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    • Big Data

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    「big data」の684件の結果

    • Placeholder
      University of California San Diego

      Big Data

      習得できるスキル: Data Management, Big Data, Data Analysis, Exploratory Data Analysis, Probability & Statistics, Distributed Computing Architecture, Machine Learning, Business Analysis, Statistical Programming, Data Science, Graph Theory, Mathematics, Apache, Computer Architecture, Databases, Data Analysis Software, NoSQL, Data Architecture, Machine Learning Algorithms, Business, Data Model, Data Structures, Spreadsheet Software, Data Mining, Python Programming, Data Visualization, SQL, Statistical Machine Learning, Statistical Visualization, Database Application, Information Technology, Cloud Computing, Software As A Service, Applied Machine Learning, Basic Descriptive Statistics, Computer Programming, Correlation And Dependence, Database Administration, Dimensionality Reduction, Feature Engineering, General Statistics, PostgreSQL, Regression, Statistical Analysis, Algorithms, Data Warehousing, Theoretical Computer Science

      4.5

      (13.5k件のレビュー)

      Beginner · Specialization · 3-6 Months

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      IBM Skills Network

      IBM Data Engineering

      習得できるスキル: Data Management, Databases, Data Architecture, Data Structures, Big Data, Database Theory, SQL, Database Administration, Apache, Extract, Transform, Load, Python Programming, Database Application, Data Model, Data Warehousing, Data Analysis, NoSQL, Data Engineering, Distributed Computing Architecture, Database Design, Operating Systems, System Programming, System Software, Programming Principles, Statistical Programming, Computer Architecture, Algebra, PostgreSQL, Applied Machine Learning, Correlation And Dependence, Feature Engineering, General Statistics, Graph Theory, Machine Learning, Machine Learning Algorithms, Machine Learning Software, Regression, Statistical Analysis, Statistical Machine Learning, Data Visualization, Data Visualization Software, Basic Descriptive Statistics, Exploratory Data Analysis, Cloud Applications, Cloud Computing, Data Science, DevOps, Kubernetes, Leadership and Management, Network Architecture, Network Security, Other Programming Languages, Professional Development, Security Engineering, Accounting, Algorithms, Business Analysis, Cloud Engineering, Computational Logic, Computational Thinking, Computer Networking, Computer Programming, Computer Programming Tools, Hardware Design, IBM Cloud, Interactive Data Visualization, Linux, Mathematical Theory & Analysis, Mathematics, Microarchitecture, Project Management, Security Strategy, Software Architecture, Software Engineering, Strategy and Operations, Theoretical Computer Science

      4.6

      (40.4k件のレビュー)

      Beginner · Professional Certificate · 3-6 Months

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      Google

      Google Data Analytics

      習得できるスキル: Data Analysis, Data Science, Statistical Programming, Business Analysis, SQL, Spreadsheet Software, Business, Data Visualization, Data Management, R Programming, Exploratory Data Analysis, Statistical Visualization, Communication, Statistical Analysis, Data Analysis Software, Business Communication, Data Structures, Data Visualization Software, Tableau Software, Big Data, Cloud Computing, Collaboration, Conflict Management, Critical Thinking, Customer Analysis, General Statistics, Leadership and Management, Plot (Graphics), Probability & Statistics, Small Data, Algorithms, Application Development, Budget Management, Change Management, Computational Logic, Computer Architecture, Computer Networking, Computer Programming, Computer Programming Tools, Cryptography, Data Mining, Data Model, Database Administration, Database Design, Databases, Decision Making, Design and Product, Distributed Computing Architecture, Entrepreneurship, Extract, Transform, Load, Feature Engineering, Finance, Financial Analysis, Full-Stack Web Development, Interactive Data Visualization, Machine Learning, Mathematical Theory & Analysis, Mathematics, Network Security, Other Programming Languages, Problem Solving, Product Design, Programming Principles, Project Management, Research and Design, Security Engineering, Security Strategy, Software Engineering, Software Security, Storytelling, Strategy and Operations, Theoretical Computer Science, Visual Design, Visualization (Computer Graphics), Web Development

