Top 10 Artificial Intelligence Courses, Certifications & Classes Online [2024]

Artificial Intelligence (AI) is the skill of the future. It has been estimated that by 2030, AI market will contribute more than $15 trillion to the world economy. There is a huge skill shortage in the field of artificial intelligence therefore if you are entering the workforce, getting skilled in AI can guarantee a promising future-proof career. For those already in the workforce, re-skilling and up-skilling with future oriented job skills like AI is more relevant now than ever.

We are seeing artificial intelligence in a myriad of applications across industries. Be it healthcare, finance, mobile, automobile, smart home devices, music and movie recommendation services, retail, security surveillance, fraud detection, virtual player games, social media apps, the possibilities are endless. Almost every business is trying to implement AI in their processes and products. Learning AI can therefore open a world of opportunities for anyone. A combination of Artificial Intelligence, Machine learning and deep learning can chart out a way to great career prospects.

Learning Artificial Intelligence (though not very easy) has become very accessible now with a variety of courses and trainings available online. These are taught by best AI educators, researchers and experts, and often come at a cost much less than a typical college course. Some of these classes are very comprehensive and include curriculum of an equivalent college degree. Some of these are even available for free and are perfect to get a glimpse into the world of AI.

To help you make the right choice, we’ve compiled this list of best artificial intelligence courses, classes, certifications, training programs and tutorials available online that you can use to gain a good grounding in the field of AI.

1. Machine Learning by Stanford University (Coursera)

This Stanford Machine Learning Certification has been created by Andrew Ng, the most renowned expert in AI and Machine Learning, cofounder of Coursera, founding lead of Google’s deep learning research unit Google Brain, former head of AI at Baidu, and currently CEO at Landing AI. It is an updated version of Andrew’s most popular Machine Learning course, that was taken by over 4.8 million learners on Coursera.

The popularity of this new, updated foundational program in AI and Machine Learning can be gauged from the fact that around 50K students and professionals signed up for the program in the first few weeks of its launch and 95% of them have given it a 5-star rating. Undoubtedly, AI experts cite this program as the single most important resource for anyone looking to learn AI and ML.

This is a three course specialization that introduces learners to the core ideas of AI, machine learning, datamining and statistical pattern recognition. It imparts them a good grounding in the mathematical, statistical, and computer science fundamentals that form the basis of automated learning machines. The course material is very extensive and requires around 3 months to complete with about 9-10 hours of effort per week. It covers the following topics:

• Difference between supervised and unsupervised learning and regression and classification tasks
• Build and train linear regression models
• Implement and understand the purpose of a cost function
• Methods for improving machine learning models by choosing the learning rate, plotting the learning curve, performing feature engineering, and applying polynomial regression
• Logistic regression model for classification
• Build and train a neural network with TensorFlow
• Build and use decision trees and tree ensemble methods, including random forests and boosted trees
• Applying machine learning algorithms with large datasets
• Performance of a machine learning system with multiple parts
• Best practices for applying machine learning
• Use unsupervised learning techniques
• Build recommender systems with a collaborative filtering approach and a content-based deep learning method
• Build a deep reinforcement learning model

For programming assignments, the courses use Python, which is a simple way to learn the fundamentals of ML.

Numerous case studies and applications are included in the program to help learners get hands-on practice. They get 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.

Key Highlights

• Highest rated amongst the top free Machine Learning and AI courses available online
• Excellent fit for beginners in the field of artificial intelligence and machine learning
• Learn about the most effective machine learning techniques, and gain practice implementing them
• Learn about some of Silicon Valley’s best practices in the field of Machine Learning and AI innovation
• Gain the practical know-how needed to quickly and powerfully apply ML techniques to new real life situations and problems
• Study the courses for free; option to get a paid certificate for showcasing your learning of AI and ML skills

Duration : Approx 3 months, 9 hours per week
Rating : 4.9
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2. Deep Learning Specialization by Andrew Ng (Coursera)

The part of AI that is rising rapidly and driving a lot of developments and transformations that AI is touted for is Deep Learning. This Coursera Deep Learning specialization created and taught by Andrew Ng is a more advanced course series for those looking to learn about AI and deep learning, how to apply it to solve problems and build a career in AI. Since it is not an entry level program, learners are expected to have Python programming and mathematics skills and some knowledge and experience in machine learning. This specialization is in fact cited as the next logical follow up to Andrew Ng’s Machine Learning course on Coursera.

