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Artificial Intelligence (AI) certification is a credential awarded to individuals who possess a certain level of proficiency in an artificial intelligence job-related task. AI certifications are a great way to boost career growth for tech professionals.
AI certifications demonstrate understanding and competence in various aspects of AI, such as machine learning, natural language processing, computer vision, robotics, and AI software.
The demand for professionals with AI certifications is great: The artificial intelligence market size is projected to grow from $515.31 billion in 2023 to more than $2 trillion by 2030, at a scorching CAGR of 21.6% – and with this growth comes enormous demand for AI experts.
This guide analyzed the best AI certifications to help you advance your careers and stay up to date with the latest AI technologies.
TABLE OF CONTENTS
Best AI Certification: Comparison Chart
Here is a head-to-head summary chart of the best AI certification courses with the features, certifying institutions and prices.
| AI Certification | Certifying Body | Duration | Study resources | AI Experience level | Course fee |
|---|---|---|---|---|---|
| AI for Everyone (Coursera) | DeepLearning.AI | 10 hours | Coursera platform, video lectures, readings | Beginner level | Free (audit) or Coursera subscription or $49 for individual course purchase |
| Certified Artificial Intelligence Scientist (CAIS) | United States Artificial Intelligence Institute | 4 – 25 weeks | Study books, self-paced videos, practice code | Intermediate and Advanced | $894 |
| Computer Science for Artificial Intelligence | Harvard University | Five months | Self-paced video | Beginner or mid-level | $448 |
| Fundamentals of Google AI for Web-Based Machine Learning | Three months | Self-paced videos | Beginner/mid-level | $498 (currently on sale for $358.20) | |
| IBM AI Engineering Professional Certificate | IBM | Two months at 10 hours a week | Coursera platform, video lectures, readings | Intermediate level | Free (audit) or Coursera subscription or $49 for individual course purchase |
| Artificial Intelligence A-Z 2023: Build an AI with ChatGPT4 (Udemy) | SuperDataScience Team and other instructors | 17 hours | On-demand video, 20 articles, three downloadable resources | Beginner/mid-level | $16.58 per month (personal plan) or $139.99 course purchase fee |
| Artificial Intelligence Engineer (AIE) Certification Process by the Artificial Intelligence Board of America (ARTiBA) | ARTiBA | N/A | A copy of the Ai Engineer’s HandbookPractice tests for AiE exam on the myARTiBA candidate dashboardAiE Study Guide | Intermediate | $550 |
| Artificial Intelligence Graduate Certificate | Stanford School of Engineering | 1 to 3 years, depending on the learner’s pace |
| Intermediate or advanced level | $18,928 – $23,296 |
| Microsoft Certified: Azure AI Engineer Associate | Microsoft | 114 hours 37 minutes |
| Intermediate or advanced level | $165 for U.S. candidate |
| Artificial Intelligence: Business Strategies and Applications | UC Berkeley | Two months | UC Berkeley platform, video lectures, readings, case studies | Intermediate | $2,800 |
| AI for Business Leaders | Udacity | Two months |
| Beginner or intermediate | Udacity subscription for a minimum of $249 per month or $2,390 per year |
| Jetson AI Certification | NVIDIA Deep Learning Institute | Four hours of online content plus project time |
| Intermediate to advanced | Free |
| Professional Machine Learning Engineer | Google Cloud | Two hours |
| Intermediate to advanced | $200 |
| Post Graduate Program in AI and Machine Learning | Purdue University, IBM, and Simplilearn | 11 months |
| Intermediate | $4,500 |
| AI Applications for Growth | Northwestern University Kellogg School of Management | Two months at four to six hours per week |
| Any AI experience level; senior business leadership experience preferred | $2,850 |
| Professional Certificate Program in Machine Learning & Artificial Intelligence | MIT Professional Education | 16 days of qualifying Short Programs courses in Professional Education |
| Beginner to intermediate | $325 application fee and per-course fees |
| AI for Non-Technical People: A Hands-On Beginner’s Course | Udemy | 1 hour 16 minutes plus time to complete hands-on projects |
| Beginner | $11.99 to $39.99, depending on time of purchase |
| Intel Edge AI Certification | Intel | 13 foundational learning plan courses plus three hands-on modules; self-paced, so time to completion varies |
| Intermediate | Free program; certain aspects of certification may cost an additional $99 per year |
| Graduate Certificate in Ethical Artificial Intelligence | San Francisco State University | 10 course units, with three each coming from approved computer science, business management, and philosophy courses; 1 course unit for independent study |
| All levels | Dependent on current registration status with SFSU; all students must pay a $7 processing fee for the certification |
| ChatGPT / AI Ethics: Ethical Intelligence in an AI World | Udemy | Two hours of video training |
| Beginner | $11.99 to $54.99, depending on time of purchase |
Best 20 AI Certifications 2023
AI certification programs usually involve completing training courses, passing assessments or exams, and meeting specific criteria set by certifying bodies or organizations.
