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 Master Program in Industrial and Smart Technology/Graduate 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

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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
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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 Develop natural language processing solutions with Azure AI Services
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
04.Quality Education   08.Decent Work and Economic Growth   09.Industry, Innovation and Infrastructure   10.Reduced Inequalities   11.Sustainable Cities and Communities   12.Responsible Consumption   17.Partnerships for the Goalsinclude experience courses:N
Please respect the intellectual property rights and use the materials legally.Please repsect gender equality.
Update Date, year/month/day:2024/07/01 16:09:16 Printed Date, year/month/day:2024 / 10 / 13
The second-hand book website:http://www.myub.com.tw/