This is a five course specialization where students learn the important technical skills and tools of deep learning. These courses cover the following topics:

• Foundations of Neural networks
• How to build deep neural networks and train them on data
• Practical aspects of deep learning, like hyperparameter tuning, regularizations and optimization
• Structure machine learning projects
• How to set up train/dev/test sets
• End-to-End deep learning and when you should use it
• Build Convolutional neural networks and apply to image data
• Sequence models and how to apply them to natural language processing problems

Alongside this, courses cover various real-world case studies from healthcare, autonomous driving, sign language reading, music generation, and natural language processing. The students get to work on many exciting projects from building a face recognition system, to building a simple translation system, and more. Furthermore, there are interviews and discussions with top leaders and pioneers in the field that give students career advice, inspiration and help them comprehend situations that they are likely to face in the real world.

Key Highlights

• Master the theory of AI and deep learning, and see how it is applied in industry
• Practice in Python and TensorFlow
• Understand industry best-practices for building deep learning applications
• Get advice from deep learning experts and leaders in the field
• Be able to implement a neural network in TensorFlow
• Understand how to diagnose errors in a machine learning system and prioritise directions for reducing error
• Understand how to build and train Recurrent Neural Networks (RNNs), and commonly-used variants such as GRUs and LSTMs

Duration : 4 months, 5 hours per week
Rating : 4.8
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3. IBM Applied AI Professional Certificate (Coursera)

This Professional Certificate program in Artificial Intelligence has been created by IBM, the global leader in Tech and one of the pioneers in AI innovation. It is aimed for those who want to learn the skills to work as AI developers. It imparts firm understanding of AI, its applications and use cases. It introduces learners to the concepts and tools like machine learning, data science, natural language processing, image classification, image processing, IBM Watson AI services, OpenCV, and APIs. Students also learn to get started with using pre-built AI smarts without having to create AI models and backends from scratch.

This is a beginner level AI Certification comprising of 6 courses and can be taken by learners with both technical and non-technical backgrounds. The first three courses of the program also constitute the complete AI Foundations For Everyone Specialization. These courses do not require any programming knowledge and have no prerequisites. They are:

1. Introduction to Artificial Intelligence (AI) – This is a very popular course and a part of multiple specializations. It introduces the basics of AI and how AI can be used in various industries. It can be taken by everyone whether developers, managers, executives or students.
2. Getting Started with AI using IBM Watson – This course introduces learners to various IBM Watson services and APIs and what they can be used for.
3. Building AI Powered Chatbots Without Programming – This course teaches how to plan, implement, test, and deploy AI powered chatbots on a website.

The final two courses require some knowledge of Python to build and deploy AI applications. An introductory Python course is included in the program for learners with no programming background. So the remaining 3 courses in the program are the following:

4. Python for Data Science and AI – This course covers Python fundamentals, including data structures and data analysis, with complete hands-on exercises.
5. Building AI Applications with Watson APIs – In this course, learners utilize multiple Watson AI services and APIs together to build smart and interactive applications.
6. Introduction to Computer Vision with Watson and OpenCV – In this course, learners understand Computer vision and its applications, also build and train custom image classifiers using Watson, Python and OpenCV.

The curriculum of this program is very extensive and includes number of hands-on learning projects, including building your own AI chatbot; building, training and testing custom image classifiers; creating a computer vision web application and deploying it to the Cloud.

Key Highlights

• Gain the skills to create AI powered applications
• Practice basics of Python and understand how to apply Python programming concepts for data science and AI
• Learn to use IBM Watson AI services and APIs to design, build & deploy AI-powered applications on the web with minimal coding
• Learn how AI-powered chatbot technology works and its applications
• Learn to create and deploy speech enabled virtual assistants with domain intelligence to Facebook etc.
• Explain what computer vision is and its applications
• Especially beneficial for those who want to become builders and developers of AI solutions
• Earn a digital badge from IBM for proficiency in Applied AI in addition to Professional Certificate from Coursera

Duration : 3-6 months, 2-4 hours per week
Rating : 4.6
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4. IBM AI Engineering Professional Certificate (Coursera)

This is another popular certificate course in artificial intelligence from IBM. It has been designed to impart the skills and tools necessary for starting a career as an AI or ML Engineer. It is suitable for existing professionals such as AI developers and data scientists who want to level up with machine learning and deep learning skills, as well as students looking to enter the workforce with highly in-demand AI and ML skills.