AI for Everyone (Coursera)
Non-technical professionals looking for a beginner-friendly AI certification course may find the AI for Everyone course beneficial. The course is hosted on Coursera and taught by Andrew Ng, courtesy of DeepLearning.AI.
This course is designed to provide a comprehensive introduction to artificial intelligence (AI) concepts, terminology, and applications without requiring any prior technical knowledge. It aims to equip non-technical professionals with the necessary understanding and skills to navigate the AI landscape.
The course consists of approximately 10 hours of video lectures, quizzes, and exercises to reinforce learning. Upon completion, students will receive a certificate from Coursera, which can be shared on professional platforms.
Experience required
This course has no prerequisites, making it suitable for both technical and non-technical individuals.
Course content
This course has four modules:
- What is AI? – 2 hours to complete.
- Building AI Project – 2 hours to complete.
- Building AI In Your Company – 3 hours to complete.
- AI and Society – 2 hours to complete.
Key course details
| Best for | Non-technical individuals |
| Course fee | Free (audit), or included with Coursera subscription |
| Duration | 10 hours |
| Supported language(s) | 8 languages, including English and Bahasa Indonesia (otomatis) |
| Assessments | Quizzes |
| Study resources | Coursera platform, video lectures, readings |
| Study format | Self-paced online learning |
| Certificate fee | Included in subscription, or $49 for individual course purchase |
Also see: 100+ Top AI Companies 2023
Certified Artificial Intelligence Scientist (CAIS)
The Certified Artificial Intelligence Scientist course offered by the United States Artificial Intelligence Institute is one of the top certifications in artificial intelligence. This comprehensive program covers various AI topics, such as machine learning, deep learning, and Computer Vision with Reinforcement Learning. CAIS also provides hands-on training and real-world projects to enhance practical skills in AI.
Experience required
- PATH 01: Bachelor’s degree or equivalent in any academic discipline and at least five years of experience in AI, ML, Data Science, Business Analytics, Business Intelligence, Project Management, or any Programming language.
- PATH 02: Master’s degree or equivalent in any academic discipline and at least four years experience in AI, ML, Data Science, Business Analytics, Business Intelligence, Engineering, Finance, and Management.
- PATH 03: Must have completed CAIC or other equivalent certification and at least four years experience for Bachelor’s Degree holders and three years experience for Masters Degree holders.
Course content
This exam includes the following general domains and their percentage weights on the exam:
- Artificial Intelligence and Machine Learning (18%).
- Strategic data science and management (15%).
- The economics of AI (12%).
- Supervised deep learning and computer vision (18%).
- AI in marketing (10%).
- Reinforcement learning (RL) (12%).
- Artificial Intelligence, cloud, and security (15%).
Key course details
| Best for | Senior professionals such as business leaders like Managers, Delivery Managers, Program Managers, Directors, and CXOs |
| Course fee | $894 |
| Duration | 4-25 weeks |
| Supported language(s) | English |
| Study resources |
|
| Study format | Self-paced |
| Certificate fee | Included in the course fee |
Also see: Top Generative AI Apps and Tools
Computer Science for Artificial Intelligence
Beginners new to the field of computer science and AI may want to consider the Computer Science for Artificial Intelligence course offered by three experts from Harvard University: Doug Lloyd and Brian Yu, who are Senior Preceptors in Computer Science at Harvard University, and David J. Malan, a Gordon McKay Professor of the Practice of Computer Science at Harvard University.
