Learn how explainable AI makes AI models more transparent, and build fair AI systems with this free online course Learn how to make AI models more transparent and understandable with this comprehensive course on Explainable AI (XAI). In this course, you will learn the basics of XAI, as well as the different techniques that can be used to explain the predictions of AI models. You will also learn about the challenges of XAI and the ethical considerations that need to be taken into account when developing explainable AI systems.
| Course Type | Online Learning |
| Course Qualification | CPD Certificate |
| Course Duration | 4-5 hours |
| Course Fee | Free |
| Entry Requirements | Like all courses on the Alison Free Learning platform this is a free, CPD-accredited course. A Graduate can choose to buy a certificate or diploma upon successful completion of a course, but this is not required or necessary. At Alison we believe that free education, more than anything, has the power to break through boundaries and transform lives. Alison is the world’s largest free online empowerment platform for education and skills training, offering over 5000 CPD accredited courses and a range of impactful career development tools. It is a for-profit social enterprise dedicated to making it possible for anyone, to study anything, anywhere, at any time, for free online, at any subject level. Through our mission, we are a catalyst for positive social change, creating opportunity, prosperity, and equality for everyone. |
| Career Path | What You Will Learn In This Free Course • Apply XAI techniques to explain the predictions of AI models • Arrange data in a way that is easy to understand and interpret • Change the features of data to improve the accuracy of AI models • Classify data into different classes • Create visualizations of data to make it easier to understand • Describe the different types of XAI techniques • Illustrate the different concepts of XAI with diagrams and examples • List the different steps involved in the XAI process • Plan a project to apply XAI techniques to a real-world problem • Analyze data to identify patterns and trends • Select the most appropriate XAI technique for a given real-world problem • Relate the concepts of XAI to other fields of study, such as statistics and machine learning |
| Course Code | 6451 |
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