The program comprises of six self-paced courses that provide learners with a complete understanding of machine learning and deep learning concepts and how to apply them to real world projects. It covers the following topics:

• Develop foundational skills in Machine Learning, and implement supervised and unsupervised machine learning models using Python libraries such as SciPy and ScikitLearn
• Scale machine learning on Big Data using Apache Spark
• Introduction to Deep Learning and Neural Networks
• Discussion of autoencoders, restricted Boltzmann machines, convolutional networks, recursive neural networks and recurrent networks
• Building deep learning models and networks using Keras library
• Using PyTorch library for learning and building deep neural networks
• Working with Tensorflow to develop, tune and deploy deep learning models
• Capstone Project to apply deep learning skills and demonstrate ability to solve real world problems

This IBM AI certificate program takes a very practical and hands-on approach to AI Engineering. All courses have hands-on labs and projects including use cases and real world applications of AI.

This is an intermediate level program and requires prior knowledge and background in certain areas like high school level mathematics, Python programming and using Jupyter notebooks. In addition to these, knowledge of SQL, statistical analysis and some linear algebra are also very helpful. For learners who do not have foundational data science or AI skills, IBM recommends that they first take IBM Applied AI professional certificate or IBM Data Science professional certificate course, before starting this program.

Key Highlights

• Curriculum designed by a panel of top IBM experts in the field
• Understand machine learning algorithms including classification, regression, clustering, and dimensional reduction
• Deploy machine learning algorithms and pipelines on Apache Spark
• Explain foundational TensorFlow concepts like main functions, operations & execution pipelines
• Determine what kind of deep learning method to use in which situation and build a deep learning model to solve a real problem
• Be able to build, train, and deploy different types of deep architectures
• Demonstrate ability to present and communicate outcomes of deep learning projects
• Option to audit all courses at no charge; verified certificate and IBM badge can be earned at a low monthly fee

Duration : 3-4 months, 12 hours per week
Rating : 4.4
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5. MicroMasters® Program in Artificial Intelligence by Columbia University (edX)

This Artificial Intelligence Certification program is offered by Columbia University, via the edX platform. It is a very rigorous, graduate-level professional program that represents 25% of the coursework towards a Master’s degree in Computer Science at Columbia.

The program consists of a series of 4 courses that serve as a foundation of expertise in artificial intelligence and machine learning and two of its key applications – robotics and computer animation. These courses are as follows:

1. Artificial Intelligence – This course provides an introduction to fundamentals of AI and how to apply them. It teaches how to design intelligent agents or bots that extract data online using certain criteria or keywords.
2. Machine Learning – This course teaches the essentials of machine learning and algorithms, including supervised learning techniques for regression and classification, unsupervised learning techniques for data modeling and analysis, probabilistic versus non-probabilistic modelling and optimization and inference algorithms.
3. Robotics – This course covers the fundamentals of robotics focusing on both the mind and the body. It teaches the core techniques for representing robots that perform real tasks in the real world.
4. Animation and CGI Motion – This course examines the basic rules of motions and how to turn them into computer programs.

Apart from the video lectures, the program includes quizzes, programming assignments, peer-reviewed assignments, and community discussion forums. There is an equal emphasis on theory and practical, with numerous exercises and projects scattered throughout the courses. Learners get to build a basic search agent, AI powered games and linear regression models.

The program assumes a basic understanding of statistics, college level algebra, calculus and knowledge of Python programming language.

The entire program is available for free online, with an option to pay for certification. Learners who subscribe for the paid certificates and successfully complete all courses receive a MicroMasters program certificate from Columbia University.

