How to Become a Machine Learning Engineer Without a Degree in 2024

A Machine Learning Engineer is responsible for creating and maintaining artificial intelligence that automates tasks and analyzes data for businesses. You can explore different routes to becoming a Machine Learning Engineer, including options that do not require pursuing a traditional university degree program. By enrolling in bootcamps and certificates at reputable training centers, you will gain the relevant skills needed to navigate the professional world. You can ultimately achieve this goal by enrolling in practical, hands-on training courses, networking with current professionals, and staying focused throughout your learning journey.

Pros and Cons of Becoming a Machine Learning Engineer Without a Degree

Pursuing a Machine Learning Engineer career without a degree is entirely possible, but there are a few things to consider before deciding which path is best for you. These considerations may depend on personal preference, such as your learning style or schedule. In addition, you may have to factor in your budget and previous experience. Above all else, finding a reputable way to learn machine learning concepts without enrolling in an accredited university is paramount. Weighing these factors can help aspiring Machine Learning Engineers make a well-informed decision that will take them to the next step in their educational endeavors.

First, the advantages of becoming a Machine Learning Engineer are vast and something to heavily weigh. When choosing a learning method, you will likely consider affordability. Degree programs are incredibly costly, often requiring students to take out loans or seek financial aid in other ways. Other learning methods, such as enrolling in courses from a training center, will be far more cost-effective. Plus, you will still receive focused training and hands-on experience (perhaps even more so than a degree program, which will likely be a blend of practical and theoretical instruction). Not to mention this is an incredibly flexible method as the time spent in class is less frequent yet more rooted in realistic experience. The benefits offered in different training methods, such as mentoring, portfolio development, or job placement, are equally invaluable. Overall, this is a flexible and easily accessible way to learn machine learning practices.

However, there are some downsides to becoming a Machine Learning Engineer without a degree from a university. Firstly, the fast-paced curriculum from a bootcamp or certificate course may be challenging, particularly if you have zero previous experience. Although most training centers structure their curriculum for novices, this can present a challenge to overcome. In addition, you want to find a reputable training center over a hands-off method or low-cost method. This reduces the risk of learning inaccurate or outdated information, thus ensuring the quality and credibility of your education. Additionally, it may depend entirely on employer preference. If they consider hiring an employee without a degree risky, they will likely explore different options. Most of all, this method requires just as much determination as pursuing a traditional degree (if not more).

Learning Methods to Become a Machine Learning Engineer Without a Degree

Certificate Courses

One of the most common and effective ways to become a Machine Learning Engineer without a degree is to enroll in certificate courses in relevant fields. These are live classes, offered either in-person or online, that provide the most interactive experience possible. The lessons and projects are hands-on and immersive, with the intent to provide students with practical skills that can easily translate from the classroom to the workplace. Certificate courses are lengthy but take far less time than a degree program. Because they offer practical training as opposed to theoretical information, students will feel well-equipped to explore any potential job prospects. Noble Desktop is among the many training centers that offer credible, in-depth certificate courses that value professional development and career preparation. Notably, certificate courses award students with a verified certificate to show that they have acquired those professional skills.

Bootcamps

Bootcamps are similar to a certificate course but more broken up and can vary in levels. By joining a specialized bootcamp in data science or machine learning, you can gain the skills necessary to prepare you for a role in various industries. This learning method can be lengthy but is typically less so than a certificate course. Additionally, they are offered live in-person or online and can be found at training centers such as Noble Desktop. The structured curriculum allows students to focus on one particular subject or tool before moving on to the next bootcamp or certificate course. Just like a certificate course, the course is structured to offer students hands-on experience as well as additional benefits to develop their skill set.

On-Demand Classes

However, there are other options aside from live training. On-demand classes are hands-off, which means students will teach themselves the material. This self-paced method lacks the necessary interaction that makes certificates and bootcamps so successful, however, it affords students a lot more flexibility and accessibility. Students in on-demand classes will still have access to resources, such as chat boxes on the course provider website that can offer assistance and provide learning materials such as texts, video tutorials, and modules. They will also complete projects but have to answer all questions through additional research. On-demand classes are useful for many reasons, although it is questionable whether this method is sufficient to serve as a way to start a new career.

Independent Learning Through Free Tutorials and Seminars

You can easily develop machine learning knowledge through free resources either in-person or online. By exploring your local area, you can find libraries and career centers that may have ways to gain a foundation in machine learning practices. Additionally, you can find articles and blogs from reputable organizations online that provide more insight into the field. There are video playlists on social media platforms like YouTube or TikTok where Machine Learning Engineers can share their thoughts on the field, experiences while working, and advice on how to start. Likewise, you can join chatrooms and discussion boards to ask questions and receive feedback on previous work. Similar to an on-demand class, there is a time and a place to use free resources. However, these will not be enough to provide the professional-grade education required to start a career.

Apprenticeships and Internships

Apprenticeships and internships are an incredibly immersive and hands-on way to learn a new skill. As it suggests, you will work alongside a professional or a team of professionals to learn more about the day-to-day workings of a Machine Learning Engineer. Companies all over the country offer apprenticeships and internships, but they are relatively competitive and hard to acquire. This may be especially true if you live in a secluded area. However, this method provides students with networking opportunities that other learning methods simply cannot. You will receive direct exposure to the field, which is a bonus.

What is a Machine Learning Engineer?

