課程大綱 Syllabus |
學生學習目標 Learning Objectives |
單元學習活動 Learning Activities |
學習成效評量 Evaluation |
備註 Notes |
序 No. | 單元主題 Unit topic |
內容綱要 Content summary |
1 | Course Introduction |
•課程介紹
•AWS與GCP雲端服務平台介紹 |
•認識AWS/GCP雲端平台之服務與API |
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2 | AWS Fundamentals |
•AWS services and infrastructure
•Compute Services on AWS
•Amazon Elastic Compute Cloud (EC2) |
•認識AWS雲端平台之服務、基礎架構與計算服務 |
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3 | Networking and Storage on AWS |
•Amazon VPC
•Amazon CloudFront Content Delivery
•Amazon Elastic Block Storage (EBS)
•Amazon Simple Storage Service (S3)
•Amazon Elastic File Service (EFS) |
•認識AWS網路、內容傳遞與儲存服務 |
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4 | Databases on AWS |
•Amazon Relational Database Service (RDS)
•Amazon DynamoDB
•Amazon Redshift
•Amazon Aurora |
•認識AWS資料庫之應用服務 |
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5 | Build Serverless Application |
•Creating a Serverless Website with Amazon S3
•Serverless Computing with AWS Lambda |
•學習在AWS上建置無伺服器應用 |
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6 | Introducing AWS Machine Learning Services |
•What is machine learning?
•Business problems solved with machine learning
•Machine learning process
•Machine learning tools overview
•Machine learning challenges
•Introducing Amazon SageMaker |
•認識人工智慧、機器學習、深度學習
•探索企業的ML使用案例
•了解企業如何使用工具和技術來實現商業目標
•了解採用AI與ML所面臨的挑戰 |
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7 | Implementing a Machine Learning Pipeline with Amazon SageMaker: Part I |
•Formulating machine learning problems
•Collecting and securing data
•Evaluating your data
•Feature engineering |
•認識Amazon SageMaker機器學習管線並實作其流程 |
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8 | Implementing a Machine Learning Pipeline with Amazon SageMaker: Part II |
•Training a model
•Hosting and using the model
•Evaluating the accuracy of the model
•Hyperparameter and model tuning |
•認識Amazon SageMaker機器學習管線並實作其流程 |
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9 | 期中考 |
測驗與實作報告 |
檢驗上半學期學習成效 |
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10 | Introducing Forecasting |
•Forecasting overview
•Processing time series data
•Using Amazon Forecast |
•認識預測和學習以Amazon Forecast服務解決商業問題 |
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11 | Introducing Natural Language Processing (NLP) |
•Natural language processing managed services
•Amazon Transcribe
•Amazon Polly
•Amazon Translation
•Comprehend
•Amazon Lex - Create a chatbot |
•瞭解與使用 AWS 自然語言處理服務 |
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12 | Amazon managed NLP services Integration Application |
•Amazon Transcribe, Amazon Translation, Amazon Comprehend, Amazon Polly, Amazon Lex之綜合應用 |
•使用Amazon託管之自然語言處理服務之實作 |
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13 | GCP 與 GAE開發環境介紹與建置 |
•GCP 雲端平台介紹
•Google App Engine的設定與SDK安裝 |
•認識Google雲端平台和Google App Engine雲端服務
•認識以Java 語言開發Google雲端服務使用的軟體及環境建置 |
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14 | GAE的API與功能介紹 |
•Google App Engine的API與功能介紹
•建立一個GAE應用程式
•在GAE中設計Servlet
•在GAE中設計JSP |
•瞭解如何在Eclipse中開發一個簡單的專案
•熟悉GAE與其開發方式,學習JSP 與Servlet的設計以及在Eclipse中進行執行與測試 |
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15 | GCP之資料儲存 |
•Cloud Storage
•Cloud Datastore
•Google App Engine API 專題 |
•瞭解GCP之資料儲存模式與實作 |
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16 | GAE之整合範例 |
•網頁應用程式服務之設計
•各項功能與頁面開發
•完成整合並使用應用程式 |
•整合相關知識並使用JSP、Servlet、Datastore等在專案中實作一個範例系統網頁 |
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17 | 期末專案分組報告(一) |
•AWS/Google雲端服務系統專題之設計與實作報告及討論 |
•學習運用所學技術於專案之合作開發 |
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18 | 期末專案分組報告(二) |
•AWS/Google雲端服務系統專題之設計與實作報告及討論 |
•學習運用所學技術於專案之合作開發 |
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