Key Highlights

• Get a solid understanding of the foundational principles of AI
• Learn from experts in the field who teach at Columbia University
• Apply concepts of machine learning to real life problems and applications
• Design and harness the power of Neural Networks
• Learn to design intelligent agents used as news retrieval services, for online shopping and automated tasks
• Explore the applications of AI in fields of robotics, vision and physical simulation
• Exercises and assignments that help to comprehend real world issues and come up with appropriate AI solutions

Duration : 10-12 months, 8-10 hours per week
Rating : 4.6
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6. Artificial Intelligence Nanodegree Programs (Udacity)

Udacity is offering multiple Nanodegree programs in its School of Artificial Intelligence. Nanodegrees are very extensive programs comprising of a larger course of study, usually presented in partnership with leading companies or universities. For those who want to make a career in AI, there are some excellent, powerful, career-centered programs that can be very helpful to advance in the field of AI by spending as little as 8-10 hours per week. There are choices for every level of knowledge and experience from complete beginner focussed programs to those intended for more advanced learners.

Some of the best Udacity AI training programs include:

• AI Product Manager – Covers AI products, creating high quality datasets, training ML models, measuring post-deployment impact and updating models and scaling your AI products.
• Intro to Machine Learning with TensorFlow – Covers foundational machine learning algorithms, supervised models, deep and unsupervised learning, neural network design and training in TensorFlow.
• AI Programming with Python – Covers the essential foundations of AI: the programming tools (Python, NumPy, PyTorch, Anaconda, pandas, and Matplotlib), the math (calculus and linear algebra), and the key techniques of neural networks (gradient descent and backpropagation).
• Artificial Intelligence for Trading – Covers basics of quantitative analysis, including data processing, trading signal generation, and portfolio management. Also teaches how to develop trading strategies, and construct a multi-factor model with optimization.
• Computer Vision – Covers computer vision and deep learning techniques—from basic image processing, to building and customizing Convolutional Neural Networks, Recurrent Neural Networks (RNN), Simultaneous Localization and Mapping (SLAM), Object Tracking, Image Classification
• Natural Language Processing – Covers Machine Learning, Speech Recognition, Sentiment Analysis, Machine Translation, Part of Speech Tagging
• Deep Reinforcement Learning – Covers Reinforcement Learning, Neural Networks, PyTorch, Deep Q-Networks (DQN), Deep Deterministic Policy Gradients (DDPG)
• Artificial Intelligence – Covers AI Algorithms, Search Algorithms, Optimization, Planning, Pattern Recognition
• Machine Learning Engineer – Covers Machine Learning, Supervised Learning, Unsupervised Learning, Deep Learning
• Deep Learning – Covers Deep Learning, Neural Networks, Jupyter Notebooks, CNNs, GANs
• AI for Business Leaders – Covers Artificial Intelligence, Machine Learning, Business Strategy, Data Labeling, Data Modeling

The Nanodegree programs in Udacity’s School of AI are organized around following four main roles or career paths:

1. Machine Learning Engineer – Udacity recommends completing following Nanodegree programs in the specified order to start a career in Machine Learning – Intro to Machine Learning with TensorFlow, Intro to Machine Learning with PyTorch, AI Programming with Python, Machine Learning Engineer.
2. Deep Learning Engineer – For working as deep learning engineer, following Nanodegree programs are suggested – AI Programming with Python, Machine Learning Engineer, Deep Learning.
3. Artificial Intelligence Specialist – The recommended programs in this career path are – Computer Vision, Natural Language Processing, Deep Reinforcement Learning and Artificial Intelligence
4. Quantitative Analyst – This career path involves building programming and linear algebra skills, then learning to analyze real data and building financial models for trading. The recommended programs are – AI Programming with Python and Artificial Intelligence for Trading.

Key Highlights

• Curriculum designed and delivered by industry experts
• Get practical experience by applying your skills to code exercises and projects
• Get 1-on-1 technical mentor support
• Personal career coach also available for career path guidance
• Complete flexibility with timelines and schedule

Duration : Self-Paced
Rating : 4.6
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7. AI for Everyone by Andrew Ng (Coursera)

This Artificial Intelligence Course from Andrew Ng is largely non-technical and is intended for those who do not need to learn in-depth technicalities of AI but who wish to learn how to make better use of AI in their organizations or roll out AI initiatives or work with an AI team. It is also an excellent course for engineers, programmers and people with technical backgrounds to learn the business aspects of AI. It is very educative and detailed for starters who do not know anything about artificial intelligence.

