课程概况
Database systems are used to provide convenient access to disk-resident data through efficient query processing, indexing structures, concurrency control, and recovery. This specialization delves into new frameworks for processing and generating large-scale datasets with parallel and distributed algorithms. Courses cover the design, deployment and use of state-of-the-art data processing systems, which provide scalable access to data.
All courses in this Specialization form the lecture and skill practice component of a corresponding course in ASU’s online Master of Computer Science Degree. You can apply to the degree program either before or after you begin the Specialization.
包含课程
第 1 门课程
Core Database Concepts
课程概述
This course introduces the world of database systems. It provides the foundation that will enable learners to master skills in data modeling and information, as well as extract information using existing database management systems. The following main topics are covered: database design/modeling, data storage and indexing, query processing/optimization, transaction management, database security, and data analytics.
您可以选择只参加本课程。
第 2 门课程
Distributed Database Systems
课程概述
The increased capabilities of a collection of logically interrelated databases distributed over a computer network enable scalable data processing. This course addresses the components of these systems, covering the following main topics: distributed database architectures, distributed data storage and indexing, distributed and parallel query processing/optimization, and concurrency control in distributed Parallel Database Systems.
第 3 门课程
NoSQL Database Systems
课程概述
Unlike traditional relational database management systems, NoSQL databases are capable of storing unstructured data. They therefore not only meet the performance, scalability, and flexibility needs that data-intensive applications require but are essential to big data processing. This course covers main NoSQL data management systems topics such as key-value stores, graph databases, and document databases.
第 4 门课程
Big Data Tools
课程概述
Systems that perform big data analytics require highly distributed architectures and new levels of memory and processing power. This course covers main topics associated with systems such as Hadopp MapReduce, Apache Spark, and Graph Processing Engines.
第 5 门课程
Data Management in the Cloud
课程概述
Ubiquitous, on-demand network access to shared pools of configurable computing resources ideally requires minimal management effort or service provider interaction. This course covers the essential characteristics of data processing in the cloud, service and deployment models, and key components of implementing Amazon Web Services, as well as constructing Hadoop clusters and performing MapReduce operations.
课程项目
Designed to help you practice and apply the skills you learn.
Project 1: Movie Recommendation Database
Project 2: Distributed Movie Recommendation Database
Project 3: Location-Aware Twitter Analytics
Project 4: Spatial Data Processing using Apache Spark
常见问题
退款政策是如何规定的？
您可以在付款后的 14 天内或在课程或专项课程开课后的 14 天内（以较晚者为准）申请退款。获得课程证书后，您便无法再退款；即使您在 14 天内完成了课程，也是如此。
请阅读完整的退款政策。
我可以只注册一门课程吗？我对整个专项课程不感兴趣。
要注册单门课程，请在目录中搜索相应的课程标题。
当当您订阅属于专项课程的课程时，您将自动订阅整个专项课程。如果您仅对单门课程感兴趣，您将需要在完成本课程后取消您的订阅，以停止定期缴纳每月费用。
可以申请助学金吗？
是的，Coursera 可以为无法承担费用的学生提供助学金。通过点击左侧“注册”按钮下的“助学金”链接可以申请助学金。您可以根据屏幕提示完成申请，申请获批后会收到通知。您需要针对专项课程中的每一门课程完成上述步骤，包括毕业项目。了解更多。
What background knowledge is necessary?
Basic computer science knowledge including computer organization and architecture, discrete mathematics, data structures, and algorithms
Knowledge of high-level programming languages (e.g., Java) and scripting language (e.g., Python), PostgreSQL
How long does it take to complete the Specialization?
Time to completion can vary based on your schedule and experience level, most individual courses, in which this Specialization has 5, will take about a month to complete if you devote 2-5 hours per week.
Do I need to take the courses in a specific order?
No, you may take the courses in any order.
Will I earn university credit for completing the Specialization?
All courses in this Specialization form the lecture and skill practice component of a corresponding course in ASU’s online Master of Computer Science Degree. You can apply to the degree program either before or after you begin the Specialization.
What will I be able to do upon completing the Specialization?
Learners completing this specialization will be able to:
Differentiate among major data models such as relational, spatial, and NoSQL
Perform queries (e.g., SQL) and analytics tasks in state-of-the-art database systems
Apply leading-edge techniques to design/tune distributed and parallel database systems
Utilize existing NoSQL database systems as appropriate for specified cases
Perform database operations (e.g., selection, projection, join, and groupby) in state-of-the-art cluster computing systems such as Hadoop/Spark
Perform scalable data processing operations (e.g., selection, projection, join, and groupby) in cloud computing environments, including Amazon AWS
