Large-Scale Database Systems

Software > Computer Software > Educational Software Johns Hopkins University

Course Overview

The specialization “Large-Scale Database Systems” is intended for post-graduate students seeking to develop advanced skills in distributed database systems, cloud computing, and machine learning. Through three comprehensive courses, you will dive into key topics such as distributed database architecture, transaction management, concurrency control, query optimization, and data reliability protocols, equipping you to handle complex data environments. You will also gain hands-on experience with cloud computing concepts, including Hadoop and the MapReduce framework, essential for large-scale data processing. In addition, you'll explore machine learning applications such as collaborative filtering, clustering, and classification techniques, learning to optimize these models for scalable analysis in distributed systems. By the end of the specialization, you will have developed an understanding of optimizing large-scale data warehouses and implementing machine learning algorithms for scalable analysis. This specialization will prepare you to design and optimize high-performance, fault-tolerant data solutions, making you well-equipped to work with large-scale distributed systems in industries like data analytics, cloud services, and machine learning development.

Course FAQs

What are the prerequisites for 'Large-Scale Database Systems'?

Prerequisites for this continuing education class are set by Johns Hopkins University. Most professional development online classes benefit from some prior knowledge. Please check the provider's page for specific requirements.

Will I receive a certificate for this CE class?

Yes, upon successful completion, Johns Hopkins University typically offers a shareable certificate to showcase your new skills and fulfill your continuing education requirements.

How long does this online course take to complete?

Completion times for online continuing education courses vary. The provider's website will have the most accurate estimate of the time commitment needed.