7 Top AI Certifications: Hotlist of 2024

AI certifications demonstrate that you possess a specified level of proficiency and competence in artificial intelligence job-related skills, making you more attractive to employers. As a tech professional, AI certification courses can boost your career growth, expand your knowledge and expertise, and help you keep abreast of emerging trends in this dynamic technology.
As AI continues to transform industries and professionals race to acquire the skills to stay ahead of the curve, certifications are becoming increasingly important to recruiters looking for assurance that candidates understand the fundamentals of AI and its various aspects, including machine learning, natural language processing, computer vision, robotics, and AI software.
Here are our picks for the top AI certifications in 2024 for learners of all levels:

AI for Everyone: Best for Understanding AI Concepts
Computer Science for Artificial Intelligence: Best for AI-Related Programming Skills
Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning: Best for Learning Fundamentals of TensorFlow
IBM AI Engineering Professional Certificate: Best for Demonstrating Proficiency in Machine Learning and Deep Learning
CertNexus Certified Artificial Intelligence Practitioner Professional Certificate: Best for CAIP Certification Exam Preparation
Advanced AI Techniques for Product Marketing: Best for Applying Generative AI to Product Marketing 
Artificial Intelligence Engineer (AiE) Certification by the AI Board of America (ARTiBA): Best for Validating AI Engineering Expertise

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Best AI Certifications: Comparison Chart
The following chart summarizes the experience level, certifying institutions, duration, and cost of the seven leading AI certification courses to help you find the right one for your skills and interests, or keep reading for more detailed information about each of our picks.

AI Certification
Certifying Body
Level
Duration
Cost
Shareable Certificate

AI for Everyone
DeepLearning.AI
Beginner
Six hours
$49 per month
Yes

Computer Science for Artificial Intelligence
Harvard University
Beginner

Five months
22 hours per week

$518
Yes

Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
DeepLearning.AI
Intermediate
17 hours
$49 per month
Yes

IBM AI Engineering Professional Certificate
IBM
Intermediate

Two months
10 hours per week

$49 per month
Yes

CertNexus Certified Artificial Intelligence Practitioner Professional Certificate
CertNexus
Intermediate
Two months
$49 per month
Yes

Advanced AI Techniques for Product Marketing
Pragmatic Institute
Intermediate
Seven-and-a-half hours
$1,295 + taxes
Yes

Artificial Intelligence Engineer (AiE) Certification
ARTiBA
Advanced
90 minutes
$550
Yes

TABLE OF CONTENTS
ToggleCourse Spotlight: Advanced AI Techniques for Product Marketing SPONSOREDBest AI Certifications: Comparison ChartTop 7 AI Certifications for 2024Computer Science for AI by Harvard UniversityIntroduction to TensorFlow for AI, ML, and Deep LearningIBM AI Engineering Professional Certificate by IBMCertNexus Certified Artificial Intelligence Practitioner Professional CertificateAdvanced AI Techniques for Product MarketingARTiBA AI Engineer (AiE) CertificationAI Job Titles and Salary RangesFrequently Asked Questions (FAQs)Bottom Line: Choosing the Right AI Certification

Top 7 AI Certifications for 2024
Artificial intelligence certification programs usually involve completing training courses, passing assessments or exams, and meeting specific criteria set by certifying bodies or organizations. All of the AI certifications recommended here include some mix of these tasks, but they take very different approaches. This includes the amount of time and expertise required to complete the AI certification—study the requirements carefully to make sure the program is a fit for you.
AI For Everyone by DeepLearning.AI
Best for Understanding AI Concepts | Beginner Level
Offered by DeepLearning.AI, AI for Everyone is a non-technical course that will help you understand AI technologies and identify opportunities to apply them to your business or organization. Without requiring any prior technical knowledge, this course provides a comprehensive introduction to AI concepts, terminology, and applications. It aims to equip non-technical professionals with the necessary understanding and skills to navigate the AI landscape. Machine learning engineers and data scientists can also benefit from this course to understand what AI can and cannot do for your business or organization.