This AI class starts with a comprehensive overview of what artificial intelligence is and finally goes on to discuss the entire workflow of AI projects and how to develop an AI strategy for your business. It covers the following topics:

• Meaning behind common AI terminology, including machine learning, deep learning, neural networks and data science
• A realistic view of AI and what it can and cannot do with examples
• How to spot opportunities to apply AI to challenges and problems in your organization
• Workflow of machine learning and data science projects
• How to build AI in your company
• Ethical and societal concerns and discussions surrounding AI

This is a 6 hour course that Andrew has developed with business applications in mind, which makes it very unique and one-of-its kind. Plus the fact that it is taught by Andrew himself, a pioneer and huge influencer in the field of artificial intelligence makes the course very popular. It is not restricted to engineers and scientists alone, anybody who sees value in AI and has interest in the subject should take this course.

Key Highlights

• Highest rated Coursera Artificial Intelligence online course
• Understand the meanings of various concepts in artificial intelligence and machine learning
• Learn how to work better with an AI team in your organization
• Learn how to chose an AI project
• Get a glimpse into the technical tools used by AI teams
• Case studies related to building an AI product and strategy
• No prerequisites, can be taken by anyone at any level of experience

Duration : 4 weeks, 2 hours per week
Rating : 4.8
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8. Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning (Coursera)

TensorFlow is a popular open-source framework for machine learning and probably the best tool you can use to implement machine learning and deep learning algorithms and principles. This TensorFlow course offered on Coursera is a part of TensorFlow in Practice Specialization by deeplearning.ai.

This course is suitable for software developers who have some experience in Python coding and some knowledge of machine learning and deep learning and who want to build scalable AI-powered algorithms in TensorFlow. It teaches how to use TensorFlow to implement the principles of machine learning and deep learning so learners can start building and applying scalable models to real-world problems.

The course comprises of 4 weekly modules that take learners from basic to mastery of TensorFlow. They cover the following topics:

• Introduction to what Machine Learning and Deep Learning are
• Introduction to Computer Vision
• Coding a Computer Vision Neural Network
• Introduction to Convolutional Neural Networks and Pooling
• Implementing convolutional layers and pooling layers
• Understanding ImageGenerator
• How to handle complex real-world images

There are abundant coding examples and programming assignments throughout the course. By the end of the course learners are able to gain practical skills to come up with scalable solutions to real-life AI challenges.

The course is taught by Lawrence Moroney, an AI advocate at Google. He has authored over 30 programming books and several science fiction novels.

Key Highlights

• Learn to apply TensorFlow skills to a wide range of problems and projects
• Learn the best practices for using TensorFlow
• Build a basic neural network in TensorFlow
• Understand how to use convolutions to improve your neural network
• Train a neural network for a computer vision application

Duration : 4 weeks, 6-9 hours per week
Rating : 4.7
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9. Artificial Intelligence A-Z™: Learn How To Build An AI (Udemy)

The path of learning Artificial Intelligence is often overwhelming with complex maths and technical topics. This Udemy AI course by Kirill Eremenko and Hadelin de Ponteves attempts to break that trend by offering an intuitive and exciting approach that guides learners into exploring the world of AI. It teaches how to combine the power of Data Science, Machine Learning and Deep Learning to create powerful AI for Real-World applications.

The course is created on the theory that Games are the simplest test environment for AI, and when an algorithm can beat a game, it is proof that same principles can be applied to real world challenges. Therefore, the course uses a simulated AI environment, OpenAI Gym (a project backed by entrepreneurs like Elon Musk and Peter Thiel) in order to learn how to create artificial intelligence which surpasses humans in games like Doom and Breakout.

The course is divided into 3 modules, each one taking a unique AI creation process of different difficulty, structure and purpose:

• Module 1 – Create AI to conquer the game of Breakout
• Module 2 – Create a more complex AI to pass a level in Doom
• Module 3 – Build an AI for self-driving cars

This is a completely hands-on course that takes learners through the practical steps necessary to be able to code self-improving AI for a range of purposes. Every tutorial starts with a blank page and the instructors write the code from scratch. This way the learners are able to follow along better and understand exactly how the code comes together and what each line means. No previous coding experience using Python is required.

The course also covers Q-learning, which is a form of machine learning based on reinforcement learning, and is being used in a lot of cutting-edge applications.

