6 Best Machine Learning Certificate 2024
6 Best Machine Learning Certificate Programs to Master AI, 2024
The post 6 Best Machine Learning Certificate 2024 appeared first on eWEEK.
The machine learning market is projected to grow at a remarkable annual rate of 36 percent from 2024-2030, making it one of the most in-demand skill sets for programmers, data scientists, and aspiring AI professionals.
To capitalize on this trend, many ML professionals are getting their machine learning certification — a formal recognition of your ML expertise by a reputable certifying body, such as Cornell University, Google, IBM, and other top AI companies.
Typically, these ML certification programs are taught by industry experts or professors and come with course material in the form of videos, quizzes, assignments, and readings, all culminating in a final certification exam – and possibly resulting in career advancement.
Here are our top picks for the best machine learning certifications of 2024:
- Machine Learning Specialization (Coursera): Best for total ML novices.
- IBM Machine Learning Professional Certificate: Best for ML intermediates.
- AWS Certified Machine Learning: Best for indicating your ML expertise in AWS.
- Google Professional Machine Learning Engineer: Best for proving your ML expertise using Google Cloud solutions.
- eCornell Machine Learning Certificate Program: Best for an academic approach to learning ML with Python.
- Microsoft Azure Data Scientist Associate Certification: Best for validating your ML expertise in Microsoft Azure.
Machine Learning Certification Comparison Chart
When selecting a machine learning certification, it’s important to take into account the certifying body, duration of the program, and course fee. You should also make sure it aligns with your artificial intelligence and ML experience level and offers study resources and techniques that fit your learning style.
| Best for | Certifying Body | Duration | Study Resources | Experience Level | Fee | |
|---|---|---|---|---|---|---|
| Machine Learning Specialization (Coursera) | Beginners breaking into the field. | Stanford University | 2 months (10 hrs per week) | Videos, labs, quizzes, reading, app items, projects. | Novices | $59 per month |
| IBM Machine Learning Professional Certificate (Coursera) | Intermediates looking to update their skill set. | IBM | 3 months (10 hrs per week) | Videos, labs, quizzes, reading, app items, projects. | Intermediates | $59 per month |
| AWS Certified Machine Learning | ML professionals who build and deploy models in AWS. | Amazon | 3 hours (65 questions) | Practice questions, exam guide, exam readiness webinar. | Advanced | $300 |
| Google Professional ML Engineer Certification | ML professionals who build and deploy models with Google Cloud. | 2 hours (50-60 questions) | 14 Google ML preparation courses and one Google lab. | Advanced | $300 | |
| eCornell Machine Learning Certificate Program | Those interested in learning Python for ML via an academic experience. | Cornell University | 3.5 months (6-9 hours per week) | Live sessions, projects, videos, readings. | Beginners | $3,750 |
| Microsoft Azure Data Scientist Associate Certification | ML professionals who build and deploy in Azure. | Microsoft | 100 minutes | ~12 hr course, 100 prep videos, exam practice sandbox. | Advanced | $165 |
TABLE OF CONTENTS
Stanford Machine Learning Specialization (Coursera)
Best 3-course series for machine learning beginners.
Taught by AI visionary Andrew NG, Stanford’s 3-course, beginner-friendly machine learning specialization will introduce you to key artificial intelligence concepts and teach you to build and train ML models using Python.
Unlike most other certification programs, this ML course is geared toward the total beginner, recommending only that course-takers have high school math knowledge and basic coding skills (loops, functions, if/else statements). As a writer who took a free intro Python course via CodeAcademy for fun, I can tell you these are easy concepts to pick up.
This low barrier to entry combined with its immersive, comprehensive, and hands-on learning experience makes this ML certification the perfect option for aspiring AI professionals looking to break into the field.
Who Should Get This Certification?
This certification is ideal for total beginners looking to get an entry-level position in the field of ML, as well as early-career data analysts, software engineers, and ML interns looking to upskill in machine learning. Some sample salaries for positions that this ML certification could possibly lead to:
- Junior Data Analyst: $85,000 per year.
