artificial intelligence course

10 Best + Free Online Artificial Intelligence Courses

Artificial Intelligence is the world’s future. Every app and website nowadays uses AI for the majority of its functionalities. Face recognition locks, registering and verifying your security for transactions, and, more recently, putting your face on various characters in gaming and non-gaming apps are all examples of how they’re employed. Artificial Intelligence makes all of this more feasible. Artificial Intelligence is a useful ability to have, especially since it was all the rage a few years ago, similar to the dot-com boom. Employers are looking for workers with a wide range of skills, particularly those who can assist their businesses move into the Next Generation.

List of 10 Best + Free Online Artificial Intelligence Courses

1. Artificial Intelligence (Northwestern | Kellogg School of Management)

This course is designed for anyone who wants to learn about artificial intelligence methods and approaches for solving business problems. Following the discussion of the fundamental themes, you will learn about how AI is affecting many industries, as well as the numerous tools that are used in operations to produce efficient solutions. By the end of the training, you’ll have a number of tactics under your belt that you may utilize to boost your company’s success.

What you will learn –

  • Understand the business applications and outcomes that can be achieved with AI.
  • Represent the voice of the business as well as the customer to data scientists and engineers.
  • Craft your AI journey, from strategy and capabilities to execution and organization.
  • Navigate the black box and ethical considerations of Artificial Intelligence to drive responsible AI initiatives.
  • Join a community of like-minded professionals who are successfully deploying AI in their organizations.

Pre-requirements –

No prerequisites are needed.

Who can take this course –

This course is open to anyone who wants to learn more and make better use of their time.

Duration – 8 weeks approx

Instructor – Mohanbir Sawney

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

This course is designed for anyone who wants to learn about artificial intelligence methods and approaches for solving business problems. Following the discussion of the fundamental themes, you will learn about how AI is affecting many industries, as well as the numerous tools that are used in operations to produce efficient solutions. By the end of the training, you’ll have a number of tactics under your belt that you may utilize to boost your company’s success.

What you will learn –

  • Synthesize components of machine learning to create functional tools for prediction of unseen data.
  • Implement and analyze learning algorithms for classification, regression and clustering.
  • Use concepts from probability, statistics, linear algebra, calculus and optimization to describe and refine the inner workings of machine learning algorithms.

Pre-requirements –

No prerequisites are needed.

Who can take this course –

This course is open to anyone who wants to learn more and make better use of their time.

Duration – 10 weeks approx

Instructor – Patrick Virtue

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

The science of getting computers to act without being explicitly programmed is known as machine learning. Self-driving cars, realistic speech recognition, successful web search, and a much-enhanced understanding of the human genome have all been made possible by machine learning in the last decade. Machine learning is now so common that you probably use it thousands of times a day without even realizing it. Many academics believe it is the most effective technique to get closer to human-level AI. This program will teach you about the most effective machine learning techniques and give you practice implementing and using them on your own. More significantly, you’ll master not only the theoretical foundations of learning but also the practical know-how required to apply these strategies to new challenges quickly and effectively. Finally, you’ll learn about some of Silicon Valley’s best practices in machine learning and AI innovation.

What you will learn –

  • 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.

Pre-requirements –

No prerequisites are needed.

Who can take this course –

This course is open to anyone who wants to learn more and make better use of their time.

Duration – 60  hours approx

Instructor – Andrew Ng

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

According to TechJury, the worldwide AI market is estimated to reach about $60 billion by 2025. Artificial Intelligence is revolutionizing people’s personal and professional life all around the world. AI is the study of computer systems that can do activities that would normally require human intellect, such as visual perception, speech recognition, and even decision-making. These technologies can be used to help organizations enhance their outcomes and productivity in a variety of ways. To compete in this new tech-driven economy, you must understand how game-changing technology like AI may help your company’s many business activities.

What you will learn –

  • Learn AI’s current capabilities and applications—and its future potential.
  • Learn how to organize and manage successful AI application projects.
  • Grasp the technical aspects of AI well enough to communicate effectively with technical teams and colleagues.
  • Learn how to avoid pitfalls associated with these new technologies.
  • Build your leadership credibility by obtaining a Certificate of Completion from UC Berkeley Executive.

