Earning a machine learning (ML) certification can propel your career forward in a field that is ripe with opportunities to advance. In fact, the demand for AI and ML jobs is expected to grow 71 percent in the next five years. This makes sense given the fact that the machine learning market is predicted to grow from just over $21 billion USD in 2022 to nearly $210 billion by the year 2029.
The Jefferson Frank Salary Survey found that 84 percent of surveyed professionals perceive certifications as helpful for standing out in a competitive job market.
A machine learning certification is a credential that you earn by taking an exam or completing a series of courses. Obtaining certification demonstrates to employers that you possess theoretical and practical understanding of algorithms.
Also read: What are the Types of Machine Learning?
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AWS Certified Machine Learning – Specialty is designed for those who have least one year of experience in development or data science and want to prove their expertise in creating, training, refining, and deploying machine learning models on the AWS Cloud.
In the Jefferson Frank Salary Survey, more than two-third of respondents found AWS certifications to be an important factor in increasing their earning potential. In fact, those who earned this certification received an 18 percent increase in salary.
Those who wish to obtain this certification should first fulfill the following prerequisites:
The proctored online exam features 50 multiple choice and multiple response questions on the following topics:
Candidates have 180 minutes to complete the exam and must receive a passing score of 750 or higher.
Amazon provides plenty of free resources to assist with preparation, such as an exam guide and sample questions.
For additional help with prep, Udemy offers a prep course for this certification.
Best for: Machine learning professionals looking to specialize in the AWS Cloud environment
Cost: $300 USD
This online certification for machine learning entails nine courses:
Each course takes two weeks for a total of three and a half months to complete the certification. One should expect to put aside between six and nine hours of work per week to make progress towards this certificate.
Upon completing all nine, learners possess the following knowledge and skills:
Candidates need not be enrolled at Cornell as a full-time student in order to obtain this certificate. It’s strongly recommended to have experience with:
The program’s website offers a free readiness test to gauge whether this certification is right for prospective learners.
Best for: Professionals with experience in data analysis, data science, developing, programming, software engineering, and statistics who need an accelerated certification program at a moderate cost level
Cost: $3,750 USD
Google also offers a Machine Learning on Google Cloud Specialization certification via Coursera. This certification comprises five courses:
In these courses, users will learn:
The program takes about four months to complete with a suggested pace of six hours per week.
According to the certification website on Coursera, this certification is intended for the intermediate level, meaning those with Python programming experience. However, it covers foundational concepts, so it is likely suitable for beginners as well.
The cost of this certification will vary depending on the pace at which an individual completes the courses. After a seven-day free trial, Coursera assesses a monthly subscription fee of $39.99. The total below assumes a four-month duration.
Best for: beginners who want to acquire foundational machine learning skills for GCP.
Cost: $1,600 USD
Building on the essential skills from the Machine Learning on Google Cloud specialization certification, Google also offers the Google Cloud Machine Learning Engineer Professional Certificate. The exam tests candidates abilities in:
Candidates are recommended to have at least three years of industry experience, including at least one year of experience designing and managing solutions using Google Cloud.
Candidates may want to obtain the Machine Learning on Google Cloud Specialization certificate before pursuing this certificate, but it’s not a requirement.
This certification is valid for two years before recertification is necessary.
The exam is a combination of multiple choice and multiple select questions that candidates have 200 minutes to complete.
Candidates may take the exam at an authorized location or in an online proctored environment.
Google provides a free exam guide, sample questions, and an on-demand webinar.
For additional help, consider Coursera’s prep course for this certification.
Best for: Machine learning engineers with some experience who want to specialize in architecting and deploying machine learning models to the Google Cloud Platform
Cost: $200
IBM offers a course-based machine learning certificate through Coursera. It entails successful completion of six courses that are designed to provide a theoretical understanding of and practice with key machine learning topics:
These courses teach the following machine learning subjects:
This certificate takes seven months to complete with approximately three hours of work each week. However, learners can progress at their own pace as their schedule permits.
Though offered in collaboration with IBM, the coursework involves hands-on projects that develop widely applicable skills not specific to IBM software and products.
