Coursera

Getting Started with AI using IBM Watson (Coursera)

Offered by IBM,

In this course you will learn how to quickly and easily get started with Artificial Intelligence using IBM Watson. You will understand how Watson works, become familiar with its use cases and real life client examples, and be introduced to several of Watson AI services from IBM that enable anyone to easily apply AI and build smart apps. You will also work with several Watson services to demonstrate AI in action.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

This course does not require any programming or computer science expertise and is designed for anyone whether you have a technical background or not.
Completing this course will count towards your learning in any of the following programs:

Syllabus

WEEK 1
Watson AI Overview
This week, you will learn how Watson AI works. You will understand the many ways Watson AI is helping professionals and businesses reimagine their workflows, learn more from less data, and protect their insights.

WEEK 2
Watson AI Services
This week, you will learn about some of the Watson AI services offered on the IBM Cloud. You will understand how organizations can use Watson AI services and the types of situations in which each service applies.

WEEK 3
More Watson AI Services
This week, you will learn about some of the Watson AI services offered on the IBM Cloud. You will understand how organizations can use Watson AI services and the types of situations in which each service applies.

WEEK 4
Watson in Action
This week, you will learn about common use cases for AI, and look at some case studies involving Watson AI. You will also experience and demonstrate AI in action yourself using Watson.

Go to Class

MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Coursera

Fractal Analytics

Responsible AI in the Generative AI Era (Coursera)

CS: Software Engineering

This one-week microlearning course provides an introduction to the Principles of Responsible AI and how those principles align with the Generative AI or GenAI space. It also informs the learners about the various challenges that Generative AI brings. You will explore the fundamental principles of responsible AI, and understand the need for developing Generative AI tools responsibly.

Aug 3rd 2026

1 Week

Artificial Intelligence Critical Thinking Problem Solving

Coursera

Coursera Instructor Network

General AI Mastery Toolbox: Master AI and Drive Success (Coursera)

Management & Leadership Business

General Artificial Intelligence (AI) has proven its value in the business world with its multiple uses. The various applications of AI have proved to be of increasing value to businesses in their ability to meet customer demand with efficiency and creativity. To remain in sync with the direction of business entities, individuals need a tool kit to assist them as they master this technology.

Aug 3rd 2026

1 Week

Business Artificial Intelligence AI

Coursera

Board Infinity

Security for Artificial Intelligence Software and Services (Coursera)

Data Science

The "Security Basics for Artificial Intelligence Software and Services" course provides an in-depth exploration of security measures and best practices in the context of AI. Spanning two comprehensive modules, the course begins with an introduction to the fundamentals of AI security, including ethical considerations and common threats. It then progresses to practical strategies for implementing robust security in AI development, such as secure coding, vulnerability assessment, and adherence to compliance standards.

Aug 3rd 2026

2 Weeks

Artificial Intelligence Security Encryption

Coursera

Dartmouth College

Generative AI for the Resilient Pricer (Coursera)

Business

In this course we’ll address the concept of leveraging Gen-AI in various economic and operational circumstances to rapidly generate pricing insights. Disruption occurs at an ever-increasing pace, driving imperfect information, limited response time, and competing priorities. The commercial excellence discipline is one that requires a holistic approach to delivering results, and those who complete this course will come away with the understanding necessary to determine where to focus for maximum effect.

Aug 3rd 2026

4 Weeks

Artificial Intelligence Pricing AI

Coursera

Edge Impulse

Computer Vision with Embedded Machine Learning (Coursera)

Data Science

Computer vision (CV) is a fascinating field of study that attempts to automate the process of assigning meaning to digital images or videos. In other words, we are helping computers see and understand the world around us! A number of machine learning (ML) algorithms and techniques can be used to accomplish CV tasks, and as ML becomes faster and more efficient, we can deploy these techniques to embedded systems.

Aug 3rd 2026

3 Weeks

Machine Learning Computer Vision Object Detection

Coursera

Sungkyunkwan University - SKKU

Machine Learning Basics (Coursera)

CS: Software Engineering

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.

Aug 3rd 2026

4 Weeks

Machine Learning Linear Regression Logistic Regression

Coursera

Coursera Instructor Network

AI-Enhanced Content Creation:Elevate Copywriting with Humata (Coursera)

Data Science

AI-driven writing isn't just about words; it's about understanding emotions. Advanced algorithms can analyze sentiments and tailor messages to evoke specific feelings, creating a powerful connection with your audience that goes beyond the text on the screen. This one-hour course is for those interested in automating the process of creating effective advertisement campaigns, website content, email marketing, and more with generative AI. More specifically, you'll learn to use Humata AI to identify a target audience and to create a compelling Facebook advertisement and blog post.

Aug 3rd 2026

1 Week

Artificial Intelligence Copywriting Advertisements

Coursera

University of Leeds

How to Get Into AI (Coursera)

CS: Design & Product

AI forms the basis for all computer learning and is the future of all complex decision-making. As such it is becoming increasingly prevalent in daily life. As a result, the outlook is bright for artificial intelligence jobs. In this course, you will learn how to navigate the dynamic field of artificial intelligence (AI), exploring its applications and the evolving landscape of AI-related careers.

Aug 3rd 2026

2 Weeks

Artificial Intelligence Workplace Career Development

Coursera

Google Cloud

Introduction to Generative AI Studio (Coursera)

CS: Software Engineering

This course introduces Generative AI Studio, a product on Vertex AI, that helps you prototype and customize generative AI models so you can use their capabilities in your applications. In this course, you learn what Generative AI Studio is, its features and options, and how to use it by walking through demos of the product. In the end, you will have a quiz to test your knowledge.

Aug 3rd 2026

1 Week

Artificial Intelligence AI Coursera Plus

Coursera

Stanford University

Probabilistic Graphical Models 3: Learning (Coursera)

Statistics & Data Analysis Data Science

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.

Aug 3rd 2026

5-12 Weeks

Algorithms Machine Learning PGM

Coursera

University of Colorado Boulder

Ethical Issues in Data Science (Coursera)

Statistics & Data Analysis Data Science

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.

Aug 3rd 2026

5-12 Weeks

Philosophy Artificial Intelligence Security

Coursera

Columbia University

Decision Making and Reinforcement Learning (Coursera)

Computer Science

This course is an introduction to sequential decision making and reinforcement learning. We start with a discussion of utility theory to learn how preferences can be represented and modeled for decision making. We first model simple decision problems as multi-armed bandit problems in and discuss several approaches to evaluate feedback. We will then model decision problems as finite Markov decision processes (MDPs), and discuss their solutions via dynamic programming algorithms. We touch on the notion of partial observability in real problems, modeled by POMDPs and then solved by online planning methods.

Aug 3rd 2026

5-12 Weeks

Algorithms Machine Learning Monte Carlo Method