Key Highlights

• Beginner friendly course to learn the fundamentals of AI, both the theory as well as its practical applications
• Get skilled to build AI adaptable to any environment in real life
• Master the State of the Art AI models
• Make a virtual Self Driving Car
• Make an AI to beat games
• Explore Q-Learning, Deep Q-Learning and Deep Convolutional Q-Learning
• Understand how to merge AI with OpenAI Gym to learn as effectively as possible
• In-course support from an expert team of professional Data Scientists
• Get downloadable Python code templates for every AI you build in the course
• Content focused on building up learner’s intuition in coding AI that leads to better learning outcomes

Duration : 16.5 hours on-demand video
Rating : 4.3
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10. Artificial Intelligence Course: Reinforcement Learning in Python (Udemy)

Reinforcement Learning is an entirely different paradigm in AI and Machine Learning. It has given us amazing insights both in behavioral psychology and neuroscience, and is the closest thing we have so far to a true general artificial intelligence. This course is one of the best AI courses out there on Reinforcement Learning. It gives learners a primer on AI-powered reinforcement learning, with a particular focus on stock trading and online advertising. It gives insights into AI techniques that one would never see in traditional supervised machine learning, unsupervised machine learning, or even deep learning.

This course is best fit for those who already have basic knowledge of theoretical and technical aspects of AI and want to understand Reinforcement learning thoroughly. Since it teaches advanced level concepts, the students are expected to know Calculus, Probability, Object-oriented programming, Python coding, Numpy coding, Linear regression, Gradient descent etc.

In this AI class students understand reinforcement learning on a technical level. Following topics are covered in the course content:

• The multi-armed bandit problem and the explore-exploit dilemma
• Ways to calculate means and moving averages and their relationship to stochastic gradient descent
• Markov Decision Processes (MDPs)
• Dynamic Programming
• Monte Carlo
• Temporal Difference (TD) Learning (Q-Learning and SARSA)
• Approximation Methods (i.e. how to plug in a deep neural network or other differentiable model into your RL algorithm)

There is also a Project where learners get to apply Q-learning to build a stock trading bot, and another about building AI for the Tic-Tac-Toe game.

Key Highlights

• Best online AI course for those looking to gain knowledge of Python-based AI reinforcement learning
• Understand the relationship between reinforcement learning and psychology
• Apply gradient-based supervised machine learning methods to reinforcement learning
• Implement 17 different reinforcement learning algorithms
• Range of exercises and assignments for hands-on practice

Duration : 12.5 hours on-demand video
Rating : 4.6
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More AI Courses

11. Master the Fundamentals of AI and Machine Learning (LinkedIn Learning – Lynda)

LinkedIn Learning is offering a learning path comprising of series of short courses to attain mastery in the foundations of artificial intelligence and machine learning. These courses are designed to teach the concepts and future directions of technologies in artificial intelligence and machine learning. They equip learners with the knowledge and tools to make more informed decisions and contributions in their work environment.

There are eight courses included in this learning path which add up to 11 hours of video content. These courses can be availed for free for the first month of signing up. After completing all the courses, learners earn a badge of completion from LinkedIn Learning. The courses are as follows:

