Top 10 Machine Learning Engineer Certifications

Certifications are important for a machine learning engineer in the job market because they provide evidence of knowledge, skills and experience in the field. A certification can help demonstrate a commitment to excellence and professional development in machine learning engineering, which can make a candidate more attractive to employers. Additionally, certifications can help differentiate a candidate from other applicants, as only those with the necessary qualifications will have them. Certifications can also provide employers with assurance that a potential employee has the technical know-how to deliver results.

This article reviews some of the top certifications for Machine Learning Engineers and explains how they can enhance a machine learning engineer's career.

What are Machine Learning Engineer Certifications?

Machine Learning Engineer Certification is a professional certification program designed to help individuals demonstrate their knowledge, skills and abilities related to the development of machine learning (ML) models. The certification provides a comprehensive overview of ML principles, algorithms and tools, and covers topics such as data pre-processing, model selection, hyperparameter tuning, evaluation metrics and deployment. It also includes hands-on projects in which participants will be required to build ML models from scratch or use existing ML libraries and frameworks. This certification helps individuals demonstrate their knowledge of the latest ML technologies and techniques and can open up new career opportunities in data science or AI engineering. In addition, it can help professionals stay up-to-date with the latest developments in the field and gain an edge over other professionals when competing for job roles.

Pro Tip: When considering a machine learning engineer certification, make sure to research the curriculum of the course and ensure that it covers all of the necessary topics to become an effective machine learning engineer. Additionally, look for courses that include hands-on experience with real-world data and projects, as this will be invaluable when you start your career.

Related: What does a Machine Learning Engineer do?

Top 10 Machine Learning Engineer Certifications

Here’s our list of the best certifications available to Machine Learning Engineers today.

1. IBM Professional Data Scientist

IBM Professional Data Scientist is a certification program that provides individuals with the skills and knowledge necessary to become a successful data scientist. The program covers the fundamentals of data science, including machine learning, deep learning, analytics, and more. It includes hands-on labs and exercises to help you develop your skills in data analysis and visualization.

The program takes approximately six months to complete. To get started, you must first register for the IBM Professional Data Scientist certification exam. Once registered, you will receive access to course materials and assessments that will help prepare you for the exam. You can also take advantage of additional resources such as online tutorials and practice tests to help you better understand the topics covered in the exam.

The cost of the IBM Professional Data Scientist certification exam is $200 USD. You can purchase vouchers from IBM or from third-party vendors like Pearson VUE or Prometric. After passing the exam, you will receive an official certificate from IBM that certifies your expertise in data science.

2. Microsoft Certified Solutions Expert (MCSE): Data Management and Analytics

Microsoft Certified Solutions Expert (MCSE): Data Management and Analytics is a certification that validates an individual’s expertise in designing, implementing, and maintaining data management and analytics solutions based on Microsoft technologies. It requires knowledge of the Microsoft SQL Server platform, including its components such as Integration Services, Analysis Services, and Reporting Services. The MCSE: Data Management and Analytics certification also covers topics such as database design, data warehousing, business intelligence, Big Data analytics, and cloud data services.

The MCSE: Data Management and Analytics certification usually takes around three months to complete. To get the certification you must pass two exams: Exam 70-767 Implementing a SQL Data Warehouse; and Exam 70-768 Developing SQL Data Models. Both exams are available online or at a local testing center.

The cost of the MCSE: Data Management and Analytics certification varies depending on your location. Generally speaking, it costs around $150 per exam plus any applicable taxes or fees.

3. SAS Certified Advanced Machine Learning Specialist

SAS Certified Advanced Machine Learning Specialist is a certification program offered by SAS, an analytics software company. It is designed to help professionals demonstrate their expertise in the field of machine learning and data science. This certification validates a person’s skills in using SAS software to create predictive models, build data visualizations, and analyze data.

To become certified as an Advanced Machine Learning Specialist, you must have at least two years of experience working with SAS software and be able to pass the SAS Certified Advanced Machine Learning Specialist exam. The exam consists of 60 multiple-choice questions that cover topics such as machine learning algorithms, model evaluation techniques, data visualization techniques, and more.

The cost for the exam is $180 USD. The exam can be taken online or at a Pearson VUE test center. It typically takes around 2 hours to complete the exam. Once you have passed the exam, you will receive your certification within 4-6 weeks.

