There’s never been a better time to earn a machine learning certification. Record levels of funding poured into AI startups this year, and AI hiring has increased by 32% since 2019. AI and machine learning skills are highly sought-after by employers, and demand for these skills is slated to grow by 71% over the next 5 years

According to Sundar Pichai, CEO of Alphabet Inc. and its subsidiary Google, the social impacts of AI will surpass those of fire and electricity. AI now supports complex, critical infrastructure like electric grids, food warehousing and distribution, cybersecurity,  healthcare, and more—and its numerous applications are growing. In 2020, the global AI market was valued at $35.92 billion and is projected to grow to $360.36 billion in 2028 as demand for AI solutions continues to expand across industries. 

To land a role in the field, you’ll need proven production engineering skills and a strong portfolio that showcases your ability to design, prototype, and deploy a machine learning or deep learning system. A machine learning certification can help you build key skills and accrue the vital hands-on experience you need to get hired. 

Do You Really Need a Machine Learning Certificate?

machine learning certification: Do You Really Need a Machine Learning Certificate?

While theoretical knowledge is important, it’s not enough to secure a machine learning position. You’ll need to practically demonstrate your mastery of machine learning concepts to impress hiring managers. Many candidates lack the applied skills necessary to succeed in machine learning roles, so building production engineering skills through a machine learning certification program is a way to make your application robust and competitive. 

The best machine learning certifications will help you master specific tools and technical concepts and guide you through the process of building realistic, complete machine learning applications. A machine learning certification will also validate your machine learning expertise in hiring contexts. Machine learning certifications that emphasize job readiness and offer career support will be most effective in helping you land your dream role. 

The Best Machine Learning Certifications

Want to evaluate your options? Let’s compare top machine learning certifications on the basis of cost, duration, reputation, and more. 

Springboard’s Machine Learning Engineering Career Track

machine learning certification: Springboard’s Machine Learning Engineering Career Track

Students enrolled in Springboard’s Machine Learning Engineering Career Track learn how to create and deploy ML algorithms, all while building a professional portfolio that will stand out to hiring managers. 

What We Like About This Certification

Springboard’s machine learning certification program matches students with industry expert mentors, who provide unlimited one-to-one support throughout the duration of the course. This machine learning certification also emphasizes hands-on skill building, and 50% of the program focuses on production engineering skills. 

Certification Details

This 500-hour course typically takes six months to complete at a pace of 15-20 hours of learning per week—although those with prior programming experience may finish faster. 

The program costs $13,140, but students who pay tuition upfront receive a 17% discount, which lowers the total cost to $10,900. Students can pay tuition over the course of six months, or defer payments until after landing a job. 

Springboard’s Machine Learning Engineering Career Track boasts a curated curriculum that covers the machine learning engineering stack, battle-tested machine learning models, deep learning, computer vision and image processing, machine learning models at scale and in production, and deploying ML systems to production. 

Springboard’s courses are highly rated on review boards like CourseReport, which awarded Springboard “Best Online Bootcamp” commendations in 2019, 2020, and 2021. Since Springboard’s founding, 94% of eligible graduates have won jobs within a year of completing their certification. Springboard grads have earned an average salary bump of $26k. 

AWS Certified Machine Learning — Specialty 

machine learning certification: AWS Certified Machine Learning — Specialty

Offered by Amazon, this certification proves expertise in creating, training, refining, and deploying machine learning models on the AWS Cloud. To earn this certification, candidates must pass the AWS Certified Machine Learning – Specialty exam. No coursework is required, but independent preparation is recommended. 

What We Like About This Certification

This certification is designed for machine learning professionals with more than one year of experience developing and deploying machine learning or deep learning models in the AWS Cloud—which means it’s a great way for those who’ve already built machine learning skills to validate their cloud expertise with an industry-recognized credential. 

Certification Details

Candidates receive 180 minutes to complete the exam, which consists of 65 multiple choice or multiple response questions. Amazon offers free and paid study resources to help candidates prepare for the test independently. The exam costs $300, and a practice exam costs $40. 

