United States
The Non-degree in Databases: Modeling and Theory at Stanford University is a program for international students taught in English.
This course is one of five self-paced courses on the topic of Databases, originating as one of Stanford's three inaugural massive open online courses released in the fall of 2011. The original "Databases" courses are now all available on edx.org.This course covers underlying principles and design considerations related to databases; it can be taken either before or after taking other courses in the Databases series.The Relational Algebra section of this course teaches the algebraic query language that provides the formal foundations of SQL.The Relational Design Theory section of the course provides comprehensive coverage of dependency theory and normal forms in relational databases, a well-accepted theoretical framework for developing good relational database schemas.The Unified Modeling Language section of this course introduces the data-modeling component of UML, and describes how UML diagrams are translated to relational database schemas.The introductory videos in this course are the same as the introductory videos in Databases: Relational Databases and SQL ; they are included for the benefit of learners who have not taken Databases: Relational Databases and SQL.
Application Fee
$0 USD
$0 USD
Tuition Fee
$120 USD
$120 USD
per year
The minimum age is 18 and the maximum age is 50.
English Fluent is required.
Minimum education level Bachelor's degree
All students from all countries are eligible to apply to this program.
1
Step 1
Choose programs
2
Step 2
Apply online
3
Step 3
Enroll
Application Fee
$0 USD
Service Fee
$0 USD
Tuition
120
Boost Your Acceptance Rate with industry's no.1 admissions review and feedback
Easy Online Application
Thousands of international students use Global Admissions with 4.9 star reviews
Free Service to Partner Universities or upgrade to our Guaranteed Service
We use cookies to improve your experience and analyze site usage. Read our Privacy Policy to learn more about our data practices.