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Why We Picked It
This course is an excellent choice for anyone seeking a foundational understanding of AI. Designed for learners with no prior background, it breaks down complex concepts into four digestible modules and focuses more on practical applications and real-world scenarios. Unlike AI programs geared towards programmers, this course focuses on the “why” and “what” of AI, helping learners build a strong foundation without getting overwhelmed with technical information.
Skills Acquired
At the end of this course, learners will gain an understanding of the following:

Common AI terminologies and concepts
Potential AI real-life applications
How to work with an AI team and build an AI strategy
How to navigate the workflow of machine learning and data science projects
Ethical and societal discussions surrounding AI

Key Course Details
Who It’s For

Non-technical professionals or AI engineers looking for a beginner-friendly course for learning the business aspect of AI

Course Requirements

No prerequisites
This course is suitable for both technical and non-technical individuals

Course Fee, Duration, and Format

Free to audit or $49 per month for Coursera subscription
Six hours to complete
Self-paced online learning via Coursera

Course Content and Assessments
There are four modules:

What is AI?
Building AI Projects
Building AI in your Company
AI and Society

To pass the course, you need to pass four assessments with one quiz at the end of each module.
Computer Science for AI by Harvard University
Best for Acquiring AI-Related Programming Skills | Beginner Level
HarvardX offers a self-paced but comprehensive professional certificate series that combines CS50’s legendary Introduction to Computer Science course with a program that delves into the concepts and algorithms of modern AI. Three experts from Harvard University facilitate this course: Doug Lloyd and Brian Yu are senior preceptors in computer science, and David J. Malan is Gordon McKay Professor of the Practice of Computer Science. Learners can apply their AI knowledge through hands-on projects and gain exposure to the theory behind graph search algorithms, classification, optimization, reinforcement learning, and other topics in artificial intelligence.

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Why We Picked It
This professional certificate stands out for building a strong foundation in programming skills essential for AI. Unlike other courses that jump right into AI concepts, this program starts with CS50’s Introduction to Computer Science, ensuring that you have a solid foundation of core programming skills in Python. With this approach, you’re better equipped to understand advanced AI-specific programming languages and frameworks used in building intelligent systems.
Skills Acquired
By the end of the course, you’ll be able to design intelligent systems on their own and master the following skills:

Understanding of computer science and programming
Articulating principles of AI and ML
Designing intelligent systems
Using AI in Python programs
Learning theories behind graph search algorithms and reinforcement learning

Key Course Details
Who It’s For

Beginners new to the field of computer science who want to learn AI-related programming

Course Requirements

No prerequisites
Basic understanding of computer programming concepts is a plus

Course Fee, Duration, and Format

$518
Five months (up to 22 hours per week)
Expert instruction and self-paced online learning via edX

Course Content and Assessments
This program includes two courses:

CS50’s Introduction to Computer Science
CS50’s Introduction to Artificial Intelligence with Python

Introduction to TensorFlow for AI, ML, and Deep Learning
Best for Learning Fundamentals of TensorFlow | Intermediate Level
Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning is a certification course offered by Deeplearning.ai on Coursera. The course covers essential topics such as the fundamentals of machine learning, neural networks, deep learning, and TensorFlow. It includes hands-on practical exercises and assignments to help learners gain valuable experience in using TensorFlow to solve real-world problems. The certification course is ideal for individuals interested in AI, ML, and DL, including students, software engineers, data scientists, and anyone seeking to expand their knowledge and skills in TensorFlow.

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Why We Picked It
This course caters to individuals who have a foundational knowledge of machine learning and deep learning concepts. It prioritizes practical applications, providing learners with hands-on experience in building and training neural networks directly within TensorFlow. By focusing on best practices and working with real-world applications, you’ll gain a strong understanding of how to effectively apply this open-source framework to your own AI projects. Additionally, this course is part of the DeepLearning.AI TensorFlow Developer Professional Certificate, which helps you prepare for the Google TensorFlow Certificate exam.
Skills Acquired
By the end of this four-module course, you’ll have a solid grasp of the following skills:

Understanding TensorFlow, ML, and computer vision fundamentals
Learning the best practices for using TensorFlow
Training a neural network for a computer vision application
Building a basic neural network in TensorFlow
Using convolutions to improve a neural network

Key Course Details
Who It’s For

Software developers who want to learn the fundamentals and application of TensorFlow

Course Requirements

The course requires experience in Python coding and high school-level math
Prior machine learning or deep learning knowledge is helpful but not required

