Artificial Intelligence (AI) has rapidly evolved in recent years, and one of its most fascinating branches is Generative AI. This technology enables computers to create content, from text to images and even music, that is often indistinguishable from human-generated content. If you're keen to explore the world of Generative AI, you're in luck because LinkedIn offers several free courses that can help you dive into this exciting field. In this article, we'll introduce you to five LinkedIn courses that will allow you to learn Generative AI at no cost.
This course provides a comprehensive introduction to Generative Adversarial Networks (GANs), a fundamental concept in Generative AI. GANs consist of two neural networks, a generator, and a discriminator, that work in tandem to create and evaluate content. This LinkedIn course explores the theory behind GANs and offers practical hands-on experience, making it an excellent starting point for those new to the field.
Text generation is one of the most exciting applications of Generative AI, and this course by Lynn Langit demonstrates how to create generative text using Python. You'll learn how to build language models and understand the underlying principles of natural language generation. By the end of the course, you'll be able to generate text that mimics human writing.
This course focuses specifically on Generative Adversarial Networks in Python. You'll explore GANs in-depth and learn how to apply them to generate images and art. The practical insights and coding exercises offered in this course will help you get hands-on experience with GANs and unleash your creativity.
Before diving deep into Generative AI, it's crucial to have a solid foundation in neural networks, which are at the core of Generative AI models. This LinkedIn course covers neural network fundamentals, making it an excellent prerequisite for anyone looking to understand how Generative AI model's function.
This advanced course delves into the intricacies of Generative Adversarial Networks (GANs) in machine learning. It covers GAN theory, advanced applications, and practical implementation. While it's more in-depth than the other courses on this list, it provides a comprehensive understanding of GANs and their applications in the real world.
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