How Long Do Machine Learning Courses Take?

While Machine Learning classes are a recommended investment, many factors go into whether a course might be right for you. One of the most important is the time commitment. With a few exceptions, courses traditionally happen at a scheduled time, and not being able to get the most out of your experience because of other obligations can be highly stressful. As you look for a course, it is important to consider how much time is required, so that you can choose an option that aligns with your lifestyle, obligations, and proficiency. This article discusses the average length of different machine learning classes according to skill level, program type, and format so that you can make a more informed decision when choosing your ideal course.

Course Length by Skill Level

Machine learning courses are segmented by proficiency, and the content can differ drastically by level. In the beginner courses, you’ll be learning the fundamentals of artificial intelligence and machine learning. This includes topics like the history and modern uses of this technology, programming languages, and how to use machine learning libraries. Intermediate and advanced courses build on these skills, and introduce topics like algorithms and deep learning. You’ll also gain hands-on experience with developing advanced machine learning applications. The skill level is not the biggest dictator of program length, but it does have an impact, as more advanced opportunities are likely to be longer and more in-depth. Let’s have a closer look at the timeline for each below.

Beginner

In general, beginner courses are shorter than their advanced counterparts. The length of the course varies widely depending on program type and format, but in the earlier stages of your machine learning education, the topics covered can generally be done in a smaller frame of time. Beginner courses come as one-day classes that will teach a fundamental skill over a full day, short courses that generally range from 1-6 weeks, and free or self-paced online courses that can be taken at your leisure. There is minimal preparation required for the foundational courses. To keep up with the workload, short courses may require an additional 5-10 hours of studying outside of class for those unfamiliar with the content. One-day courses are unlikely to need any additional preparation. 

Advanced

Advanced courses can range in length from short courses of 1-6 weeks to specialized courses that last 3-6 months. It is rare for advanced or professional-level courses to only be one day, as advanced machine learning concepts build on fundamental skills. It’s easier to start with basic courses and move to advanced courses when time allows. The time commitment outside of class varies widely depending on the program type, but advanced students can expect to dedicate anywhere from 15-20 hours of additional study and practice outside of class to reach professional goals. On top of the 30-50 hours of instructional time that is common in higher-level courses, the time commitment is much steeper than with earlier proficiencies. It’s important to note that these numbers are also highly dependent on a student’s comfort with the content. For those transitioning from beginner to advanced courses, more studying may be needed than those who are already at an advanced level, but looking to refresh their skills, improve their credentials, or gain a certificate.

Course Length by Program Type

There are different types of machine learning programs. In this section of the article, we outline three of the more popular choices: university programs, certificate programs, and bootcamps. These programming types will dictate the content learned, the resources provided, and the average time commitment. Each option caters to different learning styles and career goals, ensuring that students can find a program that fits not only their specific educational needs but their schedules, too.

University Course

Machine learning in a university setting is often attached to a degree. This is significant for two reasons. First, this means that pre-requisite classes may be required, in which case students will end up committing additional time to maintain the proficiency needed for a degree. In the case that independent classes are offered outside of a degree track, students are still required to adhere to a curriculum, which will require additional time for homework and at-home projects in their free time. For those interested in taking University courses, they can expect their classes to last for an average of 3-4 months or the length of a full semester, 2-3 times a week. Independent classes may be slightly shorter at 4-6 weeks. Overall, university programs are rigorous and structured but more of a schedule commitment than other options.

Bootcamp

Bootcamps are intensive learning opportunities that are created to build up your professional skillset. This is particularly valuable in growing fields of technology like artificial intelligence and machine learning, where a portfolio of projects can help you stand out to potential employers. The average bootcamp runs anywhere from 8-12 weeks, with most of them offering 40-50 hours of in-class instruction. Classes may be offered full-time or part-time, with the schedule changing by institution. For full-time classes, students will meet regularly during the week. Part-time classes are generally more accommodating for those with other obligations, as they may be offered in the evenings, or during the weekend. Bootcamps are traditionally certificate courses, as you gain a certificate of completion upon graduation.

Certificate Course

A machine learning certificate course is slightly different, as it focuses specifically on certification. A certificate of completion is not considered certification, as certification is more stringent and standardized, overseen by an official or certifying body. Certification is an endorsement of your machine learning skills and can be a massive boost to your resume or portfolio. These classes range in length from 4-6 weeks. If certification is not available, certificate courses are often promoted as an alternative, and can range anywhere from 4 weeks to 6 months. These courses offer a certificate of completion at the end, which can be highly valuable when entering the workforce. Certification programs that are focused on test-taking may require additional studying outside of class which can contribute to a longer schedule, but overall, many of the essentials will be covered during the course. Due to the terms certificate course and certification course sometimes being used interchangeably, it is important to double-check whether an individual who completes the course is a certified professional, or only gains a certificate of completion.

Course Length by Format

Machine learning courses are offered either in person or online. In-person courses are especially valuable for learners who enjoy face-to-face interaction, and hands-on learning in a structured environment alongside their peers. Online courses are a good option for students who prefer to choose where they learn. If additional flexibility is needed, asynchronous courses also allow them to choose when they learn, as they are self-paced and done at the student's convenience. When considering the time commitment for a machine learning course, both in-person and online boast a separate set of benefits.

Online

When choosing an online course, starting with the program type can be useful in finding out the duration of the course. For example, a bootcamp that is offered both in person and online may include 40-50 hours of instruction. In-person, this may equate to attending class 3-4 days a week, whereas online, this may be self-paced. You can take the courses with the help of an online instructor through a platform like Zoom, or you can learn via modules and online assignments that can be taken at your leisure. Online Machine Learning courses offer a bit more flexibility than their in-person counterparts, which can greatly help those with other obligations but may extend the overall time required to finish a machine-learning course.

In-Person

In-person courses come with a fixed schedule. Classes meet at a specific time each week, which can be a big benefit for those who manage their time precisely. Similar to online courses, the exact duration is dependent on the institution and program type. For example, bootcamps that are promoted at 4-6 weeks are less likely to fluctuate because the class is set for a predetermined time. When choosing in-person or online, it is much more important to base the decision on your learning style and preferences, as the duration is more closely linked to the program type and the proficiency level. 

Learn Machine Learning With Noble Desktop

If you want to learn machine learning, Noble Desktop is an excellent place to start. Their general Python Data Science & Machine Learning Bootcamp teaches Python as it relates to data analysis, machine learning, and automation. Python is a common programming language in artificial intelligence which makes it a valuable asset in the field of technology. This specific class is two bootcamps packed into one. The curriculum covers Python for automation, data visualization, and interactive dashboards. This comprehensive course will build your confidence in programming so that you’re not only ready for entry-level positions in data science and Python engineering, but capable of creating predictive models from data, and automating everyday tasks.

For those who want a more streamlined learning experience, Python for Machine Learning is one option. The course starts with fundamental concepts like regression analysis, classification, and decision trees. 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 ends with a final portfolio project that helps turn theory into practice. Since you must be familiar with Python and a few data science libraries to comfortably take these courses, it is recommended that you join Noble Desktop’s Python Programming Bootcamp if you are unfamiliar. You can gain programming essentials that will allow you to comfortably manage your new machine-learning skills.

There is also the option of taking an artificial intelligence course, specifically Noble Desktop’s Generative AI with ChatGPT. This class covers AI in a fun and exciting way. This is a great way to see machine learning in action. ChatGPT is more relevant these days than ever, and this is your opportunity to contribute to one of this decade’s more popular artificial helpers. Through this course, you’ll learn how to write prompts in a way that generates helpful responses.