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Applications of Software Architecture for Big Data

Applications of Software Architecture for Big Data

本课程是 Software Architecture for Big Data 专项课程的一部分

位教师：Tyson Gern

2,556 人已注册

包含在 Coursera Plus 中

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4个模块

深入了解一个主题并学习基础知识。

3.5

（18 条评论）

高级设置等级

推荐体验

灵活的计划

2 周在 10 小时一周

自行安排学习进度

攻读学位

了解更多

4个模块

深入了解一个主题并学习基础知识。

3.5

（18 条评论）

高级设置等级

推荐体验

灵活的计划

2 周在 10 小时一周

自行安排学习进度

攻读学位

了解更多

您将学到什么

Practice software engineering fundamentals; test first development, refactoring, continuous integration, and continuous delivery.
Architect and create a big data or distributed system using rest collaboration, event collaboration, and batch processing.
Create a performant, scalable distributed system that handles big data.

要了解的详细信息

可分享的证书

添加到您的领英档案

作业

7 项作业

授课语言：英语（English）

了解顶级公司的员工如何掌握热门技能

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Petrobras, TATA, Danone, Capgemini, P&G 和 L'Oreal 的徽标

积累特定领域的专业知识

本课程是 Software Architecture for Big Data 专项课程专项课程的一部分

在注册此课程时，您还会同时注册此专项课程。

向行业专家学习新概念
获得对主题或工具的基础理解
通过实践项目培养工作相关技能
获得可共享的职业证书

该课程共有4个模块

The course is intended for individuals who want to build a production-quality software system that leverages big data.

You will apply the basics of software engineering and architecture to create a production-ready distributed system that handles big data. You will build data intensive, distributed system, composed of loosely coupled, highly cohesive applications. This course can be taken for academic credit as part of CU Boulder’s MS in Data Science or MS in Computer Science degrees offered on the Coursera platform. These fully accredited graduate degrees offer targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission is based on performance in three preliminary courses, not academic history. CU degrees on Coursera are ideal for recent graduates or working professionals. Learn more: MS in Data Science: https://hua.dididi.sbs/degrees/master-of-science-data-science-boulder MS in Computer Science: https://coursera.org/degrees/ms-computer-science-boulder

Welcome to Applications of Software Architecture for Big Data. This is a project-based course where you will apply the knowledge and skills gained from the entire Software Architecture for Big Data specialization. In this first week, you will learn about the expectations for the project as well as how to establish the features you need to get started with your own.

涵盖的内容

4个视频9篇阅读材料1次同伴评审

4个视频总计21分钟

Project Introduction6分钟
Example Codebase5分钟
Project Selection5分钟
White Board Architecture4分钟

9篇阅读材料总计85分钟

Earn Academic Credit for Your Work! 10分钟
Course Support10分钟
Motivation for Peer Review10分钟
Assessment Expectations5分钟
AI Citation and Acknowledgement 10分钟
Project Rubric10分钟
Example Codebase10分钟
Requirements Elicitation10分钟
Story Writing10分钟

1次同伴评审总计60分钟

Project Description & White Board Architecture 60分钟

This week you will learn about the concept of a Minimum Viable Product (MVP) and how to incrementally add features to the MVP. Additionally, we will show you how to get going with a development environment and set up appropriate tests.

涵盖的内容

3个视频5篇阅读材料3个作业1次同伴评审

3个视频总计15分钟

What is an MVP?4分钟
Testing3分钟
Continuous Integration & Continuous Delivery6分钟

5篇阅读材料总计95分钟

Project Structure10分钟
Setting up a Web Application45分钟
Case Study10分钟
Unit Tests20分钟
Integration Tests10分钟

3个作业总计100分钟

Testing and CI/CD 40分钟
Testing30分钟
Continuous Integration & Continuous Delivery30分钟

1次同伴评审总计120分钟

Web Application120分钟

This week builds upon your previously created MVP. Now, you will learn how to create a database, populate the database as well as analyze the data in the database. The week ends with further elaboration on testing.

涵盖的内容

2个视频3篇阅读材料2个作业1次同伴评审

This week you will add more features to your project, including collaborative messaging. You'll end this week by building a simple health check for production monitoring and discuss acceptance testing.

涵盖的内容

1个视频2篇阅读材料2个作业

获得职业证书

将此证书添加到您的 LinkedIn 个人资料、简历或履历中。在社交媒体和绩效考核中分享。

攻读学位

课程是 University of Colorado Boulder提供的以下学位课程的一部分。如果您被录取并注册，您已完成的课程可计入您的学位学习，您的学习进度也可随之转移。

位教师

Tyson Gern

University of Colorado Boulder

3 门课程10,959 名学生

提供方

University of Colorado Boulder

从 Software Development 浏览更多内容

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人们为什么选择 Coursera 来帮助自己实现职业发展

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学生评论

3.5

18 条评论

5 stars
38.88%
4 stars
5.55%
3 stars
33.33%
2 stars
11.11%
1 star
11.11%

显示 3/18 个

已于 Nov 10, 2023审阅

This course is really great, by completing all the practical assignments I learned about many key concepts of modern software engineering.

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常见问题

A cross-listed course is offered under two or more CU Boulder degree programs on Coursera. For example, Dynamic Programming, Greedy Algorithms is offered as both CSCA 5414 for the MS-CS and DTSA 5503 for the MS-DS.

· You may not earn credit for more than one version of a cross-listed course.

· You can identify cross-listed courses by checking your program’s student handbook.

· Your transcript will be affected. Cross-listed courses are considered equivalent when evaluating graduation requirements. However, we encourage you to take your program's versions of cross-listed courses (when available) to ensure your CU transcript reflects the substantial amount of coursework you are completing directly in your home department. Any courses you complete from another program will appear on your CU transcript with that program’s course prefix (e.g., DTSA vs. CSCA).

· Programs may have different minimum grade requirements for admission and graduation. For example, the MS-DS requires a C or better on all courses for graduation (and a 3.0 pathway GPA for admission), whereas the MS-CS requires a B or better on all breadth courses and a C or better on all elective courses for graduation (and a B or better on each pathway course for admission). All programs require students to maintain a 3.0 cumulative GPA for admission and graduation.

Yes. Cross-listed courses are considered equivalent when evaluating graduation requirements. You can identify cross-listed courses by checking your program’s student handbook.

You may upgrade and pay tuition during any open enrollment period to earn graduate-level CU Boulder credit for << this course/ courses in this specialization>>. Because << this course is / these courses are >> cross listed in both the MS in Computer Science and the MS in Data Science programs, you will need to determine which program you would like to earn the credit from before you upgrade.

MS in Data Science (MS-DS) Credit: To upgrade to the for-credit data science (DTSA) version of << this course / these courses >>, use the MS-DS enrollment form. See How It Works.

MS in Computer Science (MS-CS) Credit: To upgrade to the for-credit computer science (CSCA) version of << this course / these courses >>, use the MS-CS enrollment form. See How It Works.

If you are unsure of which program is the best fit for you, review the MS-CS and MS-DS program websites, and then contact [email protected] or [email protected] if you still have questions.

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