Artificial intelligence has become a key enabler in transforming business and making it more competitive. As per the analysis done by PWC, by 2030, AI could contribute up to $15.7 trillion to the global economy. When business functions hand in hand with AI, it becomes more productive by automating processes. With augmented intelligence, it boosts up the existing workforce. Nowadays, the majority of organizations are implementing AI in their workforce. So, to immerse in AI technology-based work certification on the same plays a major role. To succeed in a future powered by artificial intelligence, you have to showcase yourself as a subject matter expert. So, obtaining a certificate can place you as a subject matter expert to potential employers. In this blog, we have listed down the 10 most effective online artificial intelligence certifications which you may find helpful.

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Top 10 Online Artificial Intelligence certifications

1. Designing and Building AI Products and Services (MIT xPRO)

This is an ideal program for people who work in the AI field and want to gain advanced capabilities. Created by skilled professionals of MIT xPRO, this curriculum focuses on the design philosophies and applications of AI across various industries. By pursuing this course, one can learn how to build an AI-based product proposal and represent it to internal stakeholders or investors for funding. Besides, it gives you a solid understanding of how deploying the right AI technologies can help you to automate routine tasks quickly while gaining insights via data analytics. The curriculum offers insights and examples from renowned MIT faculty and a professional certificate to showcase your knowledge and skills.

Prerequisites: UI/UX designers, technical product managers, technology professionals and consultants, entrepreneurs, and AI startup founders.

Topics outline –

• Introduction to the Artificial Intelligence Design Process
• Artificial Intelligence Technology Fundamentals – Machine Learning
• Artificial Intelligence Technology Fundamentals – Deep Learning
• Designing Artificial Machines to Solve Problems
• Designing Intelligent Human-Computer Interaction (HCI)
• Superminds: Designing Organizations that Combine Artificial and Human Intelligence
• Marketplace Frontiers of AI Design: Research
• Marketplace Frontiers of AI Design: Practice

Duration – 8 weeks
6 hours/week Online

2. Machine Learning AI Certification by Stanford University (Coursera)

If your motto is to learn Machine Learning, then don’t look further. Created by Andrew Ng, Professor at Stanford University, more than 2,612,800 students & professionals globally have enrolled in this program, who have rated it very highly. This course provides stress on introduction to the core concepts of this field, such as supervised learning, unsupervised learning, support vector machines, kernel, and neural networks. Draw from numerous case studies and applications and get hands-on to apply the theoretical concepts to practice. By the end of the classes, you will have the confidence to apply your knowledge to real-life scenarios.

Prerequisites: Bachelor’s degree with a minimum 3.0-grade point average; mastery of the prerequisite subject matter, including statistics and probability, linear algebra, and calculus; and experience programming in C/C++, Java, Python, or other similar languages.

Topics include:

• Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks).
• Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning).
• Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI).
• The course will also draw from numerous case studies and applications so that you’ll also learn how to apply learning algorithms to building smart robots (perception, control), text understanding (web search, anti-spam), computer vision, medical informatics, audio, database mining, and other areas.

Duration – Approx. 61 hours to complete
100% online

3. IBM Applied AI Professional Certificate (Coursera)

Designed by the global leader in IBM, the Professional Certificate in Artificial Intelligence caters to professionals who want to work as AI developers. Through this program you will gain an in-depth understanding of AI technology, its applications, and use cases. You will be familiar with concepts and tools such as machine learning, data science, natural language processing, image classification, image processing, IBM Watson AI services, OpenCV, and APIs.
With this professional certificate without a programming background, you will learn practical Python skills to design, build, and deploy AI applications on the web. These courses will also enable you to apply pre-built AI intelligence to your products and solutions

Prerequisites: Open to everyone.

Topics covered –

• What is Data science?
• Tools for data science
• Data science methodology
• Python for data science, AI, and development
• Python project for data science
• Databases and SQL for data science with Python
• Data analysis with Python
• Data visualization with Python
• Machine learning with Python
• Applied science Capstone

Duration – Approx 11 months
100% Online

4. Artificial Intelligence: Business Strategies and Applications (Berkeley ExecEd)

This program will introduce you to basic applications of AI, its capabilities, and its potential while offering in-depth information about automation, machine learning, and robotics. Completing the capstone project will make you eligible to receive the certificate of completion.

Prerequisites – Senior leaders including C-suite executives, senior managers, executives, Functional business heads, Mid-career professionals, Data scientists and analysts, and professionals eager to upskill and advance in their careers.

Topics covered –

• 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
• Capstone Business Challenge Project

Duration – 2 months
4-6 hours/week

5. Artificial Intelligence Courses (Udemy)

If you want to access all the relevant and best courses on artificial intelligence, then Udemy is the best resource for you. It offers a list of numerous AI courses focused on expanding your skills and making you an expert in this field. Taking these courses will not only provide you with the fundamental concepts of AI, but you will be very well equipped with the significant aspects and techniques of artificial intelligence. More than that, all of these courses are available with a 30-day free trial, so you can review each session carefully and then select the desired course.

