8 Top AI Certifications: Latest Hotlist You Won’t Want To Miss

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

Future Skills Certified AI Professional: Best for Enhancing Business Skills with AI

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

Course Spotlight: Advanced AI Techniques for Product Marketing SPONSORED

Offered by the Pragmatic Institute, this course covers advanced techniques for using generative AI, automated workflows and other technologies to boost marketing effectiveness.
Students will learn the latest tactics for accelerating and enhancing Product Marketing Management (PMM) deliverables.
The course provides hand-on learning and actionable insights so that today’s busy marketing professionals are empowered to use AI technology to gain major competitive advantage in the B2B landscape.

Visit Pragmatic Institute

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

Future Skills Certified AI Professional
Future Skills Academy
Intermediate
Four weeks
$299
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
ToggleTop 8 AI Certifications for 2024Computer Science for AI by Harvard UniversityIntroduction to TensorFlow for AI, ML, and Deep LearningIBM AI Engineering Professional Certificate by IBMCertified AI Professional (CAIP)CertNexus 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 8 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.

Visit DeepLearning.AI Course at Coursera

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.

Get Harvard Course at edX

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.

Get Introduction to TensorFlow at Coursera

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.

Get IBM Course at Coursera

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

Certified AI Professional (CAIP)

Best for Enhancing Business Skills with AI | Intermediate Level

Future Skills Academy’s Certified AI Professional (CAIP) program equips you with practical experience using AI for business innovation. Anyone who wants to deepen their understanding of AI will find this certification valuable, including business analysts, consultants, entrepreneurs, and marketing professionals. You’ll learn AI core concepts and advanced techniques to help enhance technical skills you can apply in the real world. Future Skill’s CAIP certification is accredited by the Continuing Professional Development (CPD) organization, demonstrating your dedication to pursuing professional development in AI.

Visit CAIP at FSA

Why I Picked It

Future Skill’s CAIP certification is an ideal program for learners who want to learn problem-solving strategies through real-world case studies and hands-on experience. Unlike instructor-led courses, this program is more flexible, making it ideal for those who prefer self-paced learning. This course will help you gain an in-depth understanding of AI core concepts, contemporary AI techniques, and AI applications for business innovation, entrepreneurship, and business strategy.

Skills Acquired

Fundamentals, history, myths, and realities of AI

Machine learning, deep learning, and neural network basics

Natural language processing and computer vision

Practical uses of AI in different industries

AI for business innovation, entrepreneurship, and business strategy

Emerging AI trends

AI in everyday life and its societal implications

Key Course Details

Who It’s For

Marketing professionals, business analysts, consultants, entrepreneurs, and innovation managers who want to expand their AI skillset

Course Requirements

No prerequisites

Course Fee, Duration, and Format

$299

Four weeks

Self-paced online learning via Future Skills

Course Content and Assessments

This certification program includes 80 lessons that cover the following areas:

Artificial intelligence fundamentals

Core concepts of AI

Advanced AI techniques

AI in practice

Business and entrepreneurial applications of AI

AI for everyday use and productivity

The future of AI and AI career opportunities

Learners must pass the final exam to gain a shareable certificate equivalent to 10 hours of CPD credit.

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.

Visit CertNexus Course at Coursera

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.

Visit AI Techniques Course at Pragmatic Institute

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.
The post 8 Top AI Certifications: Latest Hotlist You Won’t Want To Miss appeared first on eWEEK.