- Machine Learning Intern: $104,000 per year.
- Junior Software Engineer: $130,000 per year.
Pricing
- $59 per month for a Coursera subscription.
- Can take the courses for free but won’t receive a certification.
Recommended Prerequisites
- High school math (algebra, arithmetic).
- Basic coding (loops, functions, if/else statements).
For more information about generative AI providers – which are companies that hire ML experts – read our in-depth guide: Generative AI Companies: Top 20 Leaders
IBM Machine Learning Professional Certificate (Coursera)
Best 6-course series for intermediate ML professionals looking to upskill.
IBM’s Machine Learning Professional Certificate is designed to help intermediate-level tech professionals master practical, up-to-date machine learning concepts and skills that they can apply to the analysis of real-world datasets.
Through six courses, you’ll learn exploratory data analysis for machine learning, supervised ML, unsupervised ML, and deep/reinforcement learning.
All of this culminates in a final capstone project where you’ll train a neural network, construct regression models, create recommender systems in Python, and more. Once completed, you’ll receive a certificate from IBM, thus positioning you as a machine learning expert.
Who Should Get This Certification?
IBM’s certification is meant for scientists, business analysts, and software developers who want to improve their analytical skills in data science and machine learning, but the certificate is highly useful to ML professionals aspiring to a variety of data-focused roles. Some sample salaries for positions that this ML certification could possibly lead to:
- Business Analysts: $99,000 per year.
- Machine Learning Engineer: $165,000 per year.
- NLP Scientist: $146,000 per year.
- Data Engineer: $155,000 per year.
- Software Engineer: $145,000 per year.
Pricing
- $59 per month for a Coursera subscription.
- Can take the courses for free but won’t receive a certification.
Recommended Prerequisites
- Background in math, statistics, and computer programming.
AWS Certified Machine Learning
Best exam for indicating your machine learning expertise in the AWS platform.
The AWS Certified Machine Learning Speciality is a 3-hour exam that validates your ability to build, train, tune, and deploy machine learning models on AWS.
The exam can be taken in-person or online, and will test how well you can state the intuition behind basic ML algorithms, perform hyperparameter optimization, and follow model-training and deployment best practices.
For those looking to prepare, check out the AWS Skill Builder, where you’ll find helpful course material and practice questions.
Who Should Get This Certification?
This certificate is for professional developers and data scientists who have worked with ML in AWS and want to validate this skillset to employers, perhaps to land a more senior data science role. Some sample salaries for positions that this ML certification could possibly lead to:
- Machine Learning Engineer: $165,000 per year.
- Data Scientist: $155,000 per year.
- AWS Data Engineer: $164,000 per year.
- Software Engineer: $145,000 per year.
Pricing
- $300
Recommended Prerequisites
- Intended for working developers and data scientists with over a year of experience developing, architecting, or running machine learning workloads in AWS Cloud.
To see a list of the leading generative AI apps, read our guide: Top 20 Generative AI Tools and Apps 2024
Google Professional Machine Learning Engineer
Best exam for proving your ML expertise in Google Cloud solutions.
The Google Professional Machine Learning Engineer Certificate is an exam for ML professionals who build and optimize ML models using Google Cloud technologies and best practices.
Sections of the exam include 1) architecting low-code ML solutions, 2) collaborating with teams to manage models, 3) scaling prototypes into ML models, 4) serving and scaling ML models, 5) automating ML pipelines, and 6) monitoring ML solutions.
Google offers learning materials in their Machine Learning Engineer Learning Path, where you’ll find 14 courses and one lab. Google also offers an 8-course series through Coursera for preparing for the exam.
Who Should Get This Certification?
Working ML engineers and developers looking to promote their knowledge of Google Cloud technologies, ML engineering best practices, and cutting-edge ML techniques. Some sample salaries for positions that this ML certification could possibly lead to:
- Machine Learning Engineer: $165,000 per year.
- Data Scientist: $155,000 per year.
- Google Machine Learning Engineer: $165,000 per year.