• AI Accountability Essential Training
  By: Barton Poulson
  Duration: 2h 21m 49s
  This nontechnical course digs into the hazards of AI, the ethical issues posed by AI, including competing concepts of fairness and moral reasoning, social concerns and safety challenges for AI such as potential life-and-death scenarios in autonomous driving and offers potential solutions to key concerns. It discusses the importance for AI-related data science work to be transparent, explainable, accountable, and ethical in its design and execution.
• Artificial Intelligence Foundations: Machine Learning
  By: Doug Rose
  Duration: 1h 17m 56s
  This course introduces definition and types of machine learning: supervised, unsupervised, and reinforcement. It teaches how to use machine learning algorithms such as decision trees, clustering, and regression analysis to make better decisions and find patterns in your data.
• Artificial Intelligence Foundations: Thinking Machines
  By: Doug Rose
  Duration: 1h 27m 27s
  This course covers the key concepts behind artificial intelligence (AI), including strong and weak AI, different approaches to AI such as machine learning and deep learning, and practical uses for new AI-enhanced technologies.
• Artificial Intelligence Foundations: Neural Networks
  By: Doug Rose
  Duration: 1h 16m 51s
  This course covers the key concepts behind artificial neural networks. It teaches how to configure a neural network and use that network to find patterns in massive data sets.
• Cognitive Technologies: The Real Opportunities for Business
  By: Deloitte Insights
  Duration: 1h 52m 42s
  This course explains the benefits and business value of cognitive technologies such as artificial intelligence and robotics and their impact on business.
• AI The LinkedIn Way: A Conversation with Deepak Agarwal
  By: Deepak Agarwal
  Duration: 31m 3s
  In this short course, Deepak Agarwal, the VP of artificial intelligence (AI) at LinkedIn, answers questions about AI’s role at LinkedIn, careers in the field, and the future of the technology.
• Artificial Intelligence for Project Managers
  By: Oliver Yarbrough
  Duration: 41m 41s
  This course covers the impact that artificial intelligence (AI) will have on project management. It discusses how to harness its power to streamline your workflow, how to prepare for the changes that lie ahead and stay ahead of the curve.
• Learning XAI: Explainable Artificial Intelligence
  By: Aki Ohashi
  Duration: 1h 14m 14s
  This course covers how explainable artificial intelligence (XAI) works and the value it provides to data science-related businesses and initiatives from legal and commercial perspectives.

Key Highlights

• Gain a clear and detailed understanding of how AI and machine learning work
• Learn how leading companies are using AI and machine learning to change the way they do business
• Learn how the next generation of thinking about AI is addressing issues of accountability, security, and explainability
• Well designed content created by experts and industry leaders
• Abundant exercises and assignments included
• Ideal for both students and professionals
• Free access to all courses for one month

Duration : 11 hours of video content
Rating : 4.5
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12. Learn with Google AI – Free AI Courses (Google)

This is a free Google–led initiative to impart knowledge of AI skills and broaden the understanding of AI among general public. It is a collection of courses, guides, tutorials crafted by Google’s engineers and experts with the aim of providing foundational skills and knowledge in the field of artificial intelligence and topics related to it.

Irrespective of their current skill and experience level, learners can find resources, information and exercises to help develop skills and advance their projects. Beginner learners with no prior knowledge of AI and machine learning can jump in right at the start, while experienced learners can pick or choose resources and modules according to their interest and requirement.

There is a wide range of courses that help to build a board understanding of AI and many factors related to it – both technical and non-technical – when considering how AI could work for you. So apart from courses covering the fundamentals, and those that offer instructions on applying AI and ML to real-life social, environmental and humanitarian problems, one can also find good information on how to ensure that the AI implementations are transparent, ethical and people-centric.

Here’re a few courses, videos, tutorials and guides one can find on this platform:

• Using AI for social good
• Clustering
• Recommendation Systems
• Testing and Debugging in Machine Learning
• Introduction to Machine Learning Problem Framing
• Data Preparation and Feature Engineering in ML
• Machine Learning Crash Course with TensorFlow APIs
• Neural Network
• The 7 steps of machine learning
• End-to-end Machine Learning with TensorFlow on GCP

All the Google AI courses and tutorials contain sample codes, quizzes, and helpful examples which make the concepts easy to grasp for beginners as well.

Key Highlights

• Free artificial intelligence courses online that give learners a running-start
• Excellent resources available for those interested in upleveling their skill set
• Understand the types of problems your organization can solve with ML and AI
• Tips and Techniques for implementing the skills learnt to real world problems and data sets

Duration : Self-Paced
Rating : 4.5
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13. Coursera Artificial Intelligence Courses

Coursera offers a variety of courses, specializations and professional certificate programs in the field of Artificial Intelligence. These have been created in partnership with the best data science schools and universities around the world and AI industry leaders like IBM and Google.

These AI courses and Certification programs cover skills like machine learning, deep learning, python programming, artificial neural networks, tensorflow, reinforcement learning etc. Several Beginner level courses are available for learners with no prior experience in this field while more advanced courses are also available for seasoned AI professionals.