This self-paced Harvard certificate includes two courses, including CS50’s Introduction to Computer Science and CS50’s Introduction to Artificial Intelligence with Python. The course provider claims learners can finish the certification program in five months.
The course offers hands-on projects, which can help learners will gain exposure to the theory behind graph search algorithms, classification, optimization, reinforcement learning, and other topics in artificial intelligence.
Experience required
This course doesn’t have prerequisites, meaning individuals of all levels can apply. However, a basic understanding of computer programming concepts would be beneficial.
Course content
- Understanding of computer science and programming.
- Graph search algorithms.
- Reinforcement learning.
- Machine learning.
- Artificial intelligence principles.
- How to design intelligent systems.
- How to use AI in Python programs.
Key course details
| Best for | Beginners |
| Course fee | $448 |
| Duration | 5 months |
| Supported language(s) | English |
| Study resources | Self-paced videos |
| Study format | Self-paced |
| Certificate fee | Included in the course fee |
Fundamentals of Google AI for Web Based Machine Learning
This certification course is designed to help learners understand what AI really is and what it isn’t. Jason Mayes, a Senior Developer Relations Engineer for TensorFlow.js, and Laurence Moroney, Lead AI Advocate – both from Google – cover the relationship between data, machine learning, and artificial intelligence to help you discuss and use these technologies with others.
This program has two courses: Google AI for everyone, which can be completed in 4 weeks, and Google AI for JavaScript developers with TensorFlow.js, which can be completed in 7 weeks.
Experience required
No prior experience is required to take this course.
Course content
- How machine learning works and how ML, AI and deep learning fit together.
- Applied AI and what programming AI looks like.
- Introduction and overview of the TensorFlow.js library and the advantages of using ML in JavaScript.
- Ways to consume existing machine learning models.
- How to write custom models from a blank canvas (Linear Regression, Convolutional Neural Network).
- How to use industry-standard pre-made models for object detection or natural language processing.
- How to convert Python models to TensorFlow.js format to run them client side in a web browser.
Key course details
| Best for | Beginners |
| Course fee | $498 |
| Duration | Three months |
| Supported language(s) | English |
| Study resources | Self-paced videos |
| Study format | Self-paced |
| Certificate fee | Included in the course fee |
For more information, also see: Best Machine Learning Platforms
IBM AI Engineering Professional Certificate
Taught by seven experts, this intermediate-level certificate course offered by IBM takes approximately two months at 10 hours a 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.
Experience required
While there is no specific prerequisite for the course, the IBM AI Engineering Professional Certificate is an intermediate-level course which is recommended for individuals with some background knowledge or experience in programming and computer science.
Course content
- Machine Learning with Python.
- Introduction to Deep Learning & 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.
Key course details
| Best for | Intermediate level |
| Course fee | Free (audit), or included with Coursera subscription |
| Duration | Two months at 10 hours a week |
| Supported language(s) | English |
| Assessments | Quizzes |
| Study resources | Coursera platform, video lectures, readings |
| Study format | Self-paced online learning |
| Certificate fee | Included in subscription, or $49 for individual course purchase |
Artificial Intelligence A-Z 2023: Build an AI with ChatGPT4 (Udemy)
With over 231,410 students, Artificial Intelligence A-Z 2023 is a best seller on Udemy. It is best for Artificial Intelligence, Machine Learning, or Deep Learning enthusiasts.
The course teaches learners how to make a virtual self-driving car, make an AI to beat games, Q-learning, deep Q-learning, deep convolutional Q-learning and solve real-world problems with AI. The instructors provide learners with downloadable Python code templates for every AI they build in the course.
Experience required
- High School Maths.
- Basic Python knowledge.
Course content
- Part 0: Fundamentals of Reinforcement Learning.
- Part 1: Deep Q-Learning.
- Part 2: Deep Convolutional Q-Learning.
- Part 3: A3C.
Key course details
| Best for | Beginner or mid-level |
| Course fee | $16.58 per month (personal plan) or $139.99 course purchase fee |
| Duration | 17 hours |
| Supported language(s) | English |
| Assessments | Quizzes and practical projects |
| Study resources |
|
| Study format | Self-paced |
| Certificate fee | Included in the course fee |
Artificial Intelligence Engineer (AIE) Certification Process by the Artificial Intelligence Board of America (ARTiBA)
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 artificial intelligence (AI) practices.