Course Fee, Duration, and Format

Free to audit or $49 per month for Coursera subscription
Approximately 17 hours
Self-paced online learning via Coursera

Course Content and Assessments
There are four modules in this course:

A New Programming Paradigm
Introduction to Computer Vision
Enhancing Vision with Convolutional Neural Networks
Using Real-World Images

To pass the course, you need to pass four assessments and four programming assignments.
IBM AI Engineering Professional Certificate by IBM
Best for Demonstrating Proficiency in ML and DL | Intermediate Level
Taught by seven experts, this intermediate-level certificate course offered by IBM takes approximately two months at 10 hours per week to complete. It consists of six courses, which will teach learners how to write Python code that implements various classification techniques, including K-nearest neighbors (KNN), decision trees, and regression trees; image processing and analysis techniques for computer vision problems; and how to build Deep Neural Networks using PyTorch — the last course includes an AI capstone project with deep learning. By completing this certificate, students will gain the knowledge and skills needed to start a career in AI engineering or further their existing careers.

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Why We Picked It
This professional certificate is an excellent choice for professionals who want to validate their comprehensive expertise in machine learning and deep learning. IBM’s program goes beyond basic theoretical knowledge but digs deeper into practical applications, offering learners the tools and skills that employers in the AI industry look for. Learning how to use popular ML and DL libraries like TensorFlow, Keras, PyTorch, and Scikit-learn through hands-on projects helps you become more capable of solving real-world problems using these techniques.
Additionally, you can earn college credit if you’re admitted to one of the online degree programs offered by Illinois Tech, the University of London, or Ball State University once you complete this professional certificate. You will also earn a professional certificate from Coursera and receive a digital badge from IBM recognizing your proficiency in AI engineering.
Skills Acquired
After completing this course, you will gain the following skills:

Understanding ML, DL, neural networks, and ML algorithms
Deploying ML algorithms and pipelines on Apache Spark
Implementing supervised and unsupervised ML models using SciPy and ScikitLearn
Building DL models and neural networks using Keras, PyTorch, and TensorFlow

Key Course Details
Who It’s For

AI or ML engineers who want to master fundamental concepts of machine learning and deep learning

Course Requirements
This certificate’s prerequisites include:

Working knowledge of Python and Jupyter Notebooks
High school mathematics or math for machine learning
IBM Data Science Professional Certificate recommended
IBM Applied AI Professional Certificate recommended

Course Fee, Duration, and Format

Free to audit or $49 per month for Coursera subscription
Two months (10 hours per week)
Self-paced online learning via Coursera

Course Content and Assessments
There are six modules in this course:

Machine Learning with Python
Introduction to Deep Learning and Neural Networks with Keras
Introduction to Computer Vision and Image Processing
Deep Neural Networks with PyTorch
Building Deep Learning Models with TensorFlow
AI Capstone Project with Deep Learning

CertNexus Certified Artificial Intelligence Practitioner Professional Certificate
Best for CAIP Certification Exam Preparation | Intermediate Level
The CertNexus Certified Artificial Intelligence Practitioner (CAIP) Professional Certificate is designed for data scientists looking to enhance their skills and knowledge in the AI space. To earn CertNexus’s CAIP Professional Certificate, learners need to complete the CAIP specialization, which provides a comprehensive understanding of AI and ML concepts, workflows, algorithms, and technologies. The specialization covers topics such as data analysis, model training, regression, classification, clustering, advanced algorithms, and deep learning.

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Why We Picked It
This certification stands out for its comprehensive five-course series that helps you earn an industry-validated certification from a respected organization. CertNexus is a vendor-neutral certification body that meets one of the most rigorous development standards following a global framework, and its CAIP specialization validates an individual’s capability in a wide variety of AI job functions. Coursera’s CAIP certificate lets you apply AI and ML approaches to business problems, develop and test tools, and overall prepare for CertNexus’ certification using both theoretical and practical knowledge. You can also add the projects you complete at the end of each module to your work portfolio.
Skills Acquired
Through this program you will master the following skills:

Identifying business problems that AI and ML can solve
Understanding workflow tasks and ML automation
Using ML algorithms to solve supervised and unsupervised problems
Exploring advanced algorithms in AI and ML
Building multiple models to solve business problems

