NCHU Course Outline |
Course Name | (中) 深入探討人工智慧技術和雲端人工智慧服務(6902) | ||||
(Eng.) Deep Inside into AI Technologies and Cloud AI Services | |||||
Offering Dept | Master Program in Industrial and Smart Technology | ||||
Course Type | Elective | Credits | 3 | Teacher | 曹祖聖 |
Department | Doctoral Program in Industrial and Smart TechnologyPh.D | Language | English | Semester | 2024-FALL |
Course Description | 本課程講授 AI 相關技術,包含機器學習、深度學習、生成式 AI、ChatGPT、... 並且使用 Microsoft Azure 雲做為實作的平台,課程包含每週的課後作業與大量實機操作,包含撰寫程式以使用認知服務 (語言、語音、影像、文件識別、...)、串接 OpenAI 服務、訓練與最佳化 AI 模型、部署 AI 服務,也會介紹目前業界在整合 AI 上的最佳做法。課程結束後學生有能力考取至少以下一張國際證照: • Microsoft Certified: Azure AI Fundamentals • Microsoft Certified: Azure AI Engineer Associate • Microsoft Certified: Azure Data Scientist Associate --------------------------------------------------------------------------------------------- This course delivers AI-related technologies, including machine learning, deep learning, generative AI, ChatGPT... and uses Microsoft Azure cloud as the implementation platform. Students attending this course need to do weekly homework and a lot of practices in the class, including writing codes to use cognitive services. (language, speech, image, document recognition...), connecting OpenAI services, training and optimizing AI models, deploying AI services, and we will also introduce the current best practices in integrating AI in the industry. After the course, students will be able to obtain at least one of the following international certificates: • Microsoft Certified: Azure AI Fundamentals • Microsoft Certified: Azure AI Engineer Associate • Microsoft Certified: Azure Data Scientist Associate |
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Prerequisites | self-directed learning in the course | Y |
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Plan and manage an Azure AI solution Implement decision support solutions Implement computer vision solutions Implement natural language processing solutions Implement knowledge mining and document intelligence solutions Implement generative AI solutions Design and prepare a machine learning solution Explore data and train models Prepare a model for deployment Deploy and retrain a model |
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https://learn.microsoft.com/en-us/training/paths/get-started-with-artificial-intelligence-on-azure/ https://learn.microsoft.com/en-us/training/paths/explore-computer-vision-microsoft-azure/ https://learn.microsoft.com/en-us/training/paths/explore-natural-language-processing/ https://learn.microsoft.com/en-us/training/paths/document-intelligence-knowledge-mining/ https://learn.microsoft.com/en-us/training/paths/introduction-generative-ai/ https://learn.microsoft.com/en-us/training/paths/get-started-azure-ai/ https://learn.microsoft.com/en-us/training/paths/develop-decision-support/ https://learn.microsoft.com/en-us/training/paths/create-computer-vision-solutions-azure-ai/ https://learn.microsoft.com/en-us/training/paths/develop-language-solutions-azure-ai/ https://learn.microsoft.com/en-us/training/paths/implement-knowledge-mining-azure-cognitive-search/ https://learn.microsoft.com/en-us/training/paths/extract-data-from-forms-document-intelligence/ https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/ https://learn.microsoft.com/en-us/training/paths/explore-azure-machine-learning-workspace/ https://learn.microsoft.com/en-us/training/paths/work-data-azure-machine-learning/ https://learn.microsoft.com/en-us/training/paths/automate-machine-learning-model-selection-azure-machine-learning/ https://learn.microsoft.com/en-us/training/paths/train-models-scripts-azure-machine-learning/ https://learn.microsoft.com/en-us/training/paths/use-azure-machine-learning-pipelines-for-automation/ https://learn.microsoft.com/en-us/training/paths/deploy-consume-models-azure-machine-learning/ |
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Please respect the intellectual property rights and use the materials legally.Please repsect gender equality. | |
Update Date, year/month/day:2024/07/01 16:08:39 | Printed Date, year/month/day:2024 / 9 / 08 |
The second-hand book website:http://www.myub.com.tw/ |