Are Machine Learning Bootcamps Worth It?

Machine learning is a rapidly growing area of artificial intelligence that allows a computer to learn and adapt without receiving explicit instructions. Essentially, with the help of algorithms and statistical models, the machine will analyze data and draw patterns, allowing the machine to learn from itself. In recent years, artificial intelligence and machine learning have changed technology dramatically, and it has become a highly sought-after skill in many prominent industries. If you want to learn professional machine learning skills fast, bootcamps are the way to go. Not only are they comprehensive and engaging, but they offer a large amount of relevant skills and resources without demanding too high of a time commitment. This article walks you through all of the benefits that a machine learning bootcamp can bring, and how they can help you secure your dream job in technology. 

Advantages of a Machine Learning Bootcamp.

From chatGPT to autonomous vehicles, the last few decades have shown us the endless possibilities of what machine learning can do. As businesses and industries fully lean into artificial intelligence, the demand for skilled machine learning professionals continues to grow, making machine learning a worthwhile investment. A bootcamp can accelerate your entry into any high-demand field by providing you ample opportunity to practice machine learning skills in real-world settings. Below are some key advantages of enrolling in a machine learning bootcamp.

Accelerated Learning

When looking for an intensive and focused curriculum, a bootcamp is the way to go. They often cover a range of machine learning concepts, from beginner to advanced. Beginner skills can be picked up in other course types, like a workshop, seminar, or one-time course, but those formats tend to focus on specific skills rather than offering a more comprehensive look at the field. Similarly, university courses, or other longer programs hosted by private companies, will review more advanced concepts but require a longer time commitment. One unique aspect of a bootcamp is its’ focus on professional development, and what happens after you leave the course. Essential topics are covered in a short period but with an additional goal of having you work-ready in mind, which allows you to quickly and efficiently gain expertise.

Networking Opportunities

Attending a bootcamp allows you to work alongside like-minded individuals. The peers in your course will become connections that can carry into your professional life. Bootcamps are also taught by industry professionals who can endorse your skills, write recommendations, and assist you with eventually obtaining a career. Certain bootcamps offer mentorship programs, and others do 1 on 1 training opportunities so that you grow connections with those of similar interests and goals. Bootcamps are highly collaborative. Teamwork not only enhances your overall experience, but it’s beneficial to career growth in the long run. The future of machine learning is collaborative, and having an active network of people who you can work with will give you a leg up as you transition into work.

Hands-on Instruction

Bootcamps are great places to experience project-based learning. They emphasize turning your knowledge from theory to practice by giving you plenty of projects to work on. This is especially relevant to students who are more tangible learners, and who pick up content better by doing. Coupled with the collaborative component of these courses, students can get a genuine feel for what work with machine learning might look like from a career perspective. Though bootcamps aren’t the only class types that have hands-on learning, they are highly recommended for those who are not only looking to learn by doing but who also want to maximize their schedules by learning with a highly intensive curriculum in a collaborative environment.

Portfolio Building

Though a portfolio is valuable for job seekers in any industry, this is particularly true of tech jobs. It acts as a simple tool for recruiters to assess your technical expertise. It’s a way to showcase your work to those who may not have worked with you before. Depending on how you approach it, a portfolio is also a bonafide way to stand out from the crowd when job hunting. Bootcamps do projects that are portfolio-friendly. At no extra time or cost to you, by the time you leave the course, you’ll have additional endorsements to take with you in the form of assignments, projects, and other collaborative works that demonstrate your practical expertise. Some bootcamps even offer advanced career support, like resume building, interview preparation, and job placement assistance.

Considerations for a Machine Learning Bootcamp

A bootcamp is just one of several possibilities when it comes to learning machine learning. There’s more to choosing a bootcamp than just a recommendation, it’s just as important to thoroughly research and evaluate all of your options. Plenty of factors go into making sure the class you choose is right for you. If you have a budget, other obligations, specific career goals, or a preferred learning style, those things should be taken into account before committing to a program. Additionally, considering a boot camp’s curriculum and resources can make a big difference in its value. Below, we review some of the considerations that might influence how relevant a course is to you so that you can feel confident in your choice to attend.

Course Cost

Depending on your course type, the cost of a machine learning class will fluctuate. Bootcamps are highly recommended for those looking to improve their professional skills without breaking the bank. These course types often cover a wide range of information, from fundamental skills to more advanced skills. Other course types, like university courses, may cover similar information but run a higher bill because of tuition, facility, and book fees. Shorter courses, workshops, and one-time classes may be cheaper but are highly specified and often miss the inclusive curriculum of a bootcamp. Technology-related bootcamps can run you anywhere from hundreds to thousands of dollars, with the average cost of a bootcamp being approximately $13,500. Though there are cheaper bootcamps offered, there are few standard bootcamps that fall below $1,000. For those programs with a higher price point, it’s worth checking whether payment options are available since financial aid is not regularly offered for this course type.