Key Course Details
Who It’s For

Data science professionals preparing for the CAIP certification examination

Course Requirements

Understanding of fundamental AI concepts and experience working with databases and high-level programming languages such as Python, Java, or C/C++ recommended

Course Fee, Duration, and Format

$49 per month
Two months (10 hours per week)
Online via Coursera

Course Content and Assessments
This five-course series proves the following skills:

Solving business problems with AI and machine learning
Following a machine learning workflow
Building regression, classification, and clustering models
Building decision trees, SVMs, and artificial neural networks
Preparing for your CertNexus certification exam

Advanced AI Techniques for Product Marketing
Best for Applying Generative AI to Product Marketing | Intermediate Level
Offered by the Pragmatic Institute, this course covers advanced techniques for using generative AI, automated workflows, and other technologies to boost marketing effectiveness. You’ll learn the latest tactics for accelerating and enhancing Product Marketing Management (PMM) deliverables. Marketing professionals can learn advanced AI techniques through hands-on learning and actionable insights, empowering you to use AI technology to gain a major competitive advantage in the B2B landscape. Throughout the workshop, you’ll learn about the pivotal role of prompting, various prompt structures, and how prompts contribute to structured campaign goal setting, detailed buyer journeys, and more.

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Why We Picked It
This course goes beyond the basics and focuses specifically on applying generative AI in the dynamic field of marketing. You’ll learn how to craft compelling product descriptions and marketing materials using AI tools, personalize user experiences, and generate creative and targeted content. Unlike general AI courses, this program equips you with skills that you can directly apply to your existing marketing campaigns and business strategies.
Skills Acquired
At the end of the workshop, students will gain the following skills:

Applying generative AI and prompt engineering best practices
Writing effective prompts for product marketing
Using AI to differentiate marketing and messaging strategies
Analyzing and identifying trends in complex marketing datasets
Crafting data-driven ideal customer profiles and buyer personas

Key Course Details
Who It’s For

Product marketers and marketing managers who want to use generative AI and prompt engineering for their business

Course Requirements

Participants are required to have access to GPT-4, through a ChatGPT Plus, Teams, or Enterprise level access

Course Fee, Duration, and Format

$1,295
Seven and-a-half hours
In-person or online

Course Content and Assessments
The workshop will cover three modules:

Introduction to Generative AI
Using AI in Product Marketing
AI Landscape for Product Marketing

ARTiBA AI Engineer (AiE) Certification
Best for Validating AI Engineering Expertise | Advanced Level
The Artificial Intelligence Engineer (AiE) certification process is offered by the Artificial Intelligence Board of America (ARTiBA), which is a professional membership body dedicated to promoting and advancing AI practices. To receive the AiE certification, individuals must undergo a structured evaluation process assessing their knowledge and skills in various AI-related domains. Gaining this certification helps you stand out in the competitive AI industry by establishing your advanced skillset in conceiving, building, training, and running ML models and in-depth knowledge in NLP, different types of learning, cognitive computing, and more.

Get AI Engineer (AiE) Certification at ARTiBA

Why We Picked It
The AiE certification offered by ARTiBA is specifically designed to demonstrate your expertise in building and deploying AI systems. It also emphasizes the ARTiBA-developed AMDEX knowledge framework, which goes beyond platform-specific tools and focuses on in-depth practical skills. The programs also provide exclusive resources to applicants to help them in their exam preparation and in achieving an industry-recognized certification.
Skills Acquired

Developing expertise in popular AI and ML technologies and problem-solving methodologies
Understanding advanced concepts and approaches to AI modeling and application development
Proving capability and expertise in preparing for AI and ML applications
Demonstrating proficiency and the ability to understand AI and ML applications in a business context

Key Course Details
Who It’s For

AI engineers who want to demonstrate comprehensive expertise in AI systems and applications

Course Requirements
ARTiBA currently offers three registration tracks for AiE certification applicants:

AIE Track 1: Associate degree or diploma in Computer Science, IT, or related discipline plus two years’ work history in any of the computing sub-functions required
AIE Track 2: Bachelor’s degree in Computer Science, IT, or related discipline plus two years’ work-history in any computing sub-function and a good understanding of computer programming required
AIE Track 3: Master’s degree in Computer Science, IT, or any related discipline plus two years’ work history in any computing sub-functions and a good understanding of computer programming required