- Software Engineer: $145,000 per year.
Pricing
- $300
Recommended Prerequisites
- Minimum proficiency in Python and SQL.
- Experience handling large, complex datasets.
- Strong programming skills.
- Knowledge of data processing tools.
- Experience building and maintaining ML models on Google Cloud.
eCornell Machine Learning Certificate Program
Best program for an academic Python-based machine learning program.
The eCornell Machine Learning Certificate Program offers aspiring and current data science professionals the opportunity to learn machine learning and Python fundamentals in an online yet academically-rigorous environment.
At $3,750, this educational certificate program is by far the most expensive on our list. But it also comes closest to stimulating the small-classroom experience, offering online courses created by Cornell faculty, hands-on projects, live discussions sessions, and serious feedback on your assignments from course facilitators.
If you’re an aspiring machine learning professional looking to shorten your growth curve, this high-ticket certificate program might be worth the price. If you think you can pass the exam without the learning path, you can check your readiness with a free pretest now.
Who Should Get This Certification?
Aspiring and working developers, data scientists, programmers, software engineers, and statisticians looking to learn how to develop and implement ML algorithms with Python. Some sample salaries for positions that this ML certification could possibly lead to:
- Machine Learning Engineer: $165,000 per year.
- Machine Learning Intern: $104,000 per year.
- Junior Data Analyst: $85,000 per year.
- Python Programmer: $146,000 per year.
Pricing
- $3,750
Recommended Prerequisites
- Familiarity with Python.
- Knowledge of probability theory, multivariate calculus, linear algebra, and statistics.
Microsoft Azure Data Scientist Associate Certification
Best exam for data scientists confirming their ML expertise in Microsoft Azure.
The Microsoft Azure Data Scientist Associate Certification is a 100-minute, online exam for intermediate data scientists and developers familiar with using data science and machine learning techniques to develop and run machine learning workloads on Azure.
The skills tested in the exam include machine learning solution design and prep, model training, data exploration, model deployment, and model retraining — all in reference to Microsoft Azure.
To help you prepare for the exam, Microsoft offers some 13 hours of course material, 100 exam prep videos, a practice assessment, and an exam sandbox where you can practice answering questions in the same interface you’ll see during exam day.
Who Should Get This Certification?
Professional developers, data scientists, and ML engineers who want to validate their abilities to deploy and maintain machine learning workloads on Azure. Some sample salaries for positions that this ML certification could possibly lead to:
- Machine Learning Engineer: $165,000 per year.
- Data Scientist: $155,000 per year.
- Azure Data Engineer: $166,000 per year.
- Software Engineer: $145,000 per year.
Pricing
- $165
Recommended Prerequisites
- Experience with Azure machine learning and MLflow.
- Subject matter expertise in data science best practices.
To gain a deeper understanding of today’s top large language models, read our guide to Best Large Language Models
Key Benefits of Earning a Machine Learning Certification
Below are some of the best reasons to get your machine learning certification, ranging from launching an ML career to staying current with ML techniques.
Validate Your Machine Learning Skills & Knowledge
It’s one thing to tell an employer that you’re well-versed in building ML solutions in Google Cloud. It’s another to show them a certificate from Google validating this assertion.
With certificate programs, you can pass exams and earn certificates from reputable institutions that prove you know your stuff. This will help you stand out in the machine learning and data science job market.
Start a Career in Machine Learning
Not sure what the difference is between machine learning and deep learning? Or generative AI? No problem. Some machine learning certifications are designed to help total novices learn the fundamentals of machine learning, gain practical ML skills, and break into the field of AI, data analysis, and machine learning.
Learn the Current ML Techniques, Tools, and Trends
Certificate programs provide you with learning materials that draw from techniques, tools, and frameworks that professional data scientists and ML engineers are using in their real-world jobs.
This makes a program a valuable option for even the seasoned ML professional looking to update their skill set to match the current best practices, while gaining recognition for it.