      4.8

      (101.4k件のレビュー)

      Beginner · Professional Certificate · 3-6 Months

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      IBM Skills Network

      Introduction to Big Data with Spark and Hadoop

      習得できるスキル: Apache, Big Data, Data Architecture, Distributed Computing Architecture, Computer Architecture, Data Management, Cloud Applications, Cloud Computing, Data Analysis, Data Warehousing, Database Administration, Databases, DevOps, Extract, Transform, Load, Kubernetes, Network Architecture, Other Programming Languages, SQL

      4.3

      (173件のレビュー)

      Beginner · Course · 1-3 Months

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      Universitat Autònoma de Barcelona

      Big Data – Introducción al uso práctico de datos masivos

      習得できるスキル: Data Management, Big Data, Business Analysis, Data Analysis, Accounting, Probability & Statistics, Data Visualization, Apache, Machine Learning, Financial Analysis, Regression, Data Visualization Software, Theoretical Computer Science, Computer Architecture, Databases, Distributed Computing Architecture, SQL, Statistical Programming, Data Structures, Business Intelligence, Data Analysis Software, Research and Design, Scientific Visualization, Tableau Software, Visual Design, Visualization (Computer Graphics), Cloud Computing, Cloud Platforms, Artificial Neural Networks, Dimensionality Reduction, Graph Theory, Mathematics, NoSQL, Software Architecture, Software Engineering, Advertising, Algorithms, Basic Descriptive Statistics, Business Psychology, Communication, General Statistics, Human Resources, Machine Learning Algorithms, Marketing, Plot (Graphics), Statistical Machine Learning, Training

      4.6

      (2.7k件のレビュー)

      Beginner · Specialization · 3-6 Months

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      Cloudera

      Modern Big Data Analysis with SQL

      習得できるスキル: Data Management, Databases, SQL, Big Data, Statistical Programming, Data Structures, Cloud Computing, Theoretical Computer Science, Apache, Computer Architecture, Distributed Computing Architecture, Cloud Platforms, Human Computer Interaction, Software Engineering, User Experience, Cloud Storage, Computer Programming, Programming Principles, Data Model, Database Administration, Database Design, Database Theory, Data Analysis, Data Warehousing, Database Application

      4.8

      (1.4k件のレビュー)

      Beginner · Specialization · 3-6 Months

    • Placeholder
      Placeholder
      IBM Skills Network

      IBM Data Science

      習得できるスキル: Python Programming, Data Science, Data Analysis, Data Structures, Statistical Programming, Machine Learning, Data Mining, Regression, Machine Learning Algorithms, Data Visualization, General Statistics, Basic Descriptive Statistics, SQL, Applied Machine Learning, Statistical Analysis, Computer Programming Tools, Data Analysis Software, Machine Learning Software, Software Visualization, Databases, Programming Principles, Exploratory Data Analysis, Computer Programming, Statistical Visualization, Algebra, Data Management, Database Theory, Data Visualization Software, R Programming, Statistical Machine Learning, Statistical Tests, Deep Learning, Probability & Statistics, Database Application, Extract, Transform, Load, Plot (Graphics), Devops Tools, SPSS, Estimation, Interactive Data Visualization, Algorithms, Database Administration, Geovisualization, Reinforcement Learning, Theoretical Computer Science, Big Data, Business Analysis, Computational Logic, Correlation And Dependence, Econometrics, Entrepreneurship, Marketing, Mathematical Theory & Analysis, Mathematics, Spreadsheet Software, Storytelling, Supply Chain Systems, Supply Chain and Logistics, Writing

      4.6

      (106.1k件のレビュー)

      Beginner · Professional Certificate · 3-6 Months

    • Placeholder
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      Google Cloud