Some of the most popular choices of AI courses on Coursera include:

• AI For Everyone by Andrew Ng
• Machine Learning AI Certification by Stanford University
• IBM AI Engineering Professional Certificate
• Deep Learning Specialization
• AI Foundations for Everyone Specialization by IBM
• IBM Applied AI Professional Certificate
• IBM Data Science Professional Certificate
• Python for Everybody by University of Michigan
• Machine Learning Specialization by University of Washington
• Mathematics for Machine Learning Specialization by Imperial College London
• Reinforcement Learning Specialization by University of Alberta
• Developing AI Applications on Azure
• AI for Medicine
• Applied AI with DeepLearning by IBM

For learners who wish to take several courses, Coursera Plus yearly subscription plan ($399/year) can be of great value. By subscribing to Coursera Plus, learners get unlimited access to more than 3000 courses, professional certificates, specializations and guided projects. They also earn a verified certificate for every course or program they complete at no additional cost. This is an excellent option for frequent online learners to continue their learning in a seamless, affordable way.

Key Highlights

• Prepare for a career in AI by learning latest skills from top instructors
• Well rounded and industry relevant content created by experts from top universities and companies
• Option to audit the courses for free
• Earn industry-recognized shareable certificates
• Quizzes and hands-on projects to help learners apply the skills they acquire
• Opportunity to be a part of the global community of learners

Duration : Self-Paced
Rating : 4.7
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14. Free Artificial Intelligence Courses (edX)

Online learning Platform edX has partnered with top universities and institutions around the globe to offer a range of courses in the field of Artificial Intelligence. These include Professional Certificates and Micromasters programs from Harvard, Columbia, IBM and Microsoft among others. These courses are available for free to audit the content. If one pays a small fee, one can get an industry recognised certificate of completion to share with employers.

The courses available encompass the entire spectrum of Artificial Intelligence including natural language processing, python coding, math, psychology, neuroscience, reinforcement learning, predictive analytics, deep neural networks, robotics, image processing and many other disciplines. Some of the top edX AI courses and certificate programs include:

• MicroMasters® Program in Artificial Intelligence by Columbia University
• Deep Learning Professional Certificate by IBM
• Data Science Professional Certificate by Harvard University
• Machine Learning for Data Science and Analytics by Columbia University
• Professional Certificate in Computer Science for Artificial Intelligence
• Professional Certificate in Applied AI by IBM
• Professional Certificate in Foundations of AI by IBM
• Professional Certificate in Drones and Autonomous Systems by UMGC and USMx
• Professional Certificate in AI in Practice

Key Highlights

• Become an industry expert in AI and machine learning techniques
• Learn about examples of AI in use today such as self-driving cars, facial recognition systems, military drones and natural language processors
• Get hands-on experience with the AI programming of intelligent agents such as search algorithms, games and logic problem
• Learn from instructors of top institutions with assistance at every step of learning
• Self-paced courses with complete flexibility of timelines
• All courses accessible for free with option of paid certificates

Duration : Self-Paced
Rating : 4.5
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15. Udemy AI Courses

Udemy is another great platform for best online courses on artificial intelligence. It offers a range of top-rated AI courses that take learners through combining deep learning, machine learning, and data science practices to build their own AI solutions and solve unique challenges in any industry. These courses include beginner friendly courses to help learners get started with AI by imparting overall fundamental knowledge and skills as well as intermediate level courses for training in specific aspects and complex domains of AI.

One can find courses on various topics like machine learning, python, deep learning, reinforcement learning, neural networks, computer vision, tensorflow, unity, chatbot, financial trading etc. Some of the highest rated AI courses on Udemy include:

• Artificial Intelligence A-Z™: Learn How To Build An AI
• Advanced AI Tutorial: Deep Reinforcement Learning in Python
• Artificial Intelligence Course: Reinforcement Learning in Python
• Machine Learning, Data Science and Deep Learning with Python
• The Beginner’s Guide to Artificial Intelligence in Unity
• Artificial Intelligence Masterclass
• Artificial Intelligence for Business
• Deep Learning and Computer Vision A-Z™: OpenCV, SSD & GANs

Key Highlights

• AI classes from top educators and expert professionals
• Each course includes multiple quizzes, practice tests and assignments to help cement the learning
• Full lifetime access to video content, quizzes and downloadable resources, including future updates
• Get a shareable Certificate of Completion on completing the course
• 30 days money-back guarantee available

Duration : Self-Paced
Rating : 4.5
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