To receive the AIE certification, individuals must undergo a structured evaluation process assessing their knowledge and skills in various AI-related domains. The certification process consists of the following steps:
- Check your eligibility.
- Create your Myartiba account.
- AIE registration confirmation.
- Release of AIE learning material.
- Prepare for the exam & register.
- Certification award.
Experience required
ARTiBA has three registration tracks open for the AiE certification.
- AIE Track 1: Learner should have completed an Associate degree or diploma in Computer Science or Information Technology or any other related discipline plus a minimum of 2 years of work history in any of the computing sub-functions.
- AIE Track 2: Learner should have completed a bachelor’s degree in Computer Science or Information Technology or any other related discipline plus a minimum of 2 years of work-history in any computing sub-functions and must have a good understanding of computer programming.
- AIE Track 3: Current and past students have a Master’s degree in Computer Science or Information Technology or any other related discipline plus a minimum two years of work history in any computing sub-functions; must have a good understanding of computer programming.
Course content
- Essentials of Artificial Intelligence & Machine Learning (27%).
- Essentials of AI & ML Programming (21%).
- Essentials of Natural Language Processing (26%).
- Essentials of Neural Networks & Deep Learning (26%).
Key course details
| Best for | Advanced level |
| Course fee | $550 |
| Duration | N/A |
| Supported language(s) | English |
| Study resources | A copy of the Ai Engineer’s HandbookPractice tests for AiE exam on the myARTiBA candidate dashboardAiE Study Guide |
| Study format | Self-study |
| Certificate fee | Included in the course fee |
Also see: Best Artificial Intelligence Software 2023
Artificial Intelligence Graduate Certificate
Stanford School of Engineering is the issuing body of the Artificial Intelligence Graduate Certificate. This particular certification process is a bit different from the ones we have analyzed so far: it requires a significant time commitment, as it’s designed like a proper degree course – you should expect an average of 15-20 hours per week for the lecture and homework assignments. To earn the certificate, you must complete one required course and three elective courses and receive a B (3.0) or better in each course.
This program covers various aspects of AI, including the principles and techniques of AI, ML, computational logic, NLP, NLU, robotics, Deep Learning, computer vision and more.
Experience required
- Strong backgrounds in programming (C/C++, python), linear algebra, calculus, as well as statistics and probability.
- Bachelor’s degree with a minimum 3.0 grade point average.
- Each course may have individual prerequisites.
Course content
- Artificial intelligence principles and techniques.
- Machine learning.
- Natural Language Processing with deep learning.
- Computer vision.
- Reinforcement learning.
Key course details
| Best for | Those looking for degree-like certification in AI |
| Course fee | $18,928 – $23,296 |
| Duration | 1 to 3 years, depending on the learner’s pace |
| Supported language(s) | English |
| Assessments | Homework, exams |
| Study resources |
|
| Study format | Online, instructor-led |
| Certificate fee | Included in the course fee |
Microsoft Certified: Azure AI Engineer Associate
Azure AI Engineer Associate is a certification offered by Microsoft that validates an individual’s skills in designing and implementing AI solutions using Azure technologies such as Azure Cognitive Services and Azure Applied AI services.
According to Microsoft, this course will allow you to plan and manage an Azure AI solution, implement image and video processing solutions, implement natural language processing solutions, implement knowledge mining solutions, and implement conversational AI solutions.
You can prepare for this certification in two ways: self-paced and instructor-led training.
Experience required
- Knowledge of Python and C# programming.
- Prerequisites vary based on each learning path.
Course Content
- Prepare for AI engineering.
- Provision and manage Azure AI services.
- Process and translate text with Azure AI services.
- Process and translate speech with Azure AI speech services.
- Create a language understanding solution with Azure AI language.
- Build a question-answering solution.
- Build custom text analytics solutions.
- Create conversational AI solutions.
- Create computer vision solutions with Azure AI vision.
- Extract text from images and documents.
- Implement knowledge mining with Azure cognitive search.
- Develop generative AI solutions with Azure Openai service.