This certification evaluates a candidate’s ability to solve business problems with appropriate machine learning solutions, identify appropriate AWS services to implement machine learning solutions, and deploy scalable, cost-effective machine learning solutions. The exam covers data engineering, exploratory data analysis, modeling, and machine learning implementation and operations. 

Amazon is an industry leader in the field of AI, meaning this certification will confer a high level of confidence in your technical knowledge and core competencies. As per this recent survey, 70% of interviewed AWS professional certificate holders reported a 20% salary increase after earning their certification—showing that this credential carries weight with employers. 

Professional Machine Learning Engineer by Google

machine learning certification: Professional Machine Learning Engineer by Google

This certification measures your ability to design, build, and productionize machine learning models with Google Cloud technologies. Candidates must pass an exam to earn this certification, which is designed for machine learning engineers with at least three years of industry experience and one year or more of experience with the Google Cloud platform. 

What We Like About This Certification

Google offers a variety of resources to support exam preparation. Candidates can experiment with Google Cloud Free Tier for select products. Additionally, Google offers no-cost self-study courses as well as webinars and an exam guide. Newcomers to the platform can also explore the documentation and hands-on guides that address the use of machine learning methods and tools on Google Cloud.

Certification Details

Candidates are allotted two hours to take the exam, which costs $200. This certification assesses proficiency with framing and solving machine learning problems and ML model development. It also measures skills related to the design of data preparation and processing systems as well as the automation and orchestration of machine learning pipelines. 

Google’s core competency is artificial intelligence and machine learning, and its cloud platform is a popular tool for leveraging AI solutions. In fact, Job listings citing “Google Cloud” as a desired skill have increased tenfold over the past three years. In addition to verifying your expertise in the eyes of hiring managers, this certification also opens up access to the Google Cloud Certified community and Credential Holder Directory—which can be used to tap into new job opportunities. 

Azure AI Engineer Associate by Microsoft

machine learning certification: Azure AI Engineer Associate by Microsoft

This certification—which candidates earn through passing an exam—verifies your ability to implement AI solutions using Azure Cognitive Services and Azure Applied AI services. Candidates should be proficient in C# or Python and should have experience using REST-based APIs and SDKs to develop and deploy natural language processing, knowledge mining, computer vision, and conversational AI solutions on Azure. 

What We Like About This Certification

Microsoft offers free, self-directed learning paths to help candidates prepare for the Azure AI Engineer Associate exam. Some learning paths focus on broader topics like extracting text from images and documents, while others focus on learning how to use Azure’s services to perform key tasks. Alternatively, Microsoft also offers a paid, instructor-led course to help candidates prep for their test. 

Certification Details

Registration for Microsoft’s certification exam costs $165. The exam covers the following topics:

  • Planning and managing an Azure Cognitive Services solution (15-20%)
  • Computer vision solutions (20-25%)
  • Natural language processing solutions (20-25%)
  • Knowledge mining solutions (15-20%)
  • Conversational AI Solutions (15-20%)

Many companies rely on Microsoft’s cloud services to support mission-critical applications. In 2020, over half of global IT decision-makers expected their organizations to invest in Microsoft technologies. As of 2021, 92% of organizations reported having embraced a cloud computing strategy. This certification will validate your expertise in implementing AI solutions with a major cloud provider, making you a valuable asset in hiring contexts. 

IBM Machine Learning Professional Certificate

This certification demonstrates applied skills in core areas of machine learning, including supervised learning and unsupervised learning, deep learning, and reinforcement learning. To earn the certificate, candidates must complete a series of six courses offered through Coursera. Ideal candidates have a background in math, statistics, and programming. 

What We Like About This Certification

This certification is accessible to early-career or aspiring AI professionals who don’t have extensive experience under their belts. The course’s final project also provides an opportunity for candidates to apply theoretical knowledge in a hands-on context. 

