Reliability, Cloud Computing and Machine Learning

Coursera MOOC / Non-credit USD 49
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Reliability, Cloud Computing and Machine Learning

About this course

The course "Reliability, Cloud Computing and Machine Learning" explores advanced distributed database concepts, focusing on transaction management, reliability protocols, and data warehousing, while also diving deeper into cloud computing and machine learning. You will develop a solid understanding of transaction principles, concurrency control methods, and how to ensure database consistency during failures using ACID properties and protocols like ARIES. The course uniquely integrates Hadoop, MapReduce, and Accumulo, offering hands-on experience with large-scale data processing and machine learning applications such as collaborative filtering, clustering, and classification. By mastering these advanced topics, you'll gain the skills necessary to work with cutting-edge technologies used in cloud-based data processing and scalable machine learning analysis. With practical applications in both reliability management and machine learning, this course prepares you to tackle complex data management challenges, making you well-equipped for careers in cloud computing, distributed systems, and data science.

What you'll learn

  • understanding transaction principles
  • applying concurrency control methods
  • ensuring database consistency using ACID properties
  • working with Hadoop, MapReduce, and Accumulo
  • implementing machine learning applications like collaborative filtering and clustering

Course objectives

  • develop a solid understanding of reliability protocols
  • gain hands-on experience with large-scale data processing
  • prepare for careers in cloud computing, distributed systems, and data science

Skills you'll gain

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