Pre-requirements –

No prerequisites are needed.

Who can take this course –

This course is open to anyone who wants to learn more and make better use of their time.

Duration – 8 weeks approx

Instructor – Sameer B. Srivastava

5. IBM AI Engineering Professional Certificate (Coursera)

Artificial intelligence (AI) is reshaping whole industries, transforming how businesses use data to make choices across industries. To stay competitive, businesses require qualified AI engineers who can supply data-driven actionable intelligence for their businesses using cutting-edge methods such as machine learning algorithms and deep learning neural networks. This six-course Professional Certificate is designed to provide you with the skills you’ll need to succeed as an AI or machine learning engineer.
Using programming languages like Python, you’ll learn the fundamentals of machine learning and deep learning, including supervised and unsupervised learning. Object recognition, computer vision, image and video processing, text analytics, natural language processing (NLP), recommender systems, and other types of classifiers will all be addressed using popular machine learning and deep learning libraries such as SciPy, ScikitLearn, Keras, PyTorch, and Tensorflow.

What you will learn –

  • Describe machine learning, deep learning, neural networks, and ML algorithms like classification, regression, clustering, and dimensional reduction. 
  • Implement supervised and unsupervised machine learning models using SciPy and ScikitLearn. 
  • Deploy machine learning algorithms and pipelines on Apache Spark. 
  • Build deep learning models and neural networks using Keras, PyTorch, and TensorFlow. 

Pre-requirements –

No prerequisites are needed.

Who can take this course –

This course is open to anyone who wants to learn more and make better use of their time.

Duration – 32 weeks approx

Instructor – Saeed Aghabozorgi, Joseph Santarcangelo, Alex Aklson, Jeremy Nilmeier, Samaya Madhavan & Romeo Kienzler. 

6. Post Graduate Program in AI and Machine Learning (Purdue University)

Working professionals with programming experience can benefit from this AI ML certification course. Statistics, Machine Learning, Deep Learning, Natural Language Processing, and Reinforcement Learning are among the topics covered. This program is taught using our interactive learning style, which includes live sessions with global practitioners, laboratories, and industry projects.

What you will learn –

  • A practical postgraduate programme that will guide you through a learning journey to help you advance your AI, Deep Learning, and Machine Learning profession.
  • Learn about machine learning, deep learning, computer vision, natural language processing, reinforcement learning, and speech recognition, among other AI-based technologies.
  •  Learn the fundamentals of deep learning and how to use tools like TensorFlow and Keras to build artificial neural networks and traverse levels of data abstraction.
  •  Understand the terms natural language processing (NLP), feature engineering, automatic speech recognition (ASR), speech to text conversion (STC), text to speech conversion (TTC), and voice assistant devices.

Pre-requirements –

No prerequisites are needed.

Who can take this course –

This course is open to anyone who wants to learn more and make better use of their time.

Duration – 12 months approx

Instructor – Venkata N Inukollu

7. Deep Learning for Business by Yonsei University(Coursera)

AI (Artificial Intelligence) is embedded in your smartphone, smartwatch, and automotive (if it is a recent model) and serves you every day. More advanced “self-learning” capable DL (Deep Learning) and ML (Machine Learning) technologies will be used in practically every part of your organization and industry in the not-too-distant future. So now is the time to learn about DL and ML and how to apply them to your company’s benefit. The first half of the course concentrates on future business strategies based on DL and ML technology, including specifics on new state-of-the-art products/services and open source DL software, which are the future enablers. The second section concentrates on the NN (Neural Network), CNN (Convolutional NN), and RNN (Recurrent NN) systems, which are the key technologies of DL and ML systems. The third section focuses on four TensorFlow Playground projects, where you may get expertise in creating DL NNs by using the TensorFlow Playground, which is a simple, entertaining, and powerful tool. This course was created to assist you in developing business strategies and conducting technical planning for new DL and ML services and products.