4. Google Professional Machine Learning Engineer

Google Professional Machine Learning Engineer is a certification program designed to help individuals develop their skills in the field of machine learning. The program consists of two parts: an online course and a hands-on project.

The online course covers topics such as data science fundamentals, machine learning algorithms, cloud computing, and big data technologies. It also includes practical exercises to build your experience with Google Cloud Platform services for machine learning. The course takes approximately 10 weeks to complete.

The hands-on project requires you to apply the concepts you learned from the online course by building a machine learning solution on Google Cloud Platform. You will be given a dataset and must design, implement, deploy, and evaluate your model using Google Cloud Platform services. This project takes approximately 6 weeks to complete.

The cost of the certification program is $399 USD (plus applicable taxes).

5. Amazon Web Services Certified Machine Learning – Specialty

Amazon Web Services Certified Machine Learning – Specialty is an advanced certification designed to help professionals demonstrate their expertise in machine learning. It is focused on the development and deployment of machine learning models using Amazon Web Services (AWS).

The certification consists of a two-hour exam that tests your knowledge and skills in building, training, deploying, and managing machine learning models on AWS. The exam covers topics such as data preparation, model selection, hyperparameter optimization, validation techniques, and model deployment.

It takes approximately three months to prepare for the exam. To get started, you should have a basic understanding of machine learning concepts and familiarity with AWS services such as Amazon SageMaker, Amazon EC2, Amazon S3, and Amazon DynamoDB. You can also take advantage of online courses offered by AWS or third-party providers to gain more knowledge about the topics covered in the exam.

The cost of taking the exam is $300 USD. After passing the exam you will become an AWS Certified Machine Learning – Specialty professional. This certification will demonstrate your expertise in building machine learning models on AWS and will open up new career opportunities for you.

6. Cloudera Certified Professional: Data Scientist

Cloudera Certified Professional: Data Scientist is a certification program designed to validate the skills and knowledge of data scientists who are proficient in using Apache Hadoop and related technologies. The certification focuses on the ability to apply data science principles, methods, and tools to solve real-world problems. It requires candidates to demonstrate their proficiency in areas such as data wrangling, machine learning, distributed computing, natural language processing, and other big data analytics techniques.

The Cloudera Certified Professional: Data Scientist exam takes approximately two hours to complete. To get certified, applicants must pass an online proctored exam that covers topics such as Apache Hadoop, Apache Spark, HiveQL, Impala SQL, Pig Latin scripting language, and more.

The cost of the exam is $295 USD for individuals or $495 USD for groups of three or more. In addition to the exam fee, applicants may also need to pay for any applicable taxes or fees associated with taking the exam.

7. Hortonworks Certified Apache Hadoop Data Scientist

Hortonworks Certified Apache Hadoop Data Scientist (HDPCD) is a certification program designed to recognize professionals who are proficient in using the Apache Hadoop platform for data science. It is an industry-recognized certification that demonstrates an individual’s expertise in the use of Hadoop and related technologies. The HDPCD exam covers topics such as HDFS, MapReduce, Hive, Pig, Impala, Sqoop, Flume, Oozie, and YARN.

The HDPCD certification takes approximately 4 hours to complete and consists of 50 multiple-choice questions. To get certified, applicants must pass the exam with a score of 70% or higher.

The cost of the HDPCD certification is $250 USD per attempt.

8. Oracle Cloud Infrastructure Machine Learning Certification

Oracle Cloud Infrastructure Machine Learning Certification is a certification program designed to help individuals demonstrate their knowledge and skills in using Oracle Cloud Infrastructure for machine learning. This certification helps validate the expertise of professionals who are responsible for developing and deploying machine learning solutions on Oracle Cloud Infrastructure.

The certification exam consists of 60 multiple-choice questions that must be completed within 90 minutes. The exam focuses on topics such as cloud infrastructure, machine learning concepts, data engineering, model development, and model deployment.

To get the Oracle Cloud Infrastructure Machine Learning Certification, you must first register for the exam at the Oracle University website. Once registered, you will need to complete an online training course to prepare for the exam. The cost of the training course varies depending on whether you choose to take it online or in-person. After completing the training course, you can then schedule your exam at any Pearson VUE test center worldwide.

The cost of taking the Oracle Cloud Infrastructure Machine Learning Certification Exam is $245 USD.

