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 | 課程介紹 |
•Introduction to Cloud Computing
•AWS與GCP雲端服務平台介紹 |
•認識雲端服務的應用面、優點、架構與雲端運算類型
•認識AWS/GCP雲端平台之服務、基礎架構與計算服務 |
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2 | Cloud Security, Networking and Content Delivery |
•AWS Identity Access Management (IAM)
•Amazon VPC
•Amazon CloudFront Content Delivery |
•認識AWS存取安全、網路與內容傳遞服務 |
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3 | Cloud Compute |
•Compute Services on AWS
•Amazon Elastic Compute Cloud (EC2)
•Container Services
•AWS Lambda
•AWS Elastic Beanstalk |
•認識AWS雲端平台之計算服務 |
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4 | Storage on AWS |
•Amazon Elastic Block Storage (EBS)
•Amazon Simple Storage Service (S3)
•Amazon Elastic File Service (EFS) |
•認識AWS之儲存服務 |
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5 | 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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6 | Cloud Architecture, Automatic Scaling and Monitoring |
•AWS Well-Architected Framework Design Principles
•Elastic Load Balancing
•Amazon CloudWatch
•Amazon EC2 Auto Scaling |
•認識AWS架構完善的框架設計原則以及監控、自動擴展和負載平衡 |
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7 | 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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8 | 期中考 |
AWS Cloud Foundations 專案報告與討論 |
檢驗上半學期學習成效 |
實作 心得發表
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期中考
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9 | 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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10 | Implementing a Machine Learning Pipeline with Amazon SageMaker (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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11 | Implementing a Machine Learning Pipeline with Amazon SageMaker (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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12 | 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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13 | Introducing Computer Vision (CV) |
•Introduction to computer vision
•Image and video analysis
•Preparing custom datasets for computer vision |
• 認識用於圖像和視頻分析的 Amazon 託管機器學習服務
• 使用 Amazon SageMaker Ground Truth 準備自定義數dataset
• 使用 Amazon Rekognition 執行臉部偵測 |
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14 | 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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15 | Introducing GCP, GAE and APIs |
•GCP 雲端平台開發環境介紹與建置
•Google App Engine的設定與SDK安裝
•Google App Engine的API與功能介紹 |
•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
•瞭解如何在Eclipse中開發一個簡單的專案 |
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16 | 期末考 |
AWS 整合專案報告與討論 |
檢驗本課程學習成效 |
實作 心得發表
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期末考
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