today. The platform is an excellent place to find a mentor in your preferred industry, including machine learning and data science. You get to choose the machine learning mentor you want to connect with and receive their guidance and support as you try to start or grow your machine learning career. All mentors on the platform have been carefully vetted, ensuring their ability to provide the best level of support you require.