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Introduction to Relational Databases (RDBMS)
Are you ready to dive into the world of data engineering? You’ll need a solid understanding of how data is stored, processed, and accessed. You’ll need to identify the different types of database that are appropriate for the kind of data you are working with and what processing the data requires.
In this course, you will learn the essential concepts behind relational databases and Relational Database Management Systems (RDBMS). You’ll study relational data models and discover how they are created and what benefits they bring, and how you can apply them to your own data. You’ll be introduced to several industry standard relational databases, including IBM DB2, MySQL, and PostgreSQL.
This course incorporates hands-on, practical exercises to help you demonstrate your learning. You will work with real databases and explore real-world datasets. You will create database instances and populate them with tables.
No prior knowledge of databases or programming is required.
Anyone can audit this course at no-charge. If you choose to take this course and earn the Coursera course certificate, you can also earn an IBM digital badge upon successful completion of the course.
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Rating | Not enough ratings |
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Length | 5 weeks |
Effort | 4 weeks of study, 2-4 hours/week |
Starts | Jun 26 (47 weeks ago) |
Cost | $49 |
From | IBM, IBM Skills Network via Coursera |
Instructors | Sandip Saha Joy, Rav Ahuja, Lin Joyner, Rose Malcolm |
Download Videos | On all desktop and mobile devices |
Language | English |
Subjects | Data Science IT & Networking |
Tags | Data Science Data Analysis Information Technology Data Management |
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Rating | Not enough ratings |
---|---|
Length | 5 weeks |
Effort | 4 weeks of study, 2-4 hours/week |
Starts | Jun 26 (47 weeks ago) |
Cost | $49 |
From | IBM, IBM Skills Network via Coursera |
Instructors | Sandip Saha Joy, Rav Ahuja, Lin Joyner, Rose Malcolm |
Download Videos | On all desktop and mobile devices |
Language | English |
Subjects | Data Science IT & Networking |
Tags | Data Science Data Analysis Information Technology Data Management |
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