Elements of Artificial Intelligence (Reaktor)

Elements of Artificial Intelligence (Reaktor)

The elements of AI is a free online course for everyone interested in learning what AI is — with no complicated math or programming required.

The goal of this course is to demystify AI
The elements of AI is a free online course for everyone interested in learning what AI is, what is possible (and not possible) with AI, and how it affects our lives – with no complicated math or programming required. By completing the course you can earn a LinkedIn certificate. People in Finland can also earn 2 ECTS credits through the Open University.

After taking the course, you will be able to:

  • Understand some of the major implications of AI
  • Think critically about AI news and claims
  • Define and discuss what AI is
  • Explain the methods that make AI possible
Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Frontiers in Dentistry (Coursera) Coursera
University of Pennsylvania

Frontiers in Dentistry (Coursera)

In this course, Frontiers in Dentistry, you will be able to explore some of the latest advances in the field of dental medicine. The innovations in therapeutic techniques as well as our understanding of the biomedical sciences have been made possible by our research enterprise which integrates the latest emerging technology along with interdisciplinary collaborations.

Sep 28th 2026
5-12 Weeks
Machine Learning Basics (Coursera) Coursera
Sungkyunkwan University - SKKU

Machine Learning Basics (Coursera)

In this course, you will: understand the basic concepts of machine learning; understand a typical memory-based method, the K nearest neighbor method; understand linear regression; understand model analysis. Please make sure that you’re comfortable programming in Python and have a basic knowledge of mathematics including matrix multiplications, and conditional probability.

Sep 28th 2026
4 Weeks
ChatGPT Prompt Engineering for Developers (DeepLearning.AI) Other Providers
DeepLearning.AI,OpenAI

ChatGPT Prompt Engineering for Developers (DeepLearning.AI)

Go beyond the chat box. Use API access to leverage LLMs into your own applications, and learn to build a custom chatbot. In ChatGPT Prompt Engineering for Developers, you will learn how to use a large language model (LLM) to quickly build new and powerful applications. Using the OpenAI API, you’ll be able to quickly build capabilities that learn to innovate and create value in ways that were cost-prohibitive, highly technical, or simply impossible before now.

Self Paced
Self-Paced
Amazon Bedrock - Getting Started (Coursera) Coursera
AWS

Amazon Bedrock - Getting Started (Coursera)

Amazon Bedrock is a fully managed service that makes foundation models (FMs) from Amazon and leading artificial intelligence (AI) startups available through an API. In this course, you will learn the benefits of Amazon Bedrock. You will learn how to start using the service through a demonstration in the Amazon Bedrock console. You will also learn about the AI concepts of Amazon Bedrock and how you can use the service to accelerate development of generative AI applications.

Sep 28th 2026
1 Week
Introduction to Vertex AI (Coursera) Coursera
Fractal Analytics

Introduction to Vertex AI (Coursera)

Welcome to "Introduction to Vertex AI"! In this concise yet impactful microlearning course spanning around 4 hours, we're diving into the world of Vertex AI to equip you with fundamental insights and practical skills. We'll unravel the essentials of Vertex AI, guiding you through the interface to empower you to navigate this powerful platform seamlessly. Get ready to grasp strategic insights that will enable you to effectively harness the capabilities of Vertex AI in your projects.

Sep 28th 2026
2 Weeks
Probabilistic Graphical Models 3: Learning (Coursera) Coursera
Stanford University

Probabilistic Graphical Models 3: Learning (Coursera)

Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: joint (multivariate) distributions over large numbers of random variables that interact with each other. These representations sit at the intersection of statistics and computer science, relying on concepts from probability theory, graph algorithms, machine learning, and more. They are the basis for the state-of-the-art methods in a wide variety of applications, such as medical diagnosis, image understanding, speech recognition, natural language processing, and many, many more. They are also a foundational tool in formulating many machine learning problems.

Sep 28th 2026
5-12 Weeks
Ethical Issues in Data Science (Coursera) Coursera
University of Colorado Boulder

Ethical Issues in Data Science (Coursera)

Computing applications involving large amounts of data – the domain of data science – impact the lives of most people in the U.S. and the world. These impacts include recommendations made to us by internet-based systems, information that is available about us online, techniques that are used for security and surveillance, data that is used in health care, and many more. In many cases, they are affected by techniques in artificial intelligence and machine learning.

Sep 28th 2026
5-12 Weeks
Machine Learning Algorithms (Coursera) Coursera
Sungkyunkwan University - SKKU

Machine Learning Algorithms (Coursera)

In this course you will: understand the naïve Bayesian algorithm; understand the Support Vector Machine algorithm; understand the Decision Tree algorithm; understand the Clustering. Please make sure that you’re comfortable programming in Python and have a basic knowledge of mathematics including matrix multiplications, and conditional probability.

Sep 28th 2026
4 Weeks
How Diffusion Models Work (DeepLearning.AI) Other Providers
DeepLearning.AI

How Diffusion Models Work (DeepLearning.AI)

Learn and build diffusion models from the ground up. Start with an image of pure noise, and arrive at a final image, learning and building intuition at each step along the way. In How Diffusion Models Work, you will gain a deep familiarity with the diffusion process and the models which carry it out. More than simply pulling in a pre-built model or using an API, this course will teach you to build a diffusion model from scratch.

Self Paced
Self-Paced
Math for AI beginner part 1 Linear Algebra (Coursera) Coursera
Korea Advanced Institute of Science and Technology - KAIST

Math for AI beginner part 1 Linear Algebra (Coursera)

'Learn concept of AI such as machine learning, deep-learning, support vector machine which is related to linear algebra. Learn how to use linear algebra for AI algorithm. After completing this course, you are able to understand AI algorithm and basics of linear algebra for AI applications.

Sep 28th 2026
5-12 Weeks