Apache Hadoop is a software library operated by the Apache Software Foundation, an open-source software publisher. Hadoop is a framework used for distributed processing of big data, especially across a clustered network of computers. It uses simple programming models and can be used with a single server as well as with installations that involve hundreds or even thousands of machines with their own computation and storage capabilities. The Hadoop software is used to deliver services across a network of computers, any one of which could crash. This is important in data management, machine learning, data warehousing, and other machine-intensive programming applications.

What are typical careers that use Hadoop?

Careers that use Hadoop include computer engineering, computer programming, computer science, and data analysis. Hadoop is typically used in programming and data analysis positions that work with big data. Hence, more and more careers call for an understanding of it. Data management, machine learning, and cloud storage systems run on Hadoop. As more work involves big data, the ability to use Hadoop to collect and analyze it becomes more important. Learning Hadoop will prepare you to use data or to communicate with colleagues who are managing it. Structuring data warehouses and designing management dashboards can improve operations in many types of organizations. Hadoop is specialized, but its use is becoming more widespread.

How can online courses help me learn Hadoop?

Online courses can help you learn Hadoop by introducing you to the basics of it, having you work through exercises and create programs that use it, and seeing how it connects to other parts of the data warehouse. Some courses require no programming experience. Others assume that you understand programming but need specific experience with Hadoop. Some courses are practical, offering hands-on experience and leading to the creations of programs that can be used right away. Others are theoretical and explain the nature of Hadoop and the underlying principles of big data. The courses build on each other, with some leading to Specializations and online degrees.

검색
Hadoop

필터링 기준

"hadoop"에 대한 44개의 결과

IBM
IBM Data Engineering
획득할 기술: Algorithms, Apache, Big Data, Business Analysis, Cloud Computing, Cloud Engineering, Computational Logic, Computational Thinking, Computer Architecture, Computer Networking, Computer Programming, Computer Programming Tools, Data Architecture, Data Lake, Data Management, Data Model, Data Visualization, Data Visualization Software, Data Warehousing, Database Administration, Database Application, Database Theory, Databases, DevOps, Distributed Computing Architecture, Extract, Transform, Load, Graph Theory, Hardware Design, IBM Cloud, Kubernetes, Leadership and Management, Machine Learning, Machine Learning Algorithms, Mathematical Theory & Analysis, Mathematics, Microarchitecture, Network Architecture, Network Security, NoSQL, PostgreSQL, Professional Development, Programming Principles, Project Management, Python Programming, Relational Database, SQL, Security Engineering, Security Strategy, Software Architecture, Software Engineering, Statistical Programming, Strategy and Operations, Theoretical Computer Science
4.6
(34.8k개의 검토)
Beginner · Professional Certificate
University of California San Diego
Big Data
획득할 기술: Algorithms, Analytics, Apache, Big Data, Business Analysis, Computer Architecture, Computer Programming, Data Analysis, Data Architecture, Data Management, Data Model, Data Visualization, Data Warehousing, Database Administration, Databases, Distributed Computing Architecture, Exploratory Data Analysis, General Statistics, Graph Theory, Machine Learning, Machine Learning Algorithms, Mathematics, Modeling, NoSQL, PostgreSQL, Probability & Statistics, Python Programming, Regression, SQL, Statistical Programming, Theoretical Computer Science
4.5
(13.2k개의 검토)
Beginner · Specialization
Google Cloud
Data Engineering, Big Data, and Machine Learning on GCP
획득할 기술: Analytics, Apache, Applied Machine Learning, Bayesian Statistics, Big Data, Business Psychology, Cloud Computing, Cloud Platforms, Computer Architecture, Computer Networking, Computer Programming, Data Lake, Data Management, Deep Learning, Distributed Computing Architecture, Entrepreneurship, Feature Engineering, Full-Stack Web Development, General Statistics, Google Cloud Platform, Hardware Design, Machine Learning, Network Architecture, Probability & Statistics, Python Programming, Statistical Programming, Streams, Web Development
4.6
(16.5k개의 검토)
Intermediate · Specialization
Cloudera
Modern Big Data Analysis with SQL
획득할 기술: Analysis, Analytics, Apache, Big Data, Cloud Computing, Cloud Platforms, Cloud Storage, Computer Architecture, Computer Programming, Data Management, Data Model, Data Structures, Database Application, Database Design, Databases, Distributed Computing Architecture, Human Computer Interaction, Programming Principles, SQL, Software Engineering, Statistical Programming, Theoretical Computer Science, User Experience
4.7
(1.3k개의 검토)
Beginner · Specialization
Yonsei University
Emerging Technologies: From Smartphones to IoT to Big Data
획득할 기술: Adaptability, Android Development, Augmented Reality, Big Data, Business Psychology, Cloud Computing, Communication, Computational Logic, Computer Architecture, Computer Graphics, Computer Networking, Computer Vision, Data Analysis, Data Management, Entrepreneurship, Human Computer Interaction, Interactive Design, Internet, Internet Of Things, Machine Learning, Market Analysis, Marketing, Mathematical Theory & Analysis, Mathematics, Mobile Development, Network Architecture, Network Model, Network Security, Security Engineering, Theoretical Computer Science, User Experience, Virtual Reality, iOS Development
4.6
(1.6k개의 검토)
Beginner · Specialization
IBM
NoSQL, Big Data, and Spark Foundations
획득할 기술: Algorithms, Apache, Big Data, Cloud Computing, Computational Thinking, Computer Architecture, Computer Networking, Computer Programming, Data Management, Database Theory, Databases, Distributed Computing Architecture, Extract, Transform, Load, Graph Theory, IBM Cloud, Kubernetes, Machine Learning, Machine Learning Algorithms, Mathematics, Network Architecture, NoSQL, SQL, Statistical Programming, Theoretical Computer Science
4.2
(186개의 검토)
Beginner · Specialization