A Machine Learning Engineer is a technical role that requires knowledge of artificial intelligence, mathematics, and data science. They are tasked with building and deploying machine learning systems that can automate tasks to make business operations easier. In addition, they manage those systems and continually update and enhance their models to maximize their efficiency. There are multiple skills a machine learning expert would have, including mathematics, analytics, coding, and communication. 

On an average workday, a Machine Learning Engineer will analyze data, develop models, and improve their previous systems. They will typically use their keen analytics skills to determine actionable insights that help make better decisions for the business. They will also document their progress to determine what collaborative efforts should be taken. Machine Learning Engineers work closely with similar professionals such as Data Scientists and Software Engineers.

Machine Learning Engineers can work in a traditional office setting and work on projects with others on the team or individually. However, they can also work remotely or in a hybrid setting, which requires some in-house work, such as attending meetings and other collaborative sessions. In addition, they can find freelance work and offer their skills to numerous clients for a short-term period. This career is expected to become increasingly necessary in the coming years as the reliance on data and technology grows.

Can You Really Become a Machine Learning Engineer Without a Degree?

It is entirely possible to become a Machine Learning Engineer without a degree from an accredited university. You can explore bootcamps and certificate courses that provide realistic experience in the field of your choice. With machine learning, this involves practicing through hands-on projects and learning from case studies. Although a degree in a relevant field, such as computer science, mathematics, engineering, physics, or even economics can provide you with a fully developed arsenal of skills relevant to the machine learning world, this is not the only way. A traditional degree is a structured path to the career of your choice, but you can explore different training options to make your professional dreams become a reality sooner rather than later.

Steps to Become a Machine Learning Engineer

You will want to take a few key steps to become a Machine Learning Engineer. First, you’ll want to sharpen your mathematical skills in subjects like linear algebra, statistics, calculus, and probability theory. You will also want to learn myriad programming languages, such as R, Python, and Java. Beyond the specific skills, you’ll want to understand the theory and fundamentals behind machine learning, such as neural networks and deep learning architectures. Above all else, you’ll want to find a reputable training method from which to learn these essential skills.

Taking individual classes, bootcamps, or certificate courses in machine learning is one of the best ways to learn these skills. Not only are they flexible and easily accessible, they provide students with practical experience that will translate easily in the workplace. Enrolling in online courses like those at Noble Desktop allows you to explore different topics, gain base-level skills in relevant subjects, and practice the day-to-day tasks of a machine learning expert firsthand. The hands-on projects you complete in class will give you a glimpse into the field, and you’ll feel supported throughout with the help of an expert instructor. You can choose between lengthy courses or short courses, as well as beginner and advanced levels. This is truly one of the best ways to learn because the courses are customizable to your needs and help you develop professionally.

Noble Desktop offers certificate courses, bootcamps, and short courses on myriad subjects relevant to machine learning. You can explore certificates in data science and generative artificial intelligence or bootcamps in specific coding languages such as Python. In addition, their short courses range in subject matter and are typically completed within a day or so. Noble Desktop also offers students different benefits such as payment plans and the choice between full-time and part-time instruction.

Learn the Skills to Become a Machine Learning Engineer at Noble Desktop

If you are interested in becoming a Machine Learning Engineer, there are many ways to start your journey. Notably, you can explore certificate programs at reputable training centers such as Noble Desktop. Their Data Science Certificate covers all the necessary skills to become a data science professional, which is the field where machine learning practices are regularly applied. Specifically, students will learn relevant coding languages, automation, machine learning, data analysis, and predictive modeling skills. Throughout this 114-hour course, students will learn how to clean, balance, and apply machine learning algorithms to data sets with scikit-learn. In addition, they will practice analyzing data with Python libraries like NumPy and Pandas. By the end of the course, students will be able to automate everyday tasks and utilize their skills in the data science field. Noble Desktop provides students with additional benefits to support them through their learning journey. In this course, students can access 1-on-1 mentoring sessions, a free retake, and various payment plans. Upon completion, they will earn a verified digital certificate that displays their mastery of the material.

Likewise, Noble Desktop offers a Software Engineering Certificate where machine learning skills and relevant information will be discussed. In this certificate course, students will learn to use Python and Django for machine learning algorithms and task automation. In addition to Python, they will learn to build the front end of a webpage with HTML, CSS, and JavaScript, which all add interactive functionality. This course also gives students the exposure and experience they need to develop a professional portfolio with their completed projects. Over 510 total hours, students can access myriad benefits like a course retake, bonus mentoring sessions, and an additional elective course, all at no extra cost. Once the students complete the program, they will earn their verified certificate to show for all their accomplishments.

To gain more knowledge of artificial intelligence for business purposes, consider the Generative AI Certificate from Noble Desktop. In this 78-hour course, students will learn how to utilize artificial intelligence in different work settings and for varying reasons. For instance, students will learn how artificial intelligence can help automate workplace tasks or quickly analyze large data sets. The instructor will guide students through projects that leverage artificial intelligence for different marketing strategies and help create high-quality marketing designs. This course does not require any previous coding experience and is solely meant to delve deeper into the larger implications of artificial intelligence and its usefulness in the workplace. Through hands-on projects, students will gain the necessary experience to apply the skills in their field. Students can retake the course anytime within a year of their original enrollment at no additional cost. Plus, Noble Desktop will award students with a digital certificate once the course ends.