Key course details
| Best for | Software engineers |
| Course fee | $165 in the U.S. Price varies based on country |
| Duration | 114 hours 37 minutes |
| Supported language(s) | English and 12 others |
| Assessments | Online exams |
| Study resources |
|
| Study format | Self-paced, instructor-led |
| Certificate fee | Included in the course fee |
Also see: Generative AI Startups
Artificial Intelligence: Business Strategies and Applications
UC Berkeley designed this course for business professionals who are interested in understanding how artificial intelligence (AI) can be leveraged to drive business growth and innovation. The course covers various aspects of AI and its application in different business contexts. It starts by explaining the fundamental concepts of AI and machine learning and then explores neural networks and deep learning, computer vision, and NLP.
Experience required
This course has no specific prerequisites, but knowledge of business management is a plus.
Course Content
- Introduction–AI and business.
- Machine learning basics.
- Neural networks and deep learning.
- Key applications: computer vision & natural language processing.
- Robotics.
- Ai strategy.
- AI and organizations: building your AI team.
- The future of AI in business.
Key course details
| Best for | C-suite executives, senior managers, functional business heads, |
| Course fee | $2,800 |
| Duration | Two months, online 4—6 hours per week |
| Supported language(s) | English |
| Assessments | Capstone Project |
| Study resources | UC Berkeley platform, video lectures, readings, case studies |
| Study format | Instructor-led online learning |
| Certificate fee | Included in the course fee |
AI for Business Leaders
AI for Business Leaders is an online nanodegree program from Udacity that teaches business leaders how to more effectively embed AI and ML technologies into their existing business technologies and strategies. It is considered an intermediate-level training program with real-world, hands-on projects, but beginners in AI who bring extensive business skills and expertise to the table can benefit from this course as well.
Experience required
Certificate students should have familiarity with basic probability and descriptive statistics. Multiple years of experience in a business strategy role is preferred.
Course content
Lessons in this program include the following:
- AI for Business Leaders Executive Program Introduction
- Introduction to AI for Business Leaders
- Getting Help
- The Paradigm Shift
- The Math Behind the magic
- Architectures of AI Systems
- Working with Data
- Accuracy, Bias, and Ethics
- Gathering Feedback
- Thinking Bigger
- Delivering an ML/AI Strategy
A certificate is awarded based on the completion of these lessons and courses.
Key course details
| Best for | Business leaders and strategists interested in using ML and AI more effectively |
| Course fee | Udacity subscription for a minimum of $249 per month or $2,390 per year. |
| Duration | Two months |
| Supported language(s) | Unknown |
| Study resources |
|
| Study format | Self-paced |
| Certificate fee | Included with course fee |
Jetson AI Certification
The Jetson AI Specialist certification from NVIDIA Deep Learning Institute is a certification and training program that gives users a chance to learn and tailor AI skills to Jetson embedded computing technology and similar systems for machine learning applications. Students of this program will learn through a combination of hands-on, open-source projects and project-based assessments.
Experience required
For the Jetson AI Specialist certification, it’s recommended that students have a basic familiarity with Python and Linux. Students of the Jetson AI Ambassador certification program should also have teaching or training experience.
Course content
The Jetson AI Specialist certification requires all students to complete the Jetson AI Fundamentals course, which includes the following sections:
- NVIDIA Deep Learning Institute’s Getting Started with AI on Jetson Nano course
- JetBot (optional)
- Hello AI World
Users who are interested in receiving a certificate must also complete the Getting Started with AI on Jetson Nano DLI course certificate and a project-based assessment.
Key course details
| Best for | NVIDIA product users and open-source developers |
| Course fee | Free |
| Duration | Four hours of online content plus project time |
| Supported language(s) | Unknown |
| Study resources |
|
| Study format | Self-paced |
| Certificate fee | Free |
Professional Machine Learning Engineer (Google Cloud)
The Professional Machine Learning Engineer certification from Google Cloud is a skill-based exam and certification that determines how effectively ML engineers can design and architect, develop, automate and orchestrate, and monitor machine learning developments on Google Cloud platforms and technologies. No coursework is required to earn this certification, however many users elect to complete a relevant Google Cloud training path to prepare for the exam.
Experience required
No prior experience is required, though it’s a good idea to have at least three years of relevant experience and at least one year of experience working with relevant Google Cloud technologies.
