教學大綱表 (113學年度 第2學期)
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課程名稱
Course Title
(中文) 雲端運算架構基礎
(英文) Aws Cloud Computing Architecture Foundationsaws
開課單位
Departments
電機工程學系
課程代碼
Course No.
E4500
授課教師
Instructor
張伯廷
學分數
Credit
2.0 必/選修
core required/optional
選修 開課年級
Level
大三
先修科目或先備能力(Course Pre-requisites):Computer Architecture , Digital Communication
課程概述與目標(Course Overview and Goals):In this course, you will learn the details about cloud computing infrastructure, service models and applications. We will use the materials and the designed labs provided by AWS Academy to lead students to learn what and how to build the foundational architecture with safe and reliable service kernels on the AWS cloud. After the class, student will also be capable to prepare for AWS exam certification for their career plan or job requirement.
教科書(Textbook)
參考教材(Reference) AWS Academy Cloud Foundations
AWS Academy Machine Learning Foundations
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

No.
單元主題
Unit topic
內容綱要
Content summary
1 Course introduction (課程介紹) Introduction to the course roll-out based on ACF (AWS Academy Cloud Foundations) and AMLF(AWS Academy Machine Learning Foundations) and how we will evaluate student's learning progress through the lab exercise, final project and the exam. Understand the course objective and review it in your academic plan or career development. Then, you will be able to realize how to start up the AWS cloud computing lab exercise with the username and password registered. 上機實習
討論
講授
實作
 
2 Cloud Concepts Overview (雲端運算概念) 1. Cloud Computing Definition
2. Cloud Service Model
3. Cloud Computing Deployment Model
4. Advantage of Cloud Computing
5. Introduction to AWS and the Core Services
Establish the basic concepts including the cloud computing deployment and services models from the real examples and the design perspective of AWS. 上機實習
討論
講授
 
3 AWS Cloud Architecture (AWS 雲架構) 1. Architecture: designing and building
2. AWS Well-Architected Framework
- Operational Excellence
- Security
- Reliability
- Performance Efficiency
- Cost Optimization
3. AWS Cloud Infrastructure
Learn the cloud computing service architecture and core value positioning of AWS, and become a Cloud Architect after obtaining a license in the future. 上機實習
討論
講授
實作
 
4 AWS Global Infrastructure Overview (AWS 全球設施及雲服務介紹) 1. AWS Global Infrastructure (AWS 全球設施)
2. AWS service and service category overview(主要雲核心服務) including Computation(計算)、Security(資安)、Storage(儲存)、 Private Network(網路)、Database(資料庫) 、 Auto-scaling and Load Balance (自動調整及負載平衡)
Learn various AWS cloud computing core services, complete the design and implementation online, and understand its operation mode 上機實習
討論
講授
實作
 
5 AWS Cloud Security (雲資安介紹) 1. AWS shared responsibility model
2. AWS Identity and Access Management (IAM)
3. Securing a new AWS account
4. Securing accounts
5. Securing data on AWS
6. Working to ensure compliance
Students can learn how to use IAM to verify identity including user group, role and access management of resources, and maintain the security of personnel control and resource access through rules and policy. 上機實習
討論
講授
實作
實驗
 
6 AWS Cloud Services Labs (AWS 雲服務實作) 1. Networking and Content Delivery (VPC , Route 53)
2. Compute (EC2, Lambda, Beanstalk)
3. Storage (EBS, EFS, S3)
4. Databases (RDS, DynamoDB, Redshift, Aurora)
5. Elastic Load Balancing (ELB)
Learn how to use the major cloud services provided by AWS cloud to build up the cloud computing system as an architect in the designed lab environment. 上機實習
討論
講授
實驗
 
7 Cloud Computing Application(雲端運算服務應用) 1. AWS IoT (物連網架構)
2. AWS Academy Machine Learning Foundation (機器學習概論)
Let students understand how to use the functions provided by AWS to achieve IoT and machine learning solutions 上機實習
討論
講授
實作
實驗
 
8 AWS Academy Machine Learning Foundation Lab(機器學習基礎 實作) 1. Machine Learning (ML) Descriptions (機器學習敘述)
2. Use Amazon SageMaker to implement ML pipeline (實現機器學習管線程序)
3. Forecasting (電腦預測)
4. Computer vision (電腦視覺處理)
5. Natural Language processing, NLP(自然語言處理)
Using cloud computing resources to learn AI artificial intelligence and how to build up machine learning pipeline from data processing, training and inference procedures. 上機實習
討論
講授
實作
實驗
 
9 Final Project(期末專題) Final Project deliver(說明)
1. Requirement and specification (規格要求)
2. Schedule and dateline (完成期限)
3. Report in course and demo (報告並展示)
Be able to use all the knowledge learning from the course to build up an web applications based on the services provided in AWS learner lab environment. 上機實習
實作
心得發表
個別或小組指導
專題
 
10 Course conclusion and AWS exam certification (認證考試) 1. Make conclusion and the overall review on the course.
2. introduce possible future development directions, further education courses
3. Introduce AWS training and certifications after passing the exam.
4. Q&A
To refresh the key learning points of the course and know about the value or what can be achieve for their career plan if they can pass the exam and earn the certification associated. 講授
彈性教學
 
11 Final Exam (期末測驗) To simulate the AWS certification exam including ACF and AMLF. To earn the experience of certification exam using the similar test. 期末考
彈性教學
 
彈性教學週活動規劃

No.
實施期間
Period
實施方式
Content
教學說明
Teaching instructions
彈性教學評量方式
Evaluation
備註
Notes
1 起:2025-06-13 迄:2025-06-20 1.同步遠距教學 Synchronous distance learning Course conclusion and AWS exam certification (課程總結/認證考試) 期末測驗


教學要點概述:
1.自編教材 Handout by Instructor:
■ 1-1.簡報 Slids
■ 1-2.影音教材 Videos
□ 1-3.教具 Teaching Aids
□ 1-4.教科書 Textbook
□ 1-5.其他 Other
□ 2.自編評量工具/量表 Educational Assessment
□ 3.教科書作者提供 Textbook

成績考核 Performance Evaluation: 期末考:10%   實驗:50%   專題:30%   彈性教學:10%  

教學資源(Teaching Resources):
■ 教材電子檔(Soft Copy of the Handout or the Textbook)
□ 課程網站(Website)
扣考規定:https://curri.ttu.edu.tw/p/412-1033-1254.php