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所在平台: Udemy |
课程主页: https://www.udemy.com/course/certificed-generative-ai-expert-course/
课程评论：没有评论
课程名称：认证生成性人工智能专家课程 课程概述： 该课程旨在涵盖全面的生成性人工智能技能，包括以下主题： - 机器学习基础知识：监督学习与无监督学习 - 生成对抗网络（GAN）及其应用 - 变分自编码器（Variational Autoencoders）、变换器（Transformers）及其应用 - 卷积神经网络（Convolutional Neural Networks） - 专家系统与递归神经网络（Recurrent Neural Networks） - 生成性AI工具（如Alphacode、DALL E2、DUET AI、GitHub Copilot、ChatGPT4等） 此外，课程还包括： - 生成性AI基础知识, 生成性AI与非生成性AI的区别 - 生成性AI应用 - 文本数据处理 - ChatGPT概述与文本生成 - Google Bard文本生成 - 扩散AI模型 - Dream Studio平台的应用 - 使用Stable Diffusion生成和编辑图像 - 图像生成的提示工程 - 使用数据掩蔽防止数据泄露 - 私有生成性AI模型的应用 - 隐私设计在AI中的作用 课程还探讨了生成性AI在医疗、教育和旅游等行业的应用，以及在AI中与数据隐私相关的潜在风险、数据泄露的缓解方法、以及实施数据隐私文化的策略。 生成性专家具备创造、创新和生成内容的能力，深刻理解生成模型、神经网络、机器学习算法及其他先进技术，能够创造新颖而富有创意的输出。生成性AI基于数据中的模式生成新内容，如文本或图像。大型语言模型（LLMs）是这种AI的一种强大形式，可以生成类人文本，而小型语言模型（SLMs）则聚焦于使用较少数据的专门任务。检索增强生成（RAG）进一步提升了这些模型，通过外部信息来获得更准确的结果。AI代理利用生成性AI自主执行写作或研究等任务，代表了自动化和创造力的前沿发展。
This course covers below mentioed topics to be complete generative AI skills:• Machine learning basics. Supervised and Unsupervised learning. Generative Adversarial Network (GAN) and its application. Variational Autoencoders, Transformers and its application. Convolutional Neural Network , Expert systems, Recurrent neural networks. Generative AI tools (Alphacode, DALL E2, DUET AI, GIThub Copiolet, ChatGPT4 etc.)•Gen-AI basics •Gen- AI and Non Gen- AI•Gen-AI applications•Text Data•Gen-AT text Intro•Chatgpt Overview•Chatgpt - Text generation•Google bard - Text generation•Diffusion AI models•Dream studio platform•Generating Images with Stable Diffusion•Editing Images with Stable Diffusion•Prompt Engineering for Image Generation•Mitigating Data Leakage using Data Masking•Using Private Generative AI Models•Role of Privacy by Design in AIAsideGen AI use in Healthcare, Education, Tourism covered•Potential Risks to Data Privacy in AI•Mitigating Data Leakage using Data Masking•Using Private Generative AI Models•Role of Privacy by Design in AI•Implementing a Data Privacy CultureGenertive experts have good skills to create, innovate, and generate content. They have a deep understanding of generative models, neural networks, machine learning algorithms, and other advanced techniques that enable the creation of novel and creative outputs.Generative AI creates new content, like text or images, based on patterns in data. Large Language Models (LLMs) are a powerful form of this AI, generating human-like text, while Small Language Models (SLMs) focus on specialized tasks with less data. Retrieval-Augmented Generation (RAG) enhances these models by pulling in external information for more accurate results.AI Agents use generative AI to autonomously perform tasks such as writing or research. Together, they represent cutting-edge advancements in automation and creativity.