Course content
No specific coursework is required to complete the 50 to 60 multiple choice and multiple select questions that make up the certification exam, which can be taken in person or online. However, many students start with the exam guide and sample questions or complete the Machine Learning Engineer learning path, which includes online and in-person training courses.
Key course details
| Best for | Machine learning engineers with at least three years of experience and some experience with Google platforms. |
| Course fee | No course(s) required to complete certification |
| Duration | Two hours |
| Supported language(s) | English, German, Spanish, French, Portuguese, Mandarin, and more |
| Study resources |
|
| Study format | Self-paced studying with a timed examination |
| Certificate fee | $200 |
Post Graduate Program in AI and Machine Learning
The Post Graduate Program in AI and Machine Learning is a collaboration among Simplilearn, Purdue University, and IBM for business professionals who want to improve their AI and ML knowledge and skills through an online bootcamp format. Many users select this certification program for its collaborative learning format and for the blend of academic and applied business AI knowledge they can gain from Purdue and IBM.
Experience required
Students of this bootcamp program should have at least two years of work experience, a bachelor’s degree, and a basic understanding of mathematics and programming.
Course content
The program is split into foundations, core, capstone, and elective courses:
- Foundations: Mathematics & Statistics Essentials
- Foundations: Programming Refresher
- Foundations: Python for Data Science (IBM)
- Core: Applied Data Science with Python
- Core: Machine Learning
- Core: Deep Learning with TensorFlow (IBM)
- Core: Deep Learning Specialization
- Core: Essentials of Generative AI, Prompt Engineering & ChatGPT
- Capstone
- Elective master classes and advanced courses on computer vision, NLP, speech recognition, reinforcement learning, etc.
Key course details
| Best for | Business leaders and emerging leaders looking to advance their careers with applied AI and ML knowledge |
| Course fee | $4,500 |
| Duration | 11 months |
| Supported language(s) | Unknown |
| Study resources |
|
| Study format | Online courses with cohort-wide learning schedules |
| Certificate fee | Included with course fee |
AI Applications for Growth
AI Applications for Growth from Northwestern University’s Kellogg School of Management is an executive education program that teaches business leaders how to use AI and ML in a way that benefits the business and customers alike. It is an online program that is primarily designed for C-level executives and business leaders across sales, marketing, and IT roles.
Experience required
No prior experience is required, though the program is catered to the experience and workplace scenarios of business executives.
Course content
The program is primarily divided into eight module topics:
- Module One: the AI Revolution: Trends, Tools, and Applications
- Module Two: AI and Customer Experience Management
- Module Three: AI and Operations Management
- Module Four: AI and Business Support Functions
- Module Five: AI Applications in Select Industries
- Module Six: AI Applications in Autonomous Vehicles and Transportation
- Module Seven: Transforming Your Business with AI: Strategy and Capabilities
- Module Eight: Transforming Your Business with AI: Organization and Society
Key course details
| Best for | Business executives and IT managers and leaders |
| Course fee | $2,850 |
| Duration | Two months at four to six hours per week (estimated) |
| Supported language(s) | Unknown |
| Study resources |
|
| Study format | Self-paced |
| Certificate fee | Included in course fee |
Professional Certificate Program in Machine Learning & Artificial Intelligence
The Professional Certificate Program in Machine Learning & Artificial Intelligence is a professional education certification program from MIT that emphasizes the applications of AI and ML in a few emerging areas, like the Internet of Things (IoT), smart manufacturing, computer vision, and industry-specific automations and analytics. It is ideally designed for midlevel business leaders who still manage some of the day-to-day operations that AI touches.
Experience required
Though no specific experience is required, the program is designed for business professionals and tech leaders with at least three years of professional experience and at least a bachelor’s degree in a technical field.