Course Length

Bootcamps range in length, with many falling between 2 and 6 months. This range is impacted by whether the student is attending full-time or part-time, with full-time courses generally running 1-3 months, and part-time running 3-6 months. Part-time courses are ideal for any students who have other schedule commitments like work, school, or other obligations. It’s important to check the expected changes between a full-time and part-time bootcamp. Though the curriculum will generally stay the same, class times may differ dramatically. Part-time courses tend to take place in the evenings or on the weekends, whereas full-time courses are more likely to occur during weekdays and regular school or business hours. Both class types are available in person and online. Classes vary widely by institution, so even if you have a unique schedule, there is likely one that can accommodate your needs.

Career Goals

Before taking a machine learning bootcamp, it might be worthwhile to sketch out overall professional plans and career goals so that you can pick a curriculum that matches. Despite many bootcamps covering general machine learning content, there are differences between institutions. Bootcamps are geared towards professional development, career growth, and those who intend to further their education at some point in machine learning or artificial intelligence. That doesn’t mean that those without career goals should avoid bootcamps. In fact, even if you are going into a non-tech field, an understanding of machine learning is a valuable skill to add to your repertoire, as its recent popularity has allowed it to stretch to many industries. Once you have an idea of your professional outlook, you can make a more informed decision on which bootcamp will best align with this goal in the long run. 

Learning Style

Bootcamps are generally fast-paced and hands-on. While that may be ideal for some learners, it can be incredibly overwhelming for others. For students who require a more gradual pace, taking a bootcamp may not be the most efficient choice. Other options might be better geared towards your learning style. Workshops are excellent at being engaging and interactive, while also keeping the content at a more digestible pace. Bootcamps are considered intensive. Some offer special amenities that can help with managing the content, which may range from 1 on 1 tutoring sessions, to mentorships, to additional resources that can further break down content.

What Will You Learn in a Machine Learning Bootcamp? 

Machine learning falls under the branch of artificial intelligence. It’s the process of getting a machine to learn on its own with the help of algorithms, statistical models, and data. When a machine can recognize and make sense of patterns, it can use them to further develop itself. A machine learning bootcamp is likely to cover a range of skills, from beginner to advanced. In the beginner levels, you’ll pick up basic programming skills, typically in Python, and learn more about machine learning libraries such as sci-kitlearn, NumPy, and Matplotlib. Algorithms and data processing are highly important too, so learning how to classify algorithms and handle data is a concept you’re likely to encounter.

Once you’ve reached the intermediate and advanced content in the course, machine learning can become much more complex. You’ll not only need to learn about algorithms but how to apply them so that the machine can learn from them. Deep learning is a primary concept you’ll be learning at this stage, and it refers to the use of a neural network to model complex patterns in your data. With deep learning, advanced applications can be developed. This includes virtual assistants, recommendation systems, and other advanced machinery. Topics at this level also include neural networks, classification, feature engineering, and distributed learning. Mastering these topics is vital to tackling more complex machine-learning problems.

Technical skills aren’t the only thing you learn in a machine learning bootcamp. Soft skills are extremely relevant to your success in artificial intelligence. Collaboration and communication are at the top of the list. As you move through your course, you will often work on projects that require input from several parties, and certain classes may have opportunities to present your work. Logic and critical thinking are also soft skills that students grow over time. This skill is incredibly valuable for data scientists and those who work with artificial intelligence. Given how quickly machine learning is expected to grow in the next decade, staying informed is critical, and taking a course can allow you to stay up-to-date in both technical and soft skills. 

Who Will Benefit from a Machine Learning Bootcamp?

Though bootcamps are available to everyone, certain individuals may find them particularly valuable. Recent graduates and those changing careers can use the class to prepare job-hunting materials, like a portfolio or resume. Hobbyists and tech enthusiasts might find a bootcamp valuable just for the diverse range of topics it covers. Because of programming and data used in machine learning, data scientists, coding experts, and other programmers might find a bootcamp valuable not only as a refresher for their skills in Python, Java, and other coding languages but as an introduction to something new that they can do with those skills. A bootcamp is overall a great way to your skill set and develop and supplement academic knowledge with professionally focused hands-on machine learning skills. 

Learn Machine Learning With Noble Desktop

Students who are looking to learn machine learning through a bootcamp can consider Noble Desktop’s Python Data Science & Machine Learning Bootcamp. In this course, you can learn more about algorithms, and how they are tied to data science and machine learning. With the help of linear and logistic regression, students can solve machine-learning problems. After going over theoretical algorithm concepts like k-nearest neighbors, decision trees, and random forest, you can quickly transition to statistical concepts like bias, variance, and overfitting. This bootcamp does require that students be comfortable with Python and its data science libraries, NumPy and Pandas, but those who would like additional practice with programming can join the Python for Data Science Bootcamp.

Noble Desktop offers a handful of efficient and affordable bootcamps. Their Python Machine Learning bootcamp is a great way to pick up programming specifically for machine learning. You’ll use the Pandas library to clean and balance data, apply machine learning algorithms, and pick up other important theoretical concepts, such as overfitting, variance, and bias. The course starts with fundamental concepts like regression analysis, classification, and decision trees. At the end of the course, students will have a final portfolio project that helps them evaluate the performance of machine learning tools. Between both bootcamps, students will have plenty of opportunities to learn more about machine learning, as well as fundamental skills in a related industry.