Learners should be familiar with Python and have a solid understanding of statistics and linear algebra. However, since the courses start with foundational concepts and theory before taking on more complex topics, this certification is beginner friendly.
The cost will vary depending on the pace at which an individual completes the courses. After a seven-day free trial, Coursera assesses a monthly subscription fee of $39.99. The total below assumes a seven-month duration.
Best for: those with some programming experience seeking a low time and cost commitment in developing cloud-agnostic machine learning skills.
Cost: $280 USD
Microsoft’s exam-based Certified Azure AI Engineer Associate certification verifies candidates’ ability to implement AI solutions using Azure Cognitive Services and Azure Applied AI services.
This certification is a good starting point for beginners. Candidates should have experience using REST APIs and software development kits (SDKs) and be proficient in C# or Python.
The exam assesses candidates knowledge and skills in the following areas:
Candidates pass with a score of at least 700.
To prepare for the exam, candidates have access to free, self-guided study materials. Otherwise, Microsoft offers four-day, instructor-led prep courses for a fee of $1,450. Alternatively, candidates may want to check out Udemy’s prep course for this certification, which only costs $19.99. However, the prep course includes a series of practice tests without live interaction with an instructor. So if you already have a baseline understanding of the relevant Azure products, the Udemy prep course will likely be sufficient.
Best for: Those with programming and API experience looking for a cost-effective way to specialize in Azure solutions
Cost: $165 USD
Stanford University, in collaboration with DeepLearning.AI, offers this beginner-friendly, self-paced Machine Learning Specialization certificate online through Coursera. By the end of this program, learners will understand:
To obtain this certification, one must complete three courses:
It takes approximately two months to earn this certification, and you should expect to dedicate about nine hours each week.
The cost will vary depending on the pace at which an individual completes the courses. After a seven-day free trial, Coursera assesses a monthly subscription fee of $39.99. The total below assumes a two-month duration. To receive the certificate of completion, learners must pay an additional $79.
Best for: beginners who want to acquire a solid grasp of basic math and coding skills before learning the fundamentals of machine learning.
Cost: $80 USD
The right machine learning certification will depend on a range of factors:
If you’re interested in exploring and trying out machine learning, your best options will be:
Those with some programming experience under their belt should try out these intermediate certifications:
The most advanced certification is the Google Cloud Machine Learning Engineer Professional Certificate.
Most of the certifications here are specific to a particular cloud provider. However, the following provide learners with general cloud-agnostic foundational knowledge:
Some certifications here require learners to complete courses without the pressure of one exam. If you’re averse to tests, these course-based certifications are worth checking out:
The benefit of course-based certifications is that learners have more structured learning paths, and the skills acquired with each course build on one another.
Exam-based certifications, on the other hand, allow learners more freedom in terms of how to prepare. Plus, the certification process involves one key step: taking the exam. In this way, recipients can move on to the next certification or career milestone more quickly.
The amount of time and financial resources required to obtain a certification is no small factor in choosing the right certification.
In terms of time, if you want to get the certification over and done within a shorter period of time, then one of the exam-based options might be better for you. Microsoft Certified Azure AI Engineer Associate takes four to seven days to prepare and is the cheapest exam-based option at only $165.
The Cornell Cornell University Machine Learning Certificate is least advantageous in terms of cost and time, as it’s the most expensive and meets synchronously. However, it’s a great option for those who want to work directly with highly knowledgeable university faculty in an interactive setting.
Costing only $80 and taking only two months to complete, the Stanford/DeepLearning.AI Machine Learning Specialization Certificate is the least expensive and most time-effective option here.
Fortunately, if you’re currently employed in a machine learning role or a related field, your employer will likely subsidize at least part of your certification. For example, for Amazon certification recipients, 65 percent of employers are at least partially subsidizing their employees’ certifications.
Regardless of experience level, learning format preferences, schedule, and budget, there is a machine learning certification for everyone who’s interested in pursuing a career in this hot field. A machine learning certification is worth pursuing because it shows your commitment to the field. It also certifies your knowledge of machine learning theories, methods, and best practices that you can apply on the job.
Read next: 2022 IT Certification Roadmap
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