What you will learn –

  • Deep Learning fundamentals, covering several Neural Networks for supervised and unsupervised learning.
  • Convolutional Networks, Recurrent Networks, and Autoencoders are among the Deep Architectures that can be built, trained, and deployed.
  • Object recognition and Computer Vision, image and video processing, text analytics, Natural Language Processing, recommender systems, and other types of classifiers are examples of real-world applications where Deep Learning is used.
  • Using accelerated hardware and GPUs, master Deep Learning at scale.
  • Popular Deep Learning libraries like Keras, PyTorch, and Tensorflow are used to solve real-world challenges.

Pre-requirements –

No prerequisites are needed.

Who can take this course –

This course is open to anyone who wants to learn more and make better use of their time.

Duration – 8 hours approx

Instructor – Jong-Moon Chung  

8. The Business of AI (London Business School)

Artificial intelligence (AI) isn’t just another technological advancement. It is the most crucial digital technology for global company transformation, and it may have the greatest total business impact. Artificial intelligence (AI) has the potential to revolutionize cost functions and create completely new business models, but it requires a thorough grasp of both your organization and technology. Our curriculum, The Business of AI, will help you develop the skills you need to make informed AI decisions and add real value to your company.

What you will learn –

  • Learn to communicate effectively with business stakeholders with a solid understanding of the advantages and limitations of AI and ML in business settings.
  • Increase your professional value and become an in-demand leader with the rare ability to connect this powerful technology to business value and results.
  • Explore real-life examples of how the global nature of the economy has allowed AI to connect businesses around the world and deliver value across diverse applications.
  • Determine how you can leverage AI and ML to create value for your business.
  • Develop your AI expertise through the process of creating, refining and presenting your AI implementation plan.

Pre-requirements –

No prerequisites are needed.

Who can take this course –

This course is open to anyone who wants to learn more and make better use of their time.

Duration – 10 weeks approx

Instructor – Michael Davies

9. Artificial Intelligence Course: Reinforcement Learning in Python (Udemy)

This program’s instructor is a data scientist, a big data engineer, and a full-stack software engineer! He is ideally prepared to teach you AI using Python because he has a master’s degree in computer engineering and a specialization in machine learning. You’ll learn how to use gradient-based supervised methods in reinforcement learning, as well as the connections between reinforcement learning and psychology. You’ll also gain a technical understanding of reinforcement. To attend this course, you must have prior expertise with a few supervised machine learning methods as well as strong object-oriented programming capabilities.

What you will learn –

  • Apply gradient-based supervised machine learning methods to reinforcement learning.
  • Understand reinforcement learning on a technical level.
  • Understand the relationship between reinforcement learning and psychology.
  • Implement 17 different reinforcement learning algorithms.

Pre-requirements –

No prerequisites are needed.

Who can take this course –

This course is open to anyone who wants to learn more and make better use of their time.

Duration – 14.5 hours approx

Instructor – Lazy Programmer

10. Artificial Intelligence Nanodegrees (Udacity)

Artificial Intelligence has quickly become one of the most transformative technologies of our time, and there will be several chances for humans in the near future. If you want to pursue a career in AI, Udacity offers a school of AI curriculum that will introduce you to various topics in AI and Machine Learning, including introduction to AI products, annotation of datasets, training ML models, introduction to Machine Learning, Deep learning, and much more. This course includes a variety of Nano degree programs that cover a variety of topics; you can choose the program that best suits your needs. Aside from that, Udacity offers various free courses, such as Intro to AI, Intro to ML, Secure and Private AI, A/B Testing, and so on.

What you will learn –

  • Intro to Machine Learning with TensorFlow.
  • Intro to Machine Learning with PyTorch.
  • AI Programming with Python.
  • Machine Learning Engineer.
  • Deep Learning.
  • Computer Vision.
  • Natural Language Processing.
  • Deep Reinforcement Learning.
  • Artificial Intelligence.
  • Artificial Intelligence for Trading.

Pre-requirements –

No prerequisites are needed.

Duration – Self Paced

Who can take this course –

This course is open to anyone who wants to learn more and make better use of their time.

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