Recently, we wrote about how to launch a career in machine learning, and we also explored how to become a machine learning specialist. Here we’re going to explain what makes machine learning so important to the modern economy.
During this discussion, we’ll review what machine learning is, how and where it’s being applied in modern business operations, what machine learning experts actually do, and why you should consider getting into the industry.
After you’ve learned everything you need to know about what makes machine learning so important, fill out our information request form to receive additional details about CSU Global’s 100% online Master’s Degree in AI and Machine Learning, or if you’re ready to get started, submit your application today.
What is Machine Learning?
You can think of machine learning as a subset of artificial intelligence technologies, as it involves training a machine to learn more quickly and more intelligently.
Where AI technology focuses on mimicking human intelligence, allowing computers to learn from experience, machine learning focuses on making them learn more, and faster, from that experience.
In a way, machine learning is like an optimization process for AI technologies, with the machine learning engineer being responsible for providing better, faster training to AI solutions.
The goal of the machine learning process is to make AI solutions faster and smarter so they can deliver even better results for whatever task they’ve been set to achieve.
Because AI technology is capable of having such a huge impact on society and modern business practices, revolutionizing everyday tasks from planning to logistics to operations and production, machine learning experts are in extremely high demand.
What Makes Machine Learning So Useful?
Machine learning technology is now necessarily new; machine learning algorithms have existed for years, but machine learning processes have recently taken prominence due to several important technological improvements, including:
- Wider access to large volumes and varieties of data, especially the development and ubiquity of “big data”.
- Much more affordable data storage solutions, which helped make big data sets available to more organizations and for a much wider variety of applications.
- Increasing processing power that allows computers and specifically AI applications to complete calculations much faster than ever before.
These developments set the scene for machine learning to produce much better results than it was historically capable of providing, allowing machine learning applications to provide value to virtually every industry and business activity.
Anywhere that AI systems are being used, machine learning experts will be needed to help improve the results of that AI technology, and as we covered in our recent post on what makes AI so important, there’s a whole host of applications for these transformational technologies.
Where is Machine Learning Technology Being Applied?
Machine learning has already found application across a huge variety of tasks and is especially important for any application that involves collecting, analyzing, and responding to large sets of data.
Because machine learning has such a wide range of applications, you’re almost certainly already interacting with it, whether you’re aware of it or not.
Here’s a handful of specific applications where machine learning has proven to provide excellent results:
- Healthcare - Machine learning solutions are being used to help medical professionals detect the presence of diseases, and machine learning processes are also used to detect emotional states via smartphone data.
- Retail - Machine learning technology powers Amazon’s “You May Also Like” suggestions, and machine learning processes are also behind Netflix’s recommendation algorithm.
- Manufacturing - Machine learning helps manufacturers reduce process-driven losses, increase capacity by optimizing the production process, and reduce costs by guiding predictive maintenance.
- Banking & Finance - Banks and financial institutions utilize machine learning to detect and prevent fraudulent transactions, and to identify insights in financial data, allowing them to find better investment opportunities, advise investors about when to trade, and provide other important insights related to financial matters.
- Transportation - Both Google and Tesla’s self-driving cars are powered by machine learning technology, including deep learning which allows them to interpret, predict and respond to data critical for autonomous driving.
It’s clear that machine learning has been applied across a wide variety of industries, but there are still untold numbers of opportunities for machine learning technology to improve operations in virtually every sector of the modern economy.
The reason that machine learning is such an important field is that machine learning technology allows AI systems to make faster and better decisions.
What Do Machine Learning Engineers Actually Do?
Machine learning engineers are responsible for designing, building, testing, and updating AI and machine learning systems and technologies.
Accordingly, some of the more common responsibilities that machine learning specialists must be capable of handling include:
- Understanding, analyzing, and applying machine learning principles for reasoning processes and uncertainty.
- Utilizing machine learning to perform image analysis and reconstruction tasks.
- Solving a variety of complicated problems and scenarios by implementing machine learning and AI-driven solutions.
- Designing and building machine learning and AI-based solutions to perform complex tasks that model and improve upon typical human behavior.
- Devising and building complex problem-solving solutions that use machine learning principles and AI best practices.
- Evaluating and improving applications that rely on machine learning and AI processes.
This is a complex discipline that requires a great deal of technical expertise, but because the job prospects for machine learning experts are excellent, it’s a great time to consider launching a career in the industry.
Should I Pursue a Career in Machine Learning?
There are several good reasons to consider getting into machine learning.
First, machine learning technology is becoming ubiquitous, with so many potential applications that you’re virtually guaranteed to be able to find something you’d be interested in doing once you’ve developed the necessary skills and abilities.
Second, the machine learning industry and demand for machine learning experts is projected to grow rapidly over the next decade, with Forbes estimating that the global machine learning market will grow by 44% between 2017 and 2024, reaching $20.83 billion in 2024.
Finally, jobs in the AI and machine learning industry tend to pay excellent salaries, with data from the U.S. Census Bureau showing that the average salary for AI professionals is $102,521.
Some of the top positions for AI experts and machine learning specialists that offer an excellent average annual income include:
- Computer and Information Research Scientists / 2020 Median Pay: $126,830
- Software Developer / 2020 Median Pay: $110,140
- AI Engineer/Scientist / 2018 Median Pay: $99,998
If you’re interested in technology and you want to get into a field that has the potential to earn an excellent income, then machine learning may be the perfect option for you.
How To Launch a Career in Machine Learning
You may be able to land an entry-level role in the industry without a degree, but you’ll likely have a much better chance of getting a good job if you first attend and complete a degree in the field.
The best way to develop the skills, knowledge, and credentials you need to get a good job in this competitive space is to study machine learning in a serious academic setting, like CSU Global’s online Master’s Degree in AI and Machine Learning program.
Our program provides all the experience and knowledge you need to launch a successful, lifelong career as a machine learning specialist, along with the academic credentials you’ll need to convince hiring managers that you’re prepared to provide value to their organization from day one.
Studying at CSU Global ensures that your degree will be respected, and earning your Master’s in Machine Learning should help increase the odds that you can land a management or leadership role in the industry.
Can I Get My Machine Learning Degree Online?
Yes, you can get a regionally accredited online Master’s Degree in AI and Machine Learning from CSU Global.
Our accelerated online degree program was designed to be completed entirely online, and it will provide you with far more flexibility and freedom than a traditional in-person program.
Studying online with us will make it easier to juggle your educational pursuits with other existing work and family responsibilities since our entirely online program offers:
- No requirements to attend classes at set times or locations.
- Access to monthly class starts.
- Accelerated, eight-week courses.
If you’re looking for a convenient degree program that interferes as little as possible with your other responsibilities, then you should choose to study with us.
Why Should I Pick CSU Global’s Machine Learning Program?
Our online AI & Machine Learning Master’s Degree program is an excellent choice for anyone looking to pursue a career in this exciting and growing field.
This program is regionally accredited by the Higher Learning Commission and widely respected by industry professionals, while CSU Global itself is recognized as an industry leader in online education, having recently earned:
- A #1 ranking for Best Online AI Degree from Successful Student.
- Named to Analytics Insight's list of Top Online Masters Courses for Artificial Intelligence in 2021.
- A #3 ranking for Best Colleges in Colorado from Best Value Schools.
- A #3 ranking for Best Value Online Graduate School from Value Colleges.
To get additional details about our fully accredited, 100% online Master’s in AI and Machine Learning program, please give us a call at 800-462-7845, or fill out our Information Request Form.
Ready to get started today? Apply now!