Course content
All students must complete the five days of core coursework in the following two courses:
- Machine Learning for Big Data and Text Processing: Foundations
- Machine Learning for Big Data and Text Processing: Advanced
Students must complete an additional 11 days of coursework from the program’s elective catalog:
- Advanced Data Analytics for IIoT and Smart Manufacturing
- AI for Computational Design and Manufacturing
- AI Strategies and Roadmap: Systems Engineering Approach to AI Development and Deployment
- Applied Data Science Program: Leveraging AI for Effective Decision-Making
- Bioprocess Data Analytics and Machine Learning
- Deep Learning for AI and Computer Vision
- Designing Efficient Deep Learning Systems
- Foundations of Data and Models: Regression Analysis
- Graph Algorithms and Machine Learning
- Machine Learning for Healthcare
- Machine Learning for Materials Informatics
- Reinforcement Learning
- Advanced Reinforcement Learning
Key course details
| Best for | Current professionals with at least three years of experience in a technical field and other professionals looking to integrate AI and ML into their workflows |
| Course fee | Prices per course vary; no overall program cost information is available |
| Duration | Self-paced, though all students must complete course requirements within 36 months; the program includes 16 days of qualifying Short Programs courses in Professional Education |
| Supported language(s) | Unknown |
| Study resources |
|
| Study format | In-person and online scheduled courses and lectures |
| Certificate fee | $325 application fee; no additional certificate costs |
AI for Non-Technical People: A Hands-On Beginner’s Course
AI for Non-Technical People: A Hands-On Beginner’s Course is a short AI training course from Udemy that is designed specifically for business professionals and individuals with no AI or technical experience. The program focuses on the history of AI, practical applications of AI, and the basics of how to build an AI model. Compared to most courses in this guide, this is a great starting point if you’re simply interested in AI but don’t have any foundational skills or experience in related subject matter.
Experience required
No experience is necessary to complete this course and certification.
Course content
The course is divided into four main modules:
- Introduction to Artificial Intelligence
- Fundamentals of AI
- Ethical Considerations
- Hands On Project
In the hands-on project portion, users will receive the training to build and test an audio model.
Key course details
| Best for | Beginners who are interested in AI and how it works |
| Course fee | $11.99 to $39.99, depending on time of purchase |
| Duration | 1 hour and 16 minutes of online training plus time for hands-on project completion |
| Supported language(s) | English |
| Study resources |
|
| Study format | Self-paced |
| Certificate fee | Included with course fee |
Intel Edge AI Certification
The Intel Edge AI Certification is a certification program offered by Intel to users who want to demonstrate their hands-on skills with Intel edge, AI, and other developer tools. The certification program is less focused on traditional coursework and more focused on hands-on projects and skill development. Though this certification is highly specific to Intel and its products, it’s a good training ground for anyone who wants a more technical training program.
Experience required
Several prerequisite are required to complete this Intel certification:
- Intermediate Python programming knowledge
- Experience working with JupyterLab or Jupyter Notebook
- Knowledge of CNN-based architectures and deep learning layers
- Experience working with the Linux command line
- Experience with OpenCV
Course content
Rather than taking premade coursework, students of this certification will complete specific projects and build their own edge AI solutions portfolio. These are some of the projects that are part of this certification program:
- Supermarket Retail Loss Prevention with Classification
- Industrial Worker Safety with Object Detection
- Smart City Data Augmentation with Style Transfer
Key course details
| Best for | Intel product users and professionals interested in developing AI and edge computing competencies |
| Course fee | Free |
| Duration | 13 foundational learning plan courses plus three hands-on modules; self-paced, so time to completion varies |
| Supported language(s) | English, German, Spanish, French, Portuguese, Mandarin, Vietnamese, Bahasa Indonesia, and more |
| Study resources |
|
| Study format | Self-paced |
| Certificate fee | Certain aspects of certification may cost an additional $99 per year |
Graduate Certificate in Ethical Artificial Intelligence
The Graduate Certificate in Ethical Artificial Intelligence from San Francisco State University is a more academic approach to AI certification that considers the ethics of AI from all angles, using courses in computer science, business management, and philosophy to illustrate the importance of ethical practices with emerging technologies. The course culminates in a 10-page research paper, making this a much more collegiate and academic program than most others on this list.
Experience required
Students of this program must be current graduate students at SFSU or be willing to apply for admission into a graduate business certificate program and have at least a bachelor’s degree. Ideally, students will come from a philosophy, business, or computer science background, as these are the primary disciplines covered in the program.
