Data Science Careers: How to Specialize in Machine Learning

More products and applications are implementing machine learning at their core. With it, they can be able to accurately predict outcomes without being specifically programmed to do so.

Some common use cases include virtual assistants, image recognition, fraud detection, etc.

Several high-profile companies are investing in machine learning research and are creating more solutions with it.

Machine learning engineers, data scientists, and software engineers are topping the list of most in-demand IT professionals. So, it’s a really good idea to specialize in machine learning. 

What Is Machine Learning?

Machine learning is a subset of artificial intelligence. It is focused on teaching machines to learn from data and improve with experience rather than programming them for specific tasks.

They are often fed with good quality data before being trained by various machine learning models using the data and different algorithms. 

There are so many applications of machine learning around us. For example, social media algorithms capture your data and use it to customize your social media feeds.

Amazon and Netflix also use machine learning algorithms to learn our shopping or viewing preferences to recommend products or shows you may like. 

Why Specialize in Machine Learning? 

Machine learning engineers are more sought after than data scientists who identify as generalists.

When it comes to building AI-driven products, most companies would not hire someone who simply studies data and tries to extract insights from it.

They would prefer ML specialists who build models that can use data to learn by themselves.

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According to Forbes, the demand for AI and machine learning skills is growing at a 71% compound annual growth rate through 2025 with over 200,000 positions open today.

And opportunities for machine learning engineers will keep increasing as more businesses continue to implement machine learning in their applications.

What Are the Skills Required to Become a Machine Learning Specialist?

Machine learning engineers are those who design and build artificial intelligence systems and algorithms that can learn or make predictions without further programming.

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This career is ideal for those who are naturally inclined towards mathematics (linear algebra and multivariate calculus), statistics, and coding. 

The responsibilities of an ML specialist vary but you’ll mostly need technical skills (Applied mathematics, Neural Network Architecture, Data Modeling and Evaluation, etc) and programming skills (software engineering and system design, machine learning algorithms and libraries, distributed computing, etc.).

How to Specialize in Machine Learning

Artificial intelligence is the broad science of mimicking human abilities while machine learning is a subset of AI that teaches machines how to learn.

There are several job titles in this field namely, AI Engineer, ML researcher, ML engineer, data analyst, data scientist, BI developer, etc. If you want to specialize in machine learning, here are the exact steps to follow…

Learn how to code.

Machine learning specialists need a lot of coding knowledge and skills. They are often responsible for developing software-based systems and creating automation tools or algorithms to improve the systems.

So, they have to know software architecture and development as well as specific coding skills like C++, Python, R, Java, and SQL. 

Machine learning engineers should know how to work with large datasets and find useful meaning in data.

They need to know how to manage SQL and non-SQL databases as well as big data tools such as Spark or Hadoop.

Other essential programming skills include Apache Kafka, Weka platform, and Matlab or Octave. 

Sharpen your math skills. 

Machine learning is all about algorithms and good math skills are a must-have. Before you learn machine learning, it’s necessary for you to understand linear algebra and multivariate calculus.

They come in handy whenever you must implement ML algorithms from scratch.

Data is also very important in machine learning. As an ML engineer, statistics would help you handle the collection, analysis, and presentation of data.

So, you need to learn various concepts in statistics like statistical significance, probability distributions, regression, hypothesis testing, etc.

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Get a certificate in machine learning

A quick way to get a formal qualification in machine learning is to complete a machine learning certificate online.

It can equip you with skills necessary for building machine learning algorithms such as machine learning system design, unsupervised learning, recommender systems, large-scale machine learning, etc.

An online certificate in machine learning can be completed in less time than a degree. However, you should have some coding skills before enrolling in a machine learning certificate program.

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It’s easier to grasp these technical and programming concepts when you’re already a developer, data scientist, or software engineer. 

If you prefer a degree

If you are new to programming and technology, then a certificate in machine learning may not be best for you.

You can start with a bachelor’s degree in data science, mathematics, or computer science. This will help you learn applied mathematics, statistics, physics, and other basic knowledge. 

Then, you can choose to specialize in machine learning by getting extensive technical training or a master’s degree in computer science, data science, or machine learning.

Degrees can help you go from a total newbie to a machine learning specialist.

Take part in competitions and bootcamps. 

Machine learning bootcamps can help you master the advanced and complex technologies in machine learning within a short while.

They offer flexible learning so you can learn online from the comfort of your home or on campus with other students. Some bootcamps may also offer financing options and career support.

Once you have acquired the necessary knowledge and skills in machine learning, it’s time to take part in competitions.

They can help to enhance your machine learning skills and you can also add the projects you completed to your portfolio. Some machine learning competitions include – Titanic and Digit Recognizer.

Get on-the-job training. 

If you’re quite proficient in machine learning, you should apply for a machine learning position. You can find some opportunities on job boards in your area or generalized online job search sites.

But if you prefer specialized sites for tech jobs, the ML Conf Job Board, Dice, and Harnham are great. 

If you already work in data science or a related field, like computer science, chat with your line manager about your desire to specialize in machine learning.

The company may provide training and sponsor any studies to help you achieve that.

Jonathon Spire

Jonathon Spire

Tech Blogger at Jonathon Spire

My diverse background started with my computer science degree, and later progressed to building laptops and accessories. And now, for the last 7 years, I have been a social media marketing specialist and business growth consultant.

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Jonathon Spire

I blog about a range of tech topics.

For the last 7 years I have been a social media marketing specialist and business growth consultant, so I write about those the most.

Full transparency: I do review a lot of services and I try to do it as objectively as possible; I give honest feedback and only promote services I believe truly work (for which I may or may not receive a commission) – if you are a service owner and you think I have made a mistake then please let me know in the comments section.

– Jon