If you’ve been working in the technology industry for any time at all, you’re already familiar with its reliance on professional certification.
Everything from security to networking to project management skills can be honed and validated with industry certifications. Job listings are peppered with certification requirements.
Through a combination of training and assessment, certification can put a stamp of approval on your machine learning skills– exactly the validation employers are looking for.
As a valuable tool set in everything from data science to new generative AI systems, machine learning is yet another area where professional certification is becoming vitally important. As you build your knowledge and skills toward a career in AI, you’ll certainly want to identify exactly which ML certifications are the best fit for your goals.
What Is Machine Learning Certification? – Key Distinctions Between Academic Certificates and Professional Certification
Machine learning certs are a tried and tested method for validating your skills and knowledge in specific types of machine learning techniques or applications.
Though the terms certificate and certification are used interchangeably, there is a distinct and important difference between professional industry certs and the graduate and postgraduate certificates in machine learning offered through colleges and universities.
While an educational certificate of this sort may cover some of the same ground as professional industry certification, the college courses through which those skills are developed are usually designed with broader goals in mind. They are teaching the theory and concepts behind machine learning, as well as practical applications. In many cases, they are the same classes you would find in a degree program in the field.
Professional certifications serve a different purpose and come at it from a different angle. They are usually offered by professional organizations or software vendors, for starters. The classes may be to train you on specific tools or techniques, but the real intent and the real value come through tests and assessments of how well you have absorbed that material.
For this reason, professional certification is highly valued by employers. When they are hiring an ML expert, they want to know that you’re familiar with the tools they already use in-house and that have the right stuff to get the job done. Machine learning certifications in those specific tools or techniques give them that assurance.
What Are the Requirements for Earning a Machine Learning Certification?
Professional machine learning certification will test your mettle. The strength of the requirements behind the cert is a large part of the value that it offers – both to you and the company you work for, or the one you may eventually work for.
Since most machine learning certifications are offered by software and service vendors, pricing tends to be very reasonable.
Machine Learning certs rest heavily on the outcome of online examinations. Running up to 100 questions, these pose tough, realistic problems. Your command of the material is pushed to the limit.
To help you pass these tests, the typical professional ML certification program will also offer required or optional coursework. Naturally, the materials presented align precisely with the exam problems you’ll be expected to solve and the exercises you’ll complete. But in many cases, the classes also deliver valuable practical experience that will serve you well into your career.
Some certifications also have other prerequisite requirements, which can include:
- Pre-tests to verify your foundational skills in math, programming, and basic computer science concepts
- Actual on-the-job experience in related fields
- A college degree in a relevant field
As a practical matter, even certifications that don’t require such a background are tough to earn without those credentials. But for employers, it can be valuable to know that an independent certification body has verified that you have them.
Exploring Machine Learning Professional Certifications for AI and Beyond
Since machine learning has a wide range of applications that go far beyond artificial intelligence, there are many certification options that don’t go directly toward boosting your AI credentials.
That doesn’t mean you should avoid them, however. One of the big advantages to taking the machine learning educational path is that it provides diverse career opportunities, both in AI and in other fields. And with the importance of data science in many AI applications, focusing your certifications in that area can still be a great route into AI engineering –and one that allows plenty of fallback options.
What Many are Calling the Best Machine Learning Certifications Available for ML and AI Engineers Today
The landscape is constantly changing in the world of professional certification, just as it is in ML and AI. So you’ll want to keep your eye on the market to see what the latest and greatest offerings are and what employers are interested in.
For now, these certifications are the hottest and most important in the world of machine learning.
Cost – $300
Covers:
- Data Engineering; repositories, ingestion, and transformation
- Exploratory Data Analysis; data preparation for modeling, feature engineering, and visualization
- Modeling; restate business problems as ML problems, select appropriate models for specific modeling needs
- Machine Learning Implementation and Operations; creating containers and images, deploy, load balance, and log operating instances
Requires: Pass a 65-question multiple choice/multiple response exam within 180 minutes. Recommended to have 2 years of experience working with ML in AWS cloud, understand ML algorithms, and perform basic hyperparameter optimization
Cost – $100
Covers:
- Image classification modeling with deep neural networks
- Image classification modeling with deep neural networks
- Natural language processing
- Solving time series, sequence, and forecasting problems using TensorFlow
Requires: Pass a 5-hour assessment requiring completing code snippets to show competency. Must demonstrate Python programming skills in PyCharm.
Cost – $200
Covers:
- Ability to architect low-code ML solutions
- Collaboratively manage data and ML models
- Take prototype models and scale them into full ML solutions
- Automate and monitor machine learning pipelines
Requires: Passing a 50-60 question multiple choice examination within 2 hours; available with either online proctoring or at exam centers worldwide.
