Why Should You Choose Machine Learning as a Career?
It’s fair to say that machine learning is taking over the world. A report from marketsandmarkets.com shows that the machine learning market is expected to grow from $1.03 billion USD in 2016 to $8.81 billion USD by 2022. In addition, Deloitte Global predicts that the number of machine learning pilots and implementations will double in 2018 compared to 2017, and double again by 2021.
These projections mean that there is also a growing demand for professionals who know the ins and outs of machine learning. If you’ve always wanted to enroll in a course that provides you with the practical knowledge to make your future brighter, now is the perfect time to learn machine learning.
Before getting into the different ways to learn machine learning, let’s take a look at the basics of machine learning, as well as the different machine learning types and applications.
Different Ways to Learn Machine Learning
Learn Machine Learning Through Self-Study or On-the-Job
Anyone who has a basic understanding of machine learning can sharpen their skills through online blogs and materials. There are also some great resources on YouTube, like this Machine Learning Playlist by Simplilearn, which provides excellent foundation-level videos. But the biggest drawback of learning through self-study is that it will take a lot longer to learn the basics, and you might end up making avoidable, but very costly mistakes. You also don’t get the opportunity to learn from and interact with industry professionals, not to mention find it difficult to manage your time when it comes to self-study as well.
Master Machine Learning Online
Enrolling in an online education program or taking an online course is one of the best ways to master machine learning. There are several online course providers in the market, and different modes of online study. You can opt for self-learning courses or virtual classroom courses, or those that blend the two. One of the main benefits of online learning is the flexibility it provides. You can learn at any hour of the day and when it is most convenient for you, unlike traditional classroom learning. Also, online learning can save you a lot of time, since you won’t have to travel to a physical location to attend classes. You do, however, need a good, stable internet connection. Depending on the specific program you enroll in, you may also get to interact with others online over video or chat sessions, which will further aid your learning and build connections.
Take a College Course or Earn a Full Degree
Learning at a university provides you in-person interaction with professors, but you won’t get the same flexibility in schedule that you would with online courses. Additionally, university degree courses are often not optimal when it comes to developing practical skills. This is because the focus is a lot more on the academic foundations, rather than interacting and working with industry professionals. And when it comes to enrolling in a college course, it usually means pursuing a two or four-year degree.
These days, succeeding in the technology industry doesn’t necessarily require a significant amount of higher education. Attending a technical school or receiving online certification is often more than sufficient. In fact, many industry professionals tend to agree that shorter, more condensed learning is actually better, because you are focusing solely on what you want to learn. This also means you finish your program much faster.
Benefits of Learning ML through an Online Course
A professional machine learning course is great when you are looking to achieve specific career goals in a short period of time. Focused courses geared toward various projects can teach you how you can apply machine learning in real life. Projects, like building a predictive model for housing prices, building a phishing website detector using LR algorithms or KNN algorithms, or building an MNIST Classifier (to classify a given image of a handwritten digit into one of 10 classes representing integer values from zero to 9, inclusively), provides curated content for professionals to upskill in those specific areas versus a broader education. University degrees also have a much longer, undefined return on investment, as they are not always geared towards specific goals.
It Saves Time
A machine learning certification course will generally take between one to six months to complete, depending on your goals. A degree from a university, on the other hand, can take up to four years or more. If you are looking to further your education with a professional degree, you are looking at more time on top of that. It’s questionable whether all these years in school are necessary when pursuing a career in ML, as a good certification course can often offer you all the skills you need to succeed.
Machine learning certifications don’t cost as much as university degrees for several reasons:
- The certification courses are shorter which reduces any operational costs considerably.
- Most renowned ML certification courses, like Simplilearn’s Machine Learning Certification Course, are entirely online, so students don’t have to worry about transportation or living expenses. Earning a university degree, on the other hand, often requires on-campus visits, which adds to the overall cost of education.
One huge advantage of receiving a machine learning certification is that most courses are available online, and you can study from anywhere if you have a good internet connection. Whether you’re at home, commuting to or from work, or are on vacation, online learning gives you the flexibility to learn anywhere, and on any device.
All renowned online certification providers rely on student feedback to determine which instructors are good and which aren’t. They use this constructive feedback to design and refine future education programs regularly. Experienced and knowledgeable professors with years of experience at a university may not offer the practical learning experience you’re looking for, or the personalized attention you’re seeking.
Online learning can help students harness their strengths and minimize weaknesses with focus on special projects, as well as labs and guided assistance through well-known teaching assistants, such as the ones that are provided in Simplilearn’s courses.
Popular Online Machine Learning Courses
Simplilearn’s Machine Learning Certification Course
Simplilearn’s Machine Learning Certification Course provides practical learning on machine learning concepts and techniques, including supervised and unsupervised learning, mathematical and heuristic techniques, and hands-on modeling to develop algorithms and prepare you for the role of Machine Learning Engineer.
A machine learning expert conducts sessions via live, online classes. Students also receive lifetime access to the self-paced learning modules. You can practice what you learn through four real-life industry projects. The education program also offers dedicated mentoring sessions from faculty who are also industry experts.
Learn the course here.
Coursera’s Machine Learning Course
This course is also a popular choice. It includes various concepts and in-depth knowledge on machine learning to offer students. However, you might have to compromise on hands-on exercises. You will likely find this course flexible and can schedule the classes according to your convenience, but students may not receive lifetime access to the study materials and instructor support.
edX’s Machine Learning Course
Columbia University offers this course through edX. You might find it more authoritative, but again, you might have to face the flexibility issues in terms of scheduling your classes as the university’s rules will impose certain restrictions. Also, you might not be able to interact with your instructor frequently, and you may be required to learn more academic concepts, rather than work on practical real-world projects.
There are many other providers of online machine learning courses, but the above are some of the most popular options. You can make your choice based on your learning preferences, your goals, and what options they offer.
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A Technical Journalist who loves writing about Machine Learning and Artificial Intelligence. A lover of music, writing and learning something out of the box.