Prerequisites: Anyone interested in AI, machine learning, or deep learning. High school math and basic Python knowledge, but no previous coding experience required.

Courses covered –
Please follow the link provided in the course title above.

6. AI For Everyone by Andrew Ng (Coursera)

Learning Artificial intelligence is not easy because it covers the most complex topics in technology. So if you want to learn the concepts easy way, then it is worth to look at this course.

In the classes, you will learn the meaning behind basic and crucial terminologies, what AI can do and cannot do, spot opportunities to apply AI solutions to problems in your organization, and more. By the end of the lectures, you will be proficient in the business aspects of AI and apply them aptly in relevant situations. The course was created by Andrew Ng, the pioneer in the field of artificial intelligence and the founder of Coursera.

Prerequisites – Engineers and non-technical professionals.

Topics covered-

• The meaning behind common AI terminology, including neural networks, machine learning, deep learning, and data science
• What AI realistically can–and cannot–do
• How to spot opportunities to apply AI to problems in your own organization
• What it feels like to build machine learning and data science projects
• How to work with an AI team and build an AI strategy in your company
• How to navigate ethical and societal discussions surrounding AI

Duration: 4 weeks, 2 to 3 hours per week

7.Applied Machine Learning Certification Program (Purdue University)

Ideally designed for working professionals and graduates, this applied machine learning program will provide real-world insights into machine learning applications. Enrolling in this subjective program will help you learn about Python programming basics, data operations, shell scripting, conditional statements, and the Django framework. You’ll gain knowledge of essential topics like feature engineering, time series modeling, recommendation systems, feature selection, and decision tree. Industry experts will deliver the program via 8X higher live interaction with 48 hours of live online classes. After concluding the program, you’ll receive a digital certificate of completion signed by Purdue University.

Prerequisite – Basic knowledge of Python and statistics analysis are covered within this machine learning program. Therefore it can be taken up by graduates and working professionals alike.

Topics covered –

• Statistics essential
• Python training
• Data science foundations
• Applied machine learning
• Capstone project

Duration – 4 months, 8 hours/week

8. Deep Learning by Andrew Ng (Coursera)

If you want to jumpstart a career in AI, then this specialization will help you achieve that. It comprises 5 courses covering foundational topics of Deep Learning, building neural networks, and leading successful ML projects. Along with this, there are opportunities to work on case studies from various real-world industries. The practical assignments will allow you to practice the concepts in Python and in Tensorflow. Additionally, there are talks from top leaders in the field that will motivate you and help you understand the scenarios in this line of work.

Prerequisites – Anyone can attend the course.

Topics covered –

• Neural networks and deep learning
• Improving deep neural networks
• Structuring machine learning projects
• Convolutional neural networks
• Sequence models

Duration – Approx 5 months

9. Introduction to Artificial Intelligence by IBM (Coursera)

Offered by IBM, this introductory course will guide you to the basics of artificial intelligence. This course will teach you what AI is and how it is used in the software or app development industry. During the course, you will be exposed to various issues and concerns that surround artificial intelligence, like ethics and bias and jobs. After completing the course, you will

Also, demonstrate AI in action with a mini project that is designed to test your knowledge of AI. Moreover, after finishing the project, you will also receive your certificate of completion from Udacity.

Prerequisites – Anyone can pursue this course

Topics covered –

• What is AI? Applications and examples
• AI concepts, terminology, and application areas
• AI issues, concerns, and ethical considerations
• The future with AI and AI in action

Duration – 4 weeks, 1-2 hours/week

10. Machine Learning: Fundamentals and Algorithms (Carnegie Mellon University)

Created in collaboration with Carnegie Mellon University’s School of Computer Science Executive Education, this advanced program is intended to help you enhance your skills in machine learning and artificial intelligence. Joining this pragmatic curriculum will provide you with the technical knowledge and analytical methods required to train yourself for the next generation of innovation. You’ll learn how to use various concepts from probability, linear algebra, statistics, and optimization to determine and refine machine learning algorithms’ inner workings.

Prerequisites – This course requires a functional knowledge of high school level linear algebra, calculus, probability, statistics, and Python programming. Engineers, Data Analytics Professionals, Technical Managers/Directors of Data Functions.

Topics covered –

• Decision Trees
• K-Nearest Neighbor
• Model Selection
• Linear Regression
• Optimization
• Binary Logistic Regression
• Regularization
• Neural Networks
• Backward Propagation
• K-Means and Others Learning Paradigms

Duration – 10 weeks, 5-10 hours/week