hadoop과(와) 관련된 검색

hadoop platform and application framework

introduction to cloud dataproc: hadoop and spark on google cloud

provisioning and using a managed hadoop/spark cluster with cloud dataproc (command line)

introduction to big data with spark and hadoop

요약하자면, 여기에 가장 인기 있는 hadoop 강좌 10개가 있습니다.

IBM Data Engineering: IBM
Introduction to Big Data with Spark and Hadoop: IBM
Big Data: University of California San Diego
Hadoop Platform and Application Framework: University of California San Diego
Data Engineering, Big Data, and Machine Learning on GCP: Google Cloud
Introduction to Cloud Dataproc: Hadoop and Spark on Google Cloud: Google Cloud
Modern Big Data Analysis with SQL: Cloudera
Emerging Technologies: From Smartphones to IoT to Big Data: Yonsei University
Foundations for Big Data Analysis with SQL: Cloudera
NoSQL, Big Data, and Spark Foundations: IBM

Software Development에서 학습할 수 있는 스킬

Google Cloud Platform (18)

애플리케이션 프로그래밍 인터페이스 (17)

Hadoop에 대한 자주 묻는 질문

Apache Hadoop is a software library operated by the Apache Software Foundation, an open-source software publisher. Hadoop is a framework used for distributed processing of big data, especially across a clustered network of computers. It uses simple programming models and can be used with a single server as well as with installations that involve hundreds or even thousands of machines with their own computation and storage capabilities. The Hadoop software is used to deliver services across a network of computers, any one of which could crash. This is important in data management, machine learning, data warehousing, and other machine-intensive programming applications.‎
Careers that use Hadoop include computer engineering, computer programming, computer science, and data analysis. Hadoop is typically used in programming and data analysis positions that work with big data. Hence, more and more careers call for an understanding of it. Data management, machine learning, and cloud storage systems run on Hadoop. As more work involves big data, the ability to use Hadoop to collect and analyze it becomes more important. Learning Hadoop will prepare you to use data or to communicate with colleagues who are managing it. Structuring data warehouses and designing management dashboards can improve operations in many types of organizations. Hadoop is specialized, but its use is becoming more widespread.‎
Online courses can help you learn Hadoop by introducing you to the basics of it, having you work through exercises and create programs that use it, and seeing how it connects to other parts of the data warehouse. Some courses require no programming experience. Others assume that you understand programming but need specific experience with Hadoop. Some courses are practical, offering hands-on experience and leading to the creations of programs that can be used right away. Others are theoretical and explain the nature of Hadoop and the underlying principles of big data. The courses build on each other, with some leading to Specializations and online degrees.‎