Certification Details

Each course that comprises the IBM Machine Learning Professional Certificate demands 7-10 hours of study. With six courses to complete, this certification requires 42-60 hours total. After completing the coursework, candidates can opt to receive a verified certificate for a small fee.

These courses are designed to provide a theoretical understanding of and practice with key machine learning topics ranging from exploratory analysis to linear regression and classification algorithms. Students are expected to follow along and code their projects using open-source frameworks and libraries. 

IBM is a big name in both artificial intelligence and cloud computing—47 Fortune 50 Companies use the IBM Cloud, and IBM’s Watson is working on 20,000+ engagements. The IBM Machine Learning Professional Certificate course is highly rated on Coursera, and a certification from an industry leader will help your resume stand out. 

Machine Learning From Stanford University 

machine learning certification: Machine Learning From Stanford University

Offered by Stanford University through Coursera, this coursework-based certification provides a broad introduction to machine learning, data mining, and statistical pattern recognition. After completing Stanford’s course online, candidates may purchase an electronic certificate that can be printed or added to your LinkedIn profile. 

What We Like About This Certification

If you pursue this certification, your instructor will be machine learning and online education pioneer Andrew Ng. Although all video lectures are pre-recorded, you’ll still have the opportunity to learn from the founder of DeepLearning.AI and co-founder of Coursera itself. Andrew Ng is a highly influential figure in the machine learning field, and his involvement with the course is a big draw. 

Certification Details

After completing your coursework through Coursera, you’ll be able to purchase your electronic certificate for $79. The certification requires approximately 61 hours of coursework, which Coursera suggests breaking up over the span of 11 weeks. 

This certification focuses on supervised and unsupervised learning as well as machine learning best practices. By the end of the course, candidates should walk away with skills related to logistic regression, artificial neural networks, and machine learning. 

Out of over a million ratings from learners, 97% gave the syllabus content of this certification a thumbs-up rating. 10% of learners reported starting a new career after completing the certificate course, and 14% reported gaining a tangible career benefit from the course. This certification provides a solid introduction to machine learning on which job-seekers can build as they work to land their dream role. 

eCornell Machine Learning Certificate From Cornell University

This certificate program equips participants to implement machine learning algorithms and uses Python, Jupyter Notebooks, and the NumPy library for code exercises and projects. Upon completing the program’s coursework, candidates will earn a Machine Learning Certificate from Cornell Bowers College of Computing and Information Science, as well as 126 Professional Development hours. This certificate is geared toward participants who are familiar with math, statistics, linear algebra, multivariate calculus, and Python. 

What We Like About This Certification

This certification focuses on teaching candidates how to think critically about the application of machine learning. “Using a combination of math and intuition,” the course overview explains, “you will practice framing machine learning problems and construct a mental model to understand how data scientists approach these problems programmatically.” While that might sound heady, honing your ability to instinctively frame a problem in a machine learning context is important. 

Certification Details

This online, instructor-led certification program consists of seven individual courses that require two weeks apiece to complete. Overall, the program requires three and a half months of study at a recommended pace of 6-9 hours per week. Enrollment costs $3,600 flat or $565 per month. 

This certification explores problem-solving with machine learning, estimating probability distributions, learning with linear classifiers, decision trees, and model selection, debugging and improving machine learning models, learning with kernel machines, neural networks, and deep learning. 

Cornell boasts an impressive computer science pedigree, as this does the program’s faculty author Kilian Weinberger, whose work has produced important papers in the field of computer vision and contributed to the GPyTorch framework. Cornell’s computer science program has also produced a number of top machine learning researchers, meaning this certificate will carry name-brand recognition in the machine learning field. 

Professional Certificate in Data Science by Harvard

Professional Certificate in Data Science by Harvard

This course-based certification is part of a broader data science program offered by Harvard University via edX. Candidates can earn a machine learning certificate without completing the entire Professional Certificate in Data Science. Over the span of the program, candidates will work with key machine learning algorithms and exercise new skills by building a recommendation system. 

