- Apache Hadoop
- Mongodb
- Big Data
- Apache Spark
- NoSQL Databases
- NoSQL
- Cloud Database
- Cloudant
- Cassandra
- SparkSQL
- SparkML
NoSQL, Big Data, and Spark Foundations 특화 과정
Springboard your Big Data career. Master fundamentals of NoSQL, Big Data, and Apache Spark with hands-on job-ready skills in machine learning and data engineering.
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배울 내용
Work with NoSQL databases to insert, update, delete, query, index, aggregate, and shard/partition data.
Develop hands-on NoSQL experience working with MongoDB, Apache Cassandra, and IBM Cloudant.
Develop foundational knowledge of Big Data and gain hands-on lab experience using Apache Hadoop, MapReduce, Apache Spark, Spark SQL, and Kubernetes.
Perform Extract, Transform and Load (ETL) processing and Machine Learning model training and deployment with Apache Spark.
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Big Data Engineers and professionals with NoSQL skills are highly sought after in the data management industry. This Specialization is designed for those seeking to develop fundamental skills for working with Big Data, Apache Spark, and NoSQL databases. Three information-packed courses cover popular NoSQL databases like MongoDB and Apache Cassandra, the widely used Apache Hadoop ecosystem of Big Data tools, as well as Apache Spark analytics engine for large-scale data processing.
You start with an overview of various categories of NoSQL (Not only SQL) data repositories, and then work hands-on with several of them including IBM Cloudant, MonogoDB and Cassandra. You’ll perform various data management tasks, such as creating & replicating databases, inserting, updating, deleting, querying, indexing, aggregating & sharding data. Next, you’ll gain fundamental knowledge of Big Data technologies such as Hadoop, MapReduce, HDFS, Hive, and HBase, followed by a more in depth working knowledge of Apache Spark, Spark Dataframes, Spark SQL, PySpark, the Spark Application UI, and scaling Spark with Kubernetes. In the final course, you will learn to work with Spark Structured Streaming Spark ML - for performing Extract, Transform and Load processing (ETL) and machine learning tasks.
This specialization is suitable for beginners in the fields of NoSQL and Big Data – whether you are or preparing to be a Data Engineer, Software Developer, IT Architect, Data Scientist, or IT Manager.
응용 학습 프로젝트
The emphasis in this specialization is on learning by doing. As such, each course includes hands-on labs to practice & apply the NoSQL and Big Data skills you learn during lectures.
In the first course, you will work hands-on with several NoSQL databases- MongoDB, Apache Cassandra, and IBM Cloudant to perform a variety of tasks: creating the database, adding documents, querying data, utilizing the HTTP API, performing Create, Read, Update & Delete (CRUD) operations, limiting & sorting records, indexing, aggregation, replication, using CQL shell, keyspace operations, & other table operations.
In the next course, you’ll launch a Hadoop cluster using Docker and run Map Reduce jobs. You’ll explore working with Spark using Jupyter notebooks on a Python kernel. You’ll build your Spark skills using DataFrames, Spark SQL, and scale your jobs using Kubernetes.
In the final course you will use Spark for ETL processing, and Machine Learning model training and deployment using IBM Watson.
공유 가능한 수료증
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100% 온라인 강좌
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
유연한 일정
유연한 마감을 설정하고 유지 관리합니다.
초급 단계
The courses in the specialization require that you have basic computer and data literacy skills, as well as some programming background with languages such as with Python and SQL. No prior knowledge or experience of Big Data and NoSQL is required.
완료하는 데 약 4개월이 걸립니다
권장 학습 속도: 주 3시간
영어
자막: 영어
공유 가능한 수료증
완료 시 수료증 획득
100% 온라인 강좌
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
유연한 일정
유연한 마감을 설정하고 유지 관리합니다.
초급 단계
The courses in the specialization require that you have basic computer and data literacy skills, as well as some programming background with languages such as with Python and SQL. No prior knowledge or experience of Big Data and NoSQL is required.
완료하는 데 약 4개월이 걸립니다
권장 학습 속도: 주 3시간
영어
자막: 영어
특화 과정 이용 방법
강좌 수강
Coursera 특화 과정은 한 가지 기술을 완벽하게 습득하는 데 도움이 되는 일련의 강좌입니다. 시작하려면 특화 과정에 직접 등록하거나 강좌를 둘러보고 원하는 강좌를 선택하세요. 특화 과정에 속하는 강좌에 등록하면 해당 특화 과정 전체에 자동으로 등록됩니다. 단 하나의 강좌만 수료할 수도 있으며, 학습을 일시 중지하거나 언제든 구독을 종료할 수 있습니다. 학습자 대시보드를 방문하여 강좌 등록 상태와 진도를 추적해 보세요.
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모든 특화 과정에는 실습 프로젝트가 포함되어 있습니다. 특화 과정을 완료하고 수료증을 받으려면 프로젝트를 성공적으로 마쳐야 합니다. 특화 과정에 별도의 실습 프로젝트 강좌가 포함되어 있는 경우, 다른 모든 강좌를 완료해야 프로젝트 강좌를 시작할 수 있습니다.
수료증 취득
모든 강좌를 마치고 실습 프로젝트를 완료하면 취업할 때나 전문가 네트워크에 진입할 때 제시할 수 있는 수료증을 취득할 수 있습니다.
이 전문 분야에는 3개의 강좌가 있습니다.
Introduction to NoSQL Databases
77개의 평가
This course will provide you with technical hands-on knowledge of NoSQL databases and Database-as-a-Service (DaaS) offerings. With the advent of Big Data and agile development methodologies, NoSQL databases have gained a lot of relevance in the database landscape. Their main advantage is the ability to effectively handle scalability and flexibility issues raised by modern applications.
Introduction to Big Data with Spark and Hadoop
86개의 평가
Bernard Marr defines Big Data as the digital trace that we are generating in this digital era. In this course, you will learn about the characteristics of Big Data and its application in Big Data Analytics. You will gain an understanding about the features, benefits, limitations, and applications of some of the Big Data processing tools. You’ll explore how Hadoop and Hive help leverage the benefits of Big Data while overcoming some of the challenges it poses.
Data Engineering and Machine Learning using Spark
45개의 평가
Organizations need skilled, forward-thinking Big Data practitioners who can apply their business and technical skills to unstructured data such as tweets, posts, pictures, audio files, videos, sensor data, and satellite imagery and more to identify behaviors and preferences of prospects, clients, competitors, and others.
제공자:
IBM
IBM is the global leader in business transformation through an open hybrid cloud platform and AI, serving clients in more than 170 countries around the world. Today 47 of the Fortune 50 Companies rely on the IBM Cloud to run their business, and IBM Watson enterprise AI is hard at work in more than 30,000 engagements. IBM is also one of the world’s most vital corporate research organizations, with 28 consecutive years of patent leadership. Above all, guided by principles for trust and transparency and support for a more inclusive society, IBM is committed to being a responsible technology innovator and a force for good in the world.
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전문 분야를 완료하는 데 얼마나 걸리나요?
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