Course Fee, Duration, and Format

$550
The allotted time for the examination is one hour and 30 minutes
Candidates should also pass the AIE certification exam 180 days from the date of registration confirmation
Online and digitally proctored

Course Content and Assessments
The AiE certification exam is based on the AMDEX™ knowledge framework covering 48 themes spread across four essential knowledge segments:

AI and ML
AI and ML Programming
NLP
Neural Networks and DL

AI Job Titles and Salary Ranges
The field of AI has created diverse job roles, each demanding a unique skill set. As the industry continues to expand, with new AI companies forming every year, so does the complexity of AI job titles and their corresponding salary ranges.

Role
Salary Range (Annual)

Machine Learning Engineer
$92,000 – $284,000

AI Engineer
$89,000 – $215,000

Data Scientist
$91,000 – $229,000

Computer Vision Engineer
$84,000 – $237,000

Natural Language Processing Engineer
$114,000 – $344,000

Deep Learning Engineer
$92,000 – $284,000

AI Research Scientist
$124,000 – $265,000

Business Development Manager
$94,000 – $193,000

AI Product Manager
$111,000 – $276,000

AI Consultant
$97,000 – $174,000

We sourced AI jobs and salary data from Glassdoor, a certified site for professionals to access salary insights and company reviews. See our annual AI jobs salary report for an in-depth review of AI job salaries by experience and industry.
Frequently Asked Questions (FAQs)
What Are the Key Benefits of Earning an AI Certification?
AI certifications validate your expertise in a specific domain. This can enhance your credibility in the AI industry, increase your earning potential, and boost your job prospects. Obtaining comprehensive AI certifications indicates that you’re dedicated to lifelong learning and career growth, which employers respect. Certifications also provide structured learning, whether online or in person, helping you master key concepts and skills as you navigate through your chosen career path.
How Do You Prepare for an AI Certification?
Preparing for an AI certification requires a structured approach that combines theoretical knowledge and practical application. It’s important to build a solid foundation in math, statistics, and programming and an understanding of AI concepts like machine learning, deep learning, and NLP. After ensuring that you have a foundational knowledge of essential AI concepts, choose the right certification that aligns with your career goals, current learning level, and resources. Aside from researching online, you should also explore specialized AI communities for insights and discussions.
You can also start building your portfolio before signing up for an AI certification, so you can have a guided list of personal projects that you want to take during the course duration. Once you start your AI course or program, create a study plan and practice regularly to reinforce concepts and improve your problem-solving abilities. Use the resources included in your course, such as reading materials, PowerPoint presentations, and mock exams, or tools like AI chatbots to help you summarize lessons, answer practice tests, and explain technical terms.
Which AI Certification Should I Get First?
Choosing the right certification depends on your career goals and current skill level. For beginners, consider foundational certifications like those offered by Coursera or edX to gain a general overview of AI concepts. If you have some programming experience, certifications that emphasize Python and AI libraries can be a good starting point. Meanwhile, AI professionals who have more comprehensive experience should look for specialized certifications in domains like machine learning, deep learning, or data science. If you work in a particular industry, consider certifications that align with the field you’re working in, such as healthcare, finance, marketing, and more.
Can You Get a Job in AI with Just Certifications?
While certifications are valuable, they should be complemented by practical experience. A strong portfolio of AI projects can significantly enhance your job prospects and validate your expertise as an AI professional. While taking your certifications, document your hands-on experiences and special projects to add to your portfolio. Aside from certifications and practical experience, it’s also important to expand your network and be updated with the latest trends in the AI field. Search for opportunities to join industry gatherings or AI conferences to meet other professionals, learn best practices, and find career opportunities.
Bottom Line: Choosing the Right AI Certification
Choosing the right AI certification depends on your career goals and factors unique to you, such as skill level, industry focus, and available resources. Carefully consider your objectives to find a certification that aligns with your career aspiration and assess how much you can invest in terms of time, money, and other resources. You should also prioritize certifications that validate your practical skills, are widely recognized by employers, and offer a strong return on investment on your career advancement and earning potential. After finding the right AI certification, complement it with practical skills, knowledge of the latest AI trends, and a strong network of AI professionals.
If you’re specifically looking for programs focused on machine learning, read our list of the best machine learning certificates.

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