Course content
One course from each of the following categorical groups must be completed to earn this graduate certificate:
- AI Technologies and Applications (computer science coursework)
- AI Explainability and Ethics
- Data Mining
- Pattern Analysis and Machine Intelligence
- Business Ethics and Regulatory Compliance (management coursework)
- Ethics and Compliance in Business
- Ethical Principles (philosophy coursework)
- Philosophy and Current Applications of Artificial Intelligence
- Philosophical Issues in Artificial Intelligence
All students must also complete an independent study and research/reflection paper from the perspective of their chosen discipline.
Key course details
| Best for | Current San Francisco State University graduate students and others looking to learn about AI in a multidisciplinary program that covers the philosophy, business strategy, and technical elements behind AI |
| Course fee | Dependent on current registration status with SFSU |
| Duration | 10 course units, with three each coming from approved computer science, business management, and philosophy courses; 1 course unit for independent study |
| Supported language(s) | Unknown |
| Study resources |
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| Study format | In-person and online scheduled courses |
| Certificate fee | All students must pay a $7 processing fee for the certification |
ChatGPT / AI Ethics: Ethical Intelligence in an AI World
ChatGPT / AI Ethics: Ethical Intelligence in an AI World is a short certification course and program from Udemy that focuses on ethical AI from the angle of some of the emerging generative AI tools that are becoming popular in business and everyday use. Upon completion of this course, students should be able to apply ethical principles and best practices to the usage of ChatGPT and similar generative AI platforms.
Experience required
No experience is necessary to complete this course and certification.
Course content
The course is divided into four main sections with multiple lectures each:
- Introduction
- The 5 Ethical Principles Applied to Working with AI / Artificial Intelligence
- Ethics in the Age of AI: Unraveling Deeper Issues Amidst Current Concerns
- Concluding Section
Key course details
| Best for | Beginners who are looking to begin using generative AI tools or who are interested in using them in an ethical, compliant way |
| Course fee | $11.99 to $54.99, depending on time of purchase |
| Duration | Two hours of video training |
| Supported language(s) | English |
| Study resources |
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| Study format | Self-paced |
| Certificate fee | Included with course fee |
Benefits of AI Courses and Certifications
There are several compelling reasons to take AI courses and certifications:
- Skill development: AI courses provide an opportunity to develop new skills and gain a deep understanding of artificial intelligence concepts.
- Career advancement: By acquiring AI skills and certifications, you can stand out, increase your employability, and access higher-paying job roles.
- Industry recognition: AI certifications serve as a recognized proof of your competency.
- Personal growth: AI courses challenge you to think critically, innovate, and approach problems from a different perspective.
- Market demand: The skills gained through AI courses and certifications are highly sought after by industries across sectors, including healthcare, finance, retail, manufacturing, and more. These courses can open up diverse job prospects and increase your job market value.
How to Choose the Right AI Certification Course
When researching the best AI certification course for you, you must consider certain factors unique to you. The best AI certification course for you will depend on your learning objectives, current field/industry knowledge, and learning budget. The list below can help you select the best course for you.
- Learning objectives: Look for a course that covers the specific areas of AI that you are interested in or want to specialize in, such as machine learning, natural language processing, or computer vision. Also consider the depth and breadth of the course curriculum to ensure it aligns with your learning goals.
- Course format and delivery: Consider your preferred mode of learning, whether it’s online, in-person classroom training, or a combination of both.
- Instructor expertise: Check the qualifications, industry experience, and expertise of the course instructors.
- Course resources: Consider the support and resources available during and after the course.
- Cost: Evaluate the course fees and compare them with the value and benefits you will receive. Consider any financial aid or scholarships available.
- Certification and career outcomes: Check if the course provides a recognized certification upon completion and consider the career outcomes and job placement records of the course graduates.
Remember that AI is a practical field, so seek courses that emphasize hands-on projects and real-world applications.
For more information, also see: Top Robotics Startups
Bottom Line: Which AI Certification is Right for You?
The right AI certification for you depends on your specific interests, career goals, and existing knowledge in the field. Truly finding the best course for you means evaluating the full range of AI training, but here are a few picks based on our analysis:
- UC Berkeley Artificial Intelligence: Business Strategies and Applications is best for business executives.
- Microsoft Certified: Azure AI Engineer Associate is ideal for developers interested in Azure AI services.
- AI for Everyone and Artificial Intelligence A-Z 2023: Build an AI with ChatGPT4 are best for beginners.
Read next: The AI Market: An Overview