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There are 4 modules in this course
The course is intended for individuals looking to understand the basics of software engineering as they relate to building large software systems that leverage big data. You will be introduced to software engineering concepts necessary to build and scale large, data intensive, distributed systems. Starting with software engineering best practices and loosely coupled, highly cohesive data microservices, the course takes you through the evolution of a distributed system over time.
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://www.coursera.org/degrees/master-of-science-data-science-boulder
MS in Computer Science: https://coursera.org/degrees/ms-computer-science-boulder
Welcome to Fundamentals of Software Architecture for Big Data. In the first week of this course, you will learn the basics of modern software engineering. You will learn how our industry progresses over time, practice test driven development, and implement widely used data structures.
In this week you will learn the fundamentals of software architecture. You will learn how to evolve an architecture over time, how to work within a large codebase, and a bit about blockchain.
This week you will learn the fundamentals of monitoring software in production. You will learn how to create reliable background jobs, how to calculate and communicate service availability, and how to implement production metrics and monitoring.
What's included
1 video2 readings3 assignments
Show info about module content
1 video•Total 10 minutes
Production Readiness•10 minutes
2 readings•Total 120 minutes
Reliable Data Processing with Minimal Toil•60 minutes
The Calculus of Service Availability•60 minutes
3 assignments•Total 80 minutes
Deployment Papers•30 minutes
Provenance Metrics•30 minutes
Provenance Metrics Coding Exercise •20 minutes
Fundamentals of Software Architecture for Big Data
Module 4•6 hours to complete
Module details
In this last week of the course, you will learn the fundamentals of production quality databases and messaging systems. You will understand the tradeoffs between consistency and availability, how to implement database transactions to improve consistency, and how to implement messaging systems to improve availability.
What's included
3 videos4 readings4 assignments
Show info about module content
3 videos•Total 14 minutes
Cap Theorem Introduction•5 minutes
The Milk Problem•4 minutes
Event Collaboration•4 minutes
4 readings•Total 190 minutes
The Cap Theorem•60 minutes
Evolutionary Database Design•60 minutes
The Milk Problem Coding Exercise Instructions and Files•10 minutes
Perspectives on the CAP Theorem•60 minutes
4 assignments•Total 130 minutes
CAP Theorem•30 minutes
The Milk Problem•30 minutes
Perspectives on CAP Theorem•30 minutes
The Milk Problem Coding Exercise Instructions & Files•40 minutes
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Build toward a degree
This course is part of the following degree program(s) offered by University of Colorado Boulder. If you are admitted and enroll, your completed coursework may count toward your degree learning and your progress can transfer with you.¹
View eligible degrees
Build toward a degree
This course is part of the following degree program(s) offered by University of Colorado Boulder. If you are admitted and enroll, your completed coursework may count toward your degree learning and your progress can transfer with you.¹
¹Successful application and enrollment are required. Eligibility requirements apply. Each institution determines the number of credits recognized by completing this content that may count towards degree requirements, considering any existing credits you may have. Click on a specific course for more information.
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CU Boulder is a dynamic community of scholars and learners on one of the most spectacular college campuses in the country. As one of 34 U.S. public institutions in the prestigious Association of American Universities (AAU), we have a proud tradition of academic excellence, with five Nobel laureates and more than 50 members of prestigious academic academies.
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Learner reviews
3.5
92 reviews
5 stars
38.04%
4 stars
20.65%
3 stars
15.21%
2 stars
8.69%
1 star
17.39%
Showing 3 of 92
D
DR
5·
Reviewed on Oct 17, 2023
Make sure you have a basic to intermediate understanding of Java to complete the Assignments. The instructions can be vague and implied given the experience you're supposed to already have with Java.
M
MS
4·
Reviewed on Dec 14, 2023
The course is knowledgeable and enriching. The is scope for more peer interaction and virtual discussions/meetings once in a while.
J
JC
4·
Reviewed on Oct 19, 2023
Good lectures and code assignments to solidify concepts.
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.
Can I take cross-listed courses to fulfill my degree requirements?
Yes. Cross-listed courses are considered equivalent when evaluating graduation requirements. You can identify cross-listed courses by checking your program’s student handbook.
How do I upgrade and earn credit from CU Boulder?
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.
When will I have access to the lectures and assignments?
To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.