Having one of these in your resume can make a lot of difference.
Data science is one of the most versatile fields ever around; even its name is not very explanatory of what the field actually involves. Perhaps that’s one reason people find this field quite challenging and difficult to get into and even more difficult to show professionalism.
It is well known within the data science community that to be a “good” data scientist is all about how strong of a portfolio you build, how diverse your projects are, and how well they show your ability to solve any problem creatively and efficiently.
Although being a data scientist — or have a specialty in any of its branches — doesn’t require a university degree, having some certificate that proves your profession in some aspects of the field can transform your portfolio and take your career on step further.
This doesn’t only apply to the field in general, but also to all its branches. Perhaps the most famous branch of the field is machine learning. Machine learning is everywhere in our lives now, in our computers, phones, even kitchen appliances.
But just like data science, the term machine learning is an umbrella for som many algorithms and techniques, so how can you show your future employer that when you say “I am a machine learning expert,” you actually mean it?
Some companies and universities designed tests and courses that if you pass, you know how to navigate yourself in the sea of machine learning, and hence, you’re ca[able to solve any problem anyone can put in front of you. This article will cover the top 6 machine learning certificates that you can pursue this year and elevate your portfolio and chances to land your dream job.
The first certificate on this list is offered by MIT. The professional certificate program in machine learning and artificial intelligence is a short program offered to people with previous machine learning knowledge and newcomers, giving them the ability to gain the latest knowledge in the field.
This certificate is not cheap — $325 to register for it — because it’s not just a test, rather a full set of courses and materials. This short program’s core focuses on using machine learning algorithms and techniques in big data and text processing. But, if you want, you can extend the scope of the certificate — for extra fees — to cover more precise usage of machine learning, such as machine learning in the medical field, or computer version, or efficient deep learning, etc.
Each of the courses in this short program has a set number of days that you need to complete them, and the entire program courses need to be completed within 36 months of registering for the program.
The machine learning course and certificate offered by Stanford University is perhaps the better option for those who want to get into machine learning and earn a certificate at the same time. You can either audit the course for free or pay $79 to obtain a certificate upon completing the course.
This course is one of the most famous and wholesome machine learning courses you could come by; it is taught by professor Andrew Ng one of Coursera’s founders and an instructor with more than 10 million happy students. The machine learning course alone was taken/still by almost 4 million students. The course also offers subtitles in 10 languages for students whose English is not their first or preferred language.
During this course — 11 weeks — you will learn everything from the absolute beginning, covering maths and statistics to machine learning algorithms’ fundamentals and their application in computer vision, medicine, audio manipulation, and database mining.
Another certificate you can earn by taking a course on Coursera is the machine learning professional certificate offered by one of the computing industry legends, IBM. Like the Stanford University course, you can audit this course for free or earn a $39/ month certificate.
This professional certificate program includes 6 courses covering all the knowledge you need to understand both the theoretical aspects of machine learning algorithms and their practical uses. Although you may make more of the course if one has some programming knowledge, you can still take this course even if you don’t know much programming.
This course will also teach you how to use Jupyter notebooks and IBM Watson to build and develop your own projects to add to your portfolio once you have completed the course.
The final course-based certificate in this list is the machine learning certificate offered by Harvard University on edX. This course is a part of a bigger, broader data science certificate offered by Harvard University. You can either audit this course or earn a certificate upon completion for $99.
This course will cover the basics of machine learning, the basic algorithms, and techniques, how and when to use cross-validation, how to build a recommendation system, and some of the commonly used, most popular, and new machine learning algorithms.
This course is designed to be completed within 8 weeks. However, it is also self-paced, which means you can take however amount of time you need to finish this course and earn your certificate.
So far, all the certificates we covered required a specific course or a set of courses to be completed to earn the certificate. The professional machine learning engineer certificate by Google is different. This is just a certificate, meaning you need only to take a test to obtain this certificate.
For $200, you can take this Google test to measure your familiarity and ability to frame machine learning problems, design solutions, process data, and develop machine learning models. Not just that, you also need to show that you can automate efficient machine learning pipelines and optimize your solutions.
Although this certificate is not accompanied by a course that you must take to earn the certificate, Google still offers materials that you can use to prepare for the test as well as webinars given by Google experts to help you pass that test and make the most of the provided materials.
A more specific certificate is offered by Amazon, in particular the AWS system. The AWS certified machine learning is a certificate designed to measure one’s ability to design, develop and deploy machine learning models using the AWS cloud. This certificate can be obtained with a fee of $400.
Similar to the Google machine learning engineer certificate, the AWS certified machine learning specialty doesn’t require a specific course completion to obtain. This certificate is aimed more towards people who are very familiar with machine learning algorithms and techniques rather than complete beginners.
The test is available in three languages, English, Korean and Chinese. Amazon also offers some materials and practice tests that you can use to prepare for the test and pass it from the first try.
Showing profession in any field is not easy; it gets even harder when the field you’re trying to prove profession in is a diverse broad field with so many branches and techniques. Machine learning is one of the famous tech fields out there that covers more than just programming; it requires math, problem-solving skills, and even communication skills.
So, how can you prove your capabilities to your employer? Although having diverse, strong projects in your portfolio speaks loud of how capable you are, having a certificate from a top university or industrial company can be the aspect of your portfolio that leads you to land the job.
In this article, I presented you with 6 certificates designed and developed to test one’s ability to tackle and find solutions to the most complex machine learning problems. They prove that you know how to use different algorithms to solve different problems and determine the most appropriate algorithm for any given problem.
Going the extra mile to study and get these degrees will defiantly pay off the next time you apply for a job and even during the job interview. After all, good efforts always pay off if they are combined with patience and perseverance.