9. AWS Certified Big Data – Specialty

AWS Certified Big Data – Specialty is a certification designed to demonstrate an individual’s expertise in designing, deploying, and managing big data solutions on the Amazon Web Services (AWS) platform. This certification validates a candidate’s ability to:

• Design and implement big data solutions using AWS services such as Amazon EMR, Amazon Redshift, Amazon Kinesis, and Amazon S3.
• Analyze large datasets with tools such as Apache Hive, Apache Pig, and Apache Spark.
• Manage big data solutions using AWS services such as AWS Identity and Access Management (IAM), AWS CloudFormation, and AWS CloudTrail.

The exam for this certification takes approximately 3 hours to complete and consists of multiple-choice questions. Candidates must have at least 5 years of experience working with big data technologies in order to be eligible for this exam. The cost of the exam is $300 USD.

10. Coursera Deep Learning Specialization

Coursera Deep Learning Specialization is a series of 9 courses created by deeplearning.ai, which are designed to help you master the concepts and tools needed to build artificial neural networks and lead the way in deep learning. The specialization includes topics such as convolutional networks, recurrent networks, generative adversarial networks, and reinforcement learning. It also covers best practices for building and deploying AI systems.

The entire specialization takes around 4 months to complete if done on a full-time basis. However, students can take their own time to finish the courses and projects at their own pace. Each course has a duration of 2–4 weeks with quizzes and assignments that need to be completed in order to move onto the next course.

To get started with Coursera Deep Learning Specialization, you need to sign up for an account on Coursera’s website or through its mobile app. Once you have an account, you can enroll in any of the 9 courses offered in this specialization by paying the subscription fee for each course separately or pay for all 9 courses at once with a discounted price.

The cost of Coursera Deep Learning Specialization varies depending on whether you choose to pay per course or pay for all 9 courses at once. If you decide to pay per course, each course costs $49 USD/month; however, if you opt for the subscription plan which includes all 9 courses at once, it will cost $399 USD/month (which is about 10% cheaper than buying each course separately).

Do You Really Need a Machine Learning Engineer Certificate?

The answer to this question depends on your goals and ambitions. If you are looking to become a Machine Learning Engineer, then an ML Engineer Certificate may be the best way to demonstrate your skills and knowledge in the field. A certificate can help you stand out from the competition, as it shows employers that you have taken the time to specialize in a particular area of expertise. Additionally, having a certificate may also give you access to higher-level positions and opportunities for career advancement.

On the other hand, if you already have experience in Machine Learning or if your goal is simply to stay up-to-date with industry trends, then a Machine Learning Engineer Certificate may not be necessary. You can still learn about new technologies and techniques through self-study, attending conferences or taking online courses. These are all great ways to build your knowledge base without needing an official certification.

Ultimately, whether or not you need a Machine Learning Engineer Certificate depends on what type of job you’re looking for and how far along you are in your career. It’s important to weigh the pros and cons before deciding if obtaining one is right for you.

Related: Machine Learning Engineer Resume Examples

FAQs About Machine Learning Engineer Certifications

Q1. What is a Machine Learning Engineer Certification?

A1. A Machine Learning Engineer certification is a professional certification that demonstrates a person’s knowledge and skills in the field of machine learning. It typically involves completing a course or program, passing an exam, and maintaining continuing education requirements.

Q2. Are there different levels of Machine Learning Engineer Certifications?

A2. Yes, there are different levels of certifications available depending on the individual's experience and skill level. Some of the most common levels include Associate, Professional, and Expert.

Q3. How long does it take to become certified as a Machine Learning Engineer?

A3. The amount of time required to complete the certification process will depend on the individual's background and experience level with machine learning, as well as the type of certification sought after. Generally speaking, most programs can be completed within 8-12 months with full-time study.

Q4. Is there an exam required for a Machine Learning Engineer Certification?

A4. Yes, most certifications require applicants to pass an exam in order to receive their certificate or credential. In some cases, applicants may also need to complete additional coursework or other requirements before taking the exam.

Q5. What are the benefits of becoming certified as a Machine Learning Engineer?

A5: Being certified as a machine learning engineer affords individuals several benefits including increased job opportunities, higher salaries and potential promotions due to their specialized skillset in this field; greater credibility among employers; recognition from peers; and personal satisfaction from having achieved such an accomplishment