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
Prerequisites				self-directed learning in the course	Y

Relevance of Course Objectives and Core Learning Outcomes(%)			Teaching and Assessment Methods for Course Objectives
Course Objectives	Competency Indicators	Ratio(%)	Teaching Methods	Assessment Methods
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	1. 2. 3. 4. 5.	20 20 20 20 20	topic Discussion/Production Networking/Distance Education Exercises Discussion	Written Presentation Attendance Oral Presentation Assignment Study Outcome Quiz Other
Course Content and Homework/Schedule/Tests Schedule
Week Course Content Week 1 Microsoft Azure AI Fundamentals: AI Overview Microsoft Azure AI Fundamentals: Computer Vision Microsoft Azure AI Fundamentals: Natural Language Processing Week 2 Microsoft Azure AI Fundamentals: Document Intelligence and Knowledge Mining Microsoft Azure AI Fundamentals: Generative AI Week 3 Get started with Azure AI Services Week 4 Develop decision support solutions with Azure AI Services Week 5 Create computer vision solutions with Azure AI Vision Week 6 Develop natural language processing solutions with Azure AI Services Week 7 Implement knowledge mining with Azure Cognitive Search Week 8 Develop solutions with Azure AI Document Intelligence Week 9 Develop Generative AI solutions with Azure OpenAI Service Week 10 Test #1 Week 11 Explore the Azure Machine Learning workspace Week 12 Work with data in Azure Machine Learning Week 13 Automate machine learning model selection with Azure Machine Learning Week 14 Train models with scripts in Azure Machine Learning Week 15 Optimize model training with pipelines in Azure Machine Learning Week 16 Deploy and consume models with Azure Machine Learning Week 17 Test #2 Week 18 The future of AI
Evaluation
Test / Workshop / Discussion
Textbook & other References
None (use online materials)
Teaching Aids & Teacher's Website
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/
Office Hours
Sustainable Development Goals, SDGs
08.Decent Work and Economic Growth   09.Industry, Innovation and Infrastructure   10.Reduced Inequalities   11.Sustainable Cities and Communities   12.Responsible Consumption include experience courses：N

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Update Date, year/month/day：2024/07/01 16:08:39	Printed Date, year/month/day：2024 / 11 / 21
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