Cost – $49/month Coursera subscription
Covers:
- Practical machine learning skills and knowledge
- KNN, PCA, and non-negative matrix collaborative filtering
- Differences between various machine learning algorithms
- Practical course in creating recommender systems using Python
- Neural network training through regression and classification modeling
Requires: Approximately three months of study through six online courses
Cost – $165
Covers:
- •Designing suitable environments in Azure for data science processing
- Training machine learning models
- Implementing pipelines in Azure
- Running jobs to prepare, deploy, monitor, and manage machine learning solutions
Requires: Passing a 60-80 question exam within 180 minutes
Cost – $200
Covers:
- Data management and experimentation in MLflow
- MLflow model lifecycle management
- Automated testing in the ML pipeline
- Webhook use cases and connections
- Batch, streaming, and real-time deployment and processing
- Drift testing and solution monitoring
Requires: Passing a 60-question proctored online exam; one or more years hands-on experience recommended
Cost – Varies
Although they are located in Europe, IABAC offers several ML-related certifications in coordination with some American tech training organizations, which may offer the certs at different prices and with different training processes.
Covers:
- Certified Machine Learning Associate Certification
- Certified Deep Learning Expert Certification
Requires: Examination; prerequisite requirements in programming, math, and hands-on framework skills
Cost – $149
Covers:
- ML fundamentals, data preprocessing, and dimensionality reduction
- Regression and classification processes
- Supervised, unsupervised, and reinforcement learning techniques
- Deep learning, natural language processing, and time series forecasting
Requires: Passing a 100-question multiple choice exam
Other Types of Professional Certification Can Also Be Valuable in Machine Learning Careers
Machine learning certifications can be pure gold for a wide range of jobs in AI, data science, marketing, and more. But another way to look at professional certification flips that idea on its head: you may find certifications that aren’t in machine learning at all can bring a lot of value to your career in AI and machine learning.
The right choices for ML professionals looking at other cert options will depend entirely on your industry and career path. Cybersecurity, DevOps, and other IT specialties all have a thicket of certifications that are standard. Many artificial intelligence certifications themselves can deliver a hefty dose of machine learning expertise. We’ve put together a separate guide to professional certifications in AI so you can check those out.
But one of the most obvious crossovers is with data science certification. As the field that ML has grown most closely associated with outside of AI, data science and data scientists are connoisseurs of fine machine learning algorithms. Additionally, since data science has been booming for years now, the industry has had a lot more time to come up with respected and effective certification programs.
DASCA (Data Science Council of America), for example, offers a range of data science and big data related certifications which can involve ML requirements, including Senior and Principal Data Scientist certification, and a range of Big Data certifications. IBM and Microsoft also offer data science certifications in addition to their ML certs. DataCamp, an online training provider, has three data science related certifications that cover some ML skills as well.
There are also many tools used in the data science arena that have certifications available. These are sometimes also useful for machine learning careers. You can find various certs available in tools like:
- ML fundamentals, data preprocessing, and dimensionality reduction
- Microsoft Certificate Solution SQL Server
- MCSA Data Engineering with Azure
- AWS Big Data
- SAS Certified Data Scientist
- Oracle MySQL Database Administrator
- Cloudera Spark and Hadoop Developer
- MongoDB Certified Professional
- ML fundamentals, data preprocessing, and dimensionality reduction
- Oracle Certified Professional Java SE 8 Programmer
- Python Institute Certified Python Programmer
- ML fundamentals, data preprocessing, and dimensionality reduction
- Dell EMC Data Science Associate
- INFORMS Certified Analytics Professional
Online Machine Learning Certifications are Standard
The very nature of the intended audience of professional certifications almost guarantees that they are offered primarily online. When you are catering to working professionals, you have to make sure they can still get through a day of work while taking your program.
Online machine learning certification isn’t just the right choice; it’s usually the only choice.
That means delivering remote learning that allows students to tap into coursework from anywhere they can get an internet signal. You won’t have to leave town, or even your house, to earn most of these certs.
And because busy professionals can’t shift their schedules around to attend classes or take tests, the certifications must do the shifting for you. They’re offered asynchronously, available at any time, day or night. They are usually also self-paced, so you can pound through the work on a long free weekend, but scale back during a heavy week at the office or to meet family obligations.
The flexibility means you are both saving money and putting your priorities toward work and family… all while still getting a valuable credential to boost your career in the long term.
Does Professional Machine Learning Certification Increase Your Salary Level?
Since certification is largely aimed at proving your value to employers, you might expect to see some financial upside to earning a cert.
That’s certainly true, but also impossible to analyze in a field where salaries are already climbing into the stratosphere. Still, a 2021 survey from Pearson VUE, a prominent online certification testing platform, found that almost a third of IT professionals reported that certification resulted in a salary increase. Almost as many reported that it resulted in a promotion.
With a combination of professional validation and real, practical knowledge and skill development, a cert in machine learning has long-term value to your career. If it doesn’t result in an immediate salary bump, it’s still living on your resume for the next time an opportunity arises.
And, of course, earning certification also builds your own confidence in your command of real-world skills. That’s a benefit you can’t put a price on, and one that puts you in a position to climb higher and achieve more in your machine learning career.