What We Like About This Certification

This shorter course is ideal for helping newcomers grapple with machine learning fundamentals. For those who want to explore AI at a relatively low cost under the guidance of a globally recognized educational institution, this certification offers an excellent theoretical and practical introduction to machine learning. 

Certification Details

At a cost of $99, this certification falls on the more affordable end of the spectrum. Students can complete the machine learning certificate portion of the Professional Certificate in Data Science after 8 weeks at a pace of 2-4 hours of study per week. 

The course covers machine learning basics, such as identifying predictive relationships within datasets and training algorithms to predict future outcomes. Through the recommendation system project, this certification provides hands-on experience with topics like regularization and principal component analysis—but you’ll need more opportunities to strengthen applied skills and build a professional portfolio before applying for machine learning roles. 

Applied Data Science With Python Specialization by the University of Michigan

Applied Data Science With Python Specialization by the University of Michigan

This course-based certification program offered through Coursera introduces candidates to data science via Python. It’s designed for participants with programming backgrounds who want to learn how to implement machine learning techniques using popular Python libraries and frameworks like Scikit-Learn, Matplotlib, Pandas, and more. After completing the required coursework and a hands-on project, candidates will receive a shareable certificate. 

What We Like About This Certification

Python is one of the most popular programming languages for machine learning—plus it’s highly accessible to newcomers. Furthermore, if you’ve got a lot of free time on your hands and want to move through your coursework quickly, this certification might be an economical choice. Learners pay a monthly fee for the course, candidates can save money by progressing quickly through the course. 

Certification Details

This certification costs $49 a month and requires 5 months to complete at a pace of seven hours of study per week. The modules cover applied plotting, charting, and data representation in Python, machine learning in Python, text mining in Python, and social network analysis in Python. 

Each course within the certificate program has a minimum rating of 4.2 stars out of 5. According to Coursera’s Learner Career Outcomes, 13% of participants started a new career after earning this certification, and 13% received a pay increase or promotion. 

Are Machine Learning Certificates Worth It?

The best machine learning certifications not only validate a candidate’s technical skills but also provide the career support necessary to help connect emerging professionals with job opportunities. The certification that is right for you will depend on your level of prior experience as well as your career goals. 

If you’re a career-switcher hoping to get hired as a machine learning engineer, prioritize certification programs that offer mentorship opportunities and a curriculum that prioritizes project-based learning. If you are already employed in the AI industry and want to demonstrate your proficiency with specific tools, the best machine learning certification for you may be exam-based rather than coursework-oriented. 

No matter your decision, 94% of IT leaders concur that employees who have earned IT certifications add value that exceeds the cost of the certification itself. Machine learning engineers and AI developers are among the top 5 AI roles that companies plan to recruit or train for, and a certification can help instill a hiring manager’s confidence in your skills. 
Last but not least, a machine learning certification can increase your earnings. 28% of IT professionals report that earning a certification resulted in salary increases, and 216% reported a promotion. Not all certifications offer equal support or carry the same weight in the eyes of employers, but earning the right certification for you could add up to larger career dividends  in the long run.

Is machine learning engineering the right career for you?

Knowing machine learning and deep learning concepts is important—but not enough to get you hired. According to hiring managers, most job seekers lack the engineering skills to perform the job. This is why more than 50% of Springboard’s Machine Learning Career Track curriculum is focused on production engineering skills. In this course, you’ll design a machine learning/deep learning system, build a prototype, and deploy a running application that can be accessed via API or web service. No other bootcamp does this.

Our machine learning training will teach you linear and logistical regression, anomaly detection, cleaning, and transforming data. We’ll also teach you the most in-demand ML models and algorithms you’ll need to know to succeed. For each model, you will learn how it works conceptually first, then the applied mathematics necessary to implement it, and finally learn to test and train them.

Find out if you’re eligible for Springboard’s Machine Learning Career Track.