Where to Find Machine Learning Classes

Machine Learning is a rapidly growing field with plenty of unique job opportunities, but where are classes offered for those who are ready to take the plunge? There is a wide range of institutions that can provide training in machine learning. Whether you’re looking for professional development, or want to take your hobby to the next level, there is an institution for you. In this article, we review the most common places to find a machine learning class, as well as additional considerations that can help you choose the best course for you.

Professional Training Centers

Professional training centers specialize in a structured curriculum that can help you grow in your career. The curriculum is specifically geared towards professional development. As machine learning is a relatively new field and steadily growing with the help of the world’s technology boom, a professional training center is a good way to access the most up-to-date information while also growing your network. Classes in a professional training center are engaging, interactive, and hands-on. They may be offered as a bootcamp, short course, webinar, workshop, or other format. When choosing to attend a professional training center, there are a few things to consider. First, these centers are highly technical, as they are career-focused. This means that you are likely to learn subjects according to their relevance in the industry, rather than a big picture of machine learning. This does not mean that professional training centers will not give you a comprehensive education. Rather, while other institutions may introduce you to artificial intelligence at large, the history of machine learning, and a variety of other uses in modern-day technology, it’s more likely that courses taken at professional training centers will be more specific. Classes are generally shorter than those taken at other institutions, and they often require a commitment to a set schedule. With Noble Desktop’s Classes Near Me tool, you can easily find and compare different professional training centers to make a more informed decision.

Universities and Colleges

Higher education institutes are a perfect option for those looking to get a wider degree in artificial intelligence or machine learning. Universities and colleges offer comprehensive degree options like a Bachelors, Masters, or PhD. A degree can act as not only an endorsement of your skills but recognition of a more rigorous and in-depth understanding of the field. To take machine learning courses at the university level, there are often prerequisites that must be fulfilled, which can provide a more well-rounded understanding of the topic. There are similarities to this format and a professional training center, in that university classes are also highly interactive and hands-on. The projects done in these courses can be added to a portfolio for a smoother transition to the professional workforce. With that in mind, university courses are notably expanded in terms of content. When taking the higher education route, it’s important to keep in mind the time commitment attached to a full degree. Some colleges host independent courses that are a great alternative to full-time programming. These may still require admission to the university, so it’s important to double-check the requirements for attending beforehand.

On-Demand Learning Platforms

For the ultimate flexibility, consider an on-demand learning platform. There are machine learning courses available online that can match a more unique schedule, and take a bit of the stress out of the alternative options. On-demand learning platforms like Udemy, Coursera, and LinkedIn Learning, are all about comfort and flexibility. Many of the courses are self-paced and don’t require any strict time commitment. They run on video lectures, interactive quizzes, and hands-on projects, and at the end of the course, students are generally provided with a certificate of completion that can act as an endorsement on their professional documents. As these courses can be accessed at any time, from anywhere, they are ideal for non-traditional students who may have other obligations, like a full-time job, family commitments, or just a preference for a more relaxed learning style. When paying for an on-demand machine learning course, be mindful of whether a subscription fee or a bigger package is required to access the course.

Workshops and Networking Events

Workshops and networking events may be hosted by any institution. This includes professional learning centers, universities, or even private institutions. They are perfect for students who want to learn machine learning in a quick, palatable way. Because many of the courses offered through these events are short, they do not have the length required for a more comprehensive overview of machine learning. These classes are geared more toward those who would like an introduction to a specific part of machine learning or artificial intelligence. They are less of a time and money commitment and double as a way to meet community members and influential professionals. One-day events, or those that are meant to be taken over a short period, can be found during a workshop, seminar, or networking event. Platforms like EventBrite or Noble Desktop’s classes near me tool are perfect for locating these classes. When choosing this route, you’ll want to be mindful of any fees associated with any fees attached to the event, as these can quickly become more expensive than the full-time courses. This is especially true of conferences, where registration fees can be relatively costly.

Free Online Resources

Free online resources are great for beginner machine-learning enthusiasts. You won’t have to worry about shelling out extra cash just to pick up the basics. More than that, there is often a large community of learners and institutions behind free online resources, which can make them a valuable networking opportunity. That being said, intermediate and advanced are much more limited in terms of free resources. Learning upper-level concepts is much more efficient through a class. It’s also important to consider that online resources must be vetted by you. Some platforms offer free materials that are not properly vetted. It is the learner’s responsibility to ensure that the content is appropriate. Whereas in a course you are provided with quality content that is aligned with your proficiency, you are responsible for making sure the online resources you access work for you. 

Private Tutors and Mentoring

Though they cost a bit more money, private tutors are a great way to learn machine learning if you want materials that are built around your learning proficiencies and preferences. A private tutor comes with a higher price tag but can be taken as 1:1 learning, or small group learning that has been specifically tailored to your goals and learning outcomes. Private tutoring works best for those who need immediate and frequent feedback. Certain courses will offer private tutoring as part of their package, and costs are worked into the overall fees for the program. In addition to private tutoring, programs may offer a mentorship program, in which you can be linked with industry professionals and higher-level peers. A mentor will provide advice and guidance that can help you pick up machine learning essentials more quickly, and more than that, they can walk you through the ins and outs of machine learning in a professional setting.

Learn Machine Learning with Noble Desktop

Noble Desktop has a valuable Classes Near Me tool that is both an easy and efficient way to find machine learning courses in your area. If you’re looking for a bootcamp that can provide you with all of the machine learning essentials, Noble Desktop also offers Python Data Science & Machine Learning Bootcamp. With the popularity of Python in artificial intelligence and technology overall, you’ll be picking up valuable skills that are relevant in many industries. This course teaches algorithms and how they are tied to data science and machine learning. With the help of linear and logistic regression, you will become familiar with common machine-learning problems and will gain hands-on experience with solving them. 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. 

For those who want a more streamlined learning experience, Python for Machine Learning is offered as a standalone course. 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 the different bootcamps, students will have ample opportunity to pick up machine learning, while also gaining valuable experience in professional-level skills. You must be familiar with Python and its data science libraries, NumPy and Pandas, to comfortably take these courses. If you need assistance with getting those proficiencies, consider joining Noble Desktop’s Python Programming Bootcamp. It will provide a thorough overview of programming essentials that can be used to better Python and programming as a whole.