Earn at Affordable Prices Compared to College Degrees
Compared to college degrees in computer science or data analysis, which cost over six figures, these certification programs enable you to earn credit for machine learning skills and gain a respected credential for as low as a couple hundred dollars.
Go at Your own Pace
Certificate programs enable you to prepare for certification exams and take machine learning courses at your own speed, from the comfort of your home. This makes them ideal for busy tech professionals.
How to Choose the Best Machine Learning Certification for You
When deciding on a machine learning certificate, it’s important to take into account the following considerations:
- Price: Find a certification that works with your budget.
- Prerequisites: Make sure the courses and/or exam cater to your specific experience level.
- Specialty: Some programs are designed for professionals familiar with a specific solution (for example, Google’s certificate is for building ML models using G Suite technologies), so pick a program that focuses on the tools you plan to work with.
- Learning Materials: Whether you’re learning a new ML subject from scratch or filling in some gaps to prepare for the exam, check out the study materials and online courses to see if they are sufficient for your needs.
- Your Career Goals: Pick a certificate program that will help you land the job or get the promotion you desire.
In sum, the best machine learning certification will be one that fits your budget, experience level, and timeline, and helps you achieve your specific machine learning and AI career goals.
How We Evaluated Machine Learning Certifications
To evaluate the various machine learning certifications on the market and find the best ones, we looked at the cost of the certification, the reputation of the certifying body, the quality of learning materials, and the accessibility.
Cost
We looked into how much the machine learning certification costs in terms of time commitment and exam and course fee.
Reputation of Certifying Body
The “street cred” of the certifying body came into our consideration since they’re likely to provide cutting-edge courses and will look great on your resume to future employers.
Quality of Course / Exam Preparation Material
We examined the learning materials to see if they would adequately prepare an aspiring machine learning professional for the jobs they’re applying to. We focused on hand-on learning experiences like projects and assignments.
Accessibility
To assess the accessibility, we checked out how easy it was for users to prepare for and take the exam from home, as well as factors like access to course instructors and self-paced learning.
Frequently Asked Questions (FAQs)
How do you prepare for machine learning certification?
To prepare for machine learning certification, start by reading the exam’s prerequisites. If you feel you fall short, check to see if the certifying body offers preparation materials that will help you round out your knowledge.
Most program’s offer a learning path that includes online videos, practice questions, and readings. Some course-based programs, like eCornell’s certificate, even offer feedback on your assignments as well as live discussions hosted by course facilitators.
Which machine learning certification should I get first?
The first machine learning certification you should get is the one you feel most comfortable passing. For example, if you have experience doing ML projects with AWS, take the AWS certificate exam. If you’re a total newbie, take Stanford’s ML specialization through Coursera. That’ll ensure you get the credentials you deserve as quickly as possible.
Can you get a machine learning job with just certifications?
Though it may be difficult without on-the-job experience, you can still get a machine learning job with just a certificate by using these tactics:
- Learn ML in Public: Take on machine learning and coding projects and write about your findings and the process on social media to position yourself as an expert.
- Pretend you Have the Job: Find areas of interest where you can apply machine learning to improve some aspect, then create an ML model or solution and share it.
- Focus on Smaller Companies: Startups will be more likely to hire you for a niche ML skill than big companies, who generally want people with advanced degrees.
- Prepare for Interviews: Practice talking about the machine learning projects you’ve worked on, the latest technologies and trends, and your relevant technical skills.
If you do these activities consistently, you’ll have a greater chance of landing a machine learning job with nothing but your certification. At any rate, your prospects will be better than if you merely sent out resumes highlighting your certificate and in-course projects.
Bottom Line: Machine Learning Certifications Can Boost Your Career
A machine learning certification is one of the most affordable and time-efficient ways to validate your machine learning knowledge and expertise – and get hired in a lucrative new role.
Once you’ve completed the exam, you can list the formal certificate on your LinkedIn profile and resume to help you land machine learning jobs or get a promotion. Good luck!
If you’re looking for additional AI certifications to help you stand out, check out our list of the top 30 AI certifications.
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