Recognizing Hallucinations, Inaccuracies, and Bias in AI
Demystify AI-generated content challenges - hallucinations, inaccuracies, biases. Develop detection skills and bias correction methods. Explore ethical AI use for transparency.
Skill level
BeginnerTime to complete
Approx. <1 hourCertificate of completion
YesPrerequisites
None
About this course
In this course, you will gain a focused understanding of the challenges related to hallucinations, inaccuracies, and biases in AI-generated content, including foundational concepts, identification strategies, and mitigation approaches to help you recognize and address these issues responsibly.
Learning objectives
- Discover the key concepts covered in this course
- Recognize the implications of ai-generated hallucinations in image and text generation
- Identify how the generative ai process can unintentionally lead to biased or inaccurate outputs
How it works
Expert-led videos
In this course, you'll watch videos created by industry-leading experts for some of the biggest tech companies in the world. They'll cover key concepts, go through sample applications, prepare you for industry certifications, and more. Watch on any device — whenever and wherever you want — to learn at your own pace.
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7 Facts You Probably Didn’t Know About Language Models
Everyone’s been talking about artificial intelligence (AI) as generative AI systems have become more mainstream over the past year. But the technology underlying these impressive programs isn’t new. The use of language models, computer programs that learn to understand and generate human language by analyzing large amounts of text, goes back decades.
Today, language models are used to build generative AI that can perform tons of different tasks. Here are a few fun facts that’ll give you a sense of their potential — but if you want to learn more about all the cool things you can do with AI, check out our AI courses.
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