      Data Engineering, Big Data, and Machine Learning on GCP

      習得できるスキル: Cloud Computing, Data Management, Computer Architecture, Cloud Platforms, Google Cloud Platform, Big Data, Distributed Computing Architecture, Machine Learning, SQL, Apache, Data Science, Hardware Design, Extract, Transform, Load, Cloud Storage, Full-Stack Web Development, Web Development, Databases, Information Technology, Python Programming, Statistical Programming, Computer Networking, Computer Programming, Data Analysis, Data Analysis Software, Data Visualization, Data Warehousing, Database Administration, Database Application, Database Theory, Kubernetes, Network Architecture, Operating Systems, Software Framework, System Programming, Theoretical Computer Science, Applied Machine Learning, Bayesian Statistics, Business Psychology, Cloud Applications, Cloud Infrastructure, Computational Thinking, Data Architecture, Data Model, Data Structures, Deep Learning, Entrepreneurship, Exploratory Data Analysis, Feature Engineering, General Statistics, Machine Learning Algorithms, Machine Learning Software, Probability & Statistics, Tensorflow

      4.6

      (17.4k件のレビュー)

      Intermediate · Specialization · 3-6 Months

    • Placeholder
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      IBM Skills Network

      NoSQL, Big Data, and Spark Foundations

      習得できるスキル: Big Data, Data Architecture, Apache, Data Management, Databases, NoSQL, Distributed Computing Architecture, Database Theory, Database Administration, Data Structures, Database Application, Data Model, Computer Architecture, Data Analysis, Extract, Transform, Load, Applied Machine Learning, Correlation And Dependence, Feature Engineering, General Statistics, Graph Theory, Machine Learning, Machine Learning Algorithms, Machine Learning Software, Regression, Statistical Analysis, Statistical Machine Learning, Statistical Programming, Database Design, Data Warehousing, SQL, Cloud Applications, Cloud Computing, DevOps, Kubernetes, Network Architecture, Other Programming Languages, Algorithms, Computational Thinking, Computer Networking, Computer Programming, IBM Cloud, Mathematics, Theoretical Computer Science

      4.3

      (307件のレビュー)

      Beginner · Specialization · 3-6 Months

    • Placeholder
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      University of Colorado Boulder

      Software Architecture for Big Data

      習得できるスキル: BlockChain, Finance, Software Architecture, Software Engineering, Theoretical Computer Science, Big Data

      3.4

      (8件のレビュー)

      Advanced · Specialization · 1-3 Months

    • Placeholder
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      University of California San Diego

      Introduction to Big Data

      習得できるスキル: Big Data, Data Architecture, Distributed Computing Architecture, Apache, Cloud Computing, Data Analysis Software, NoSQL, Software As A Service, Computer Architecture, Data Analysis, Data Management

      4.6

      (10.7k件のレビュー)

      Mixed · Course · 1-3 Months

    • Placeholder
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      IBM Skills Network

      IBM Data Analyst

      習得できるスキル: Data Analysis, Python Programming, Data Visualization, Exploratory Data Analysis, Basic Descriptive Statistics, Data Structures, Statistical Programming, Data Science, Statistical Visualization, Plot (Graphics), Data Management, General Statistics, SQL, Databases, Business Analysis, Microsoft Excel, Spreadsheet Software, Data Mining, Statistical Analysis, Programming Principles, Probability & Statistics, Regression, Machine Learning, Algebra, Computer Programming, Data Analysis Software, Database Theory, Probability Distribution, Applied Machine Learning, Statistical Tests, Big Data, Correlation And Dependence, Data Visualization Software, Database Application, Estimation, NoSQL, Geovisualization, ArcGIS, Cloud Computing, Data Warehousing, Database Administration, Extract, Transform, Load, HTML and CSS, Knitr, Mathematics, Minitab, PostgreSQL, R Programming, SAS (Software), SPSS, Apache, Computational Logic, Computer Programming Tools, Econometrics, Leadership and Management, Mathematical Theory & Analysis, Operating Systems, Professional Development, Statistical Machine Learning, System Programming, Theoretical Computer Science

      4.6

      (60.7k件のレビュー)

      Beginner · Professional Certificate · 3-6 Months

    big dataに関連する検索

    big data analytics
    big data analysis with scala and spark (scala 2 version)
    big data integration and processing
    big data analysis with scala and spark
    big data modeling and management systems
    big data, genes, and medicine
    big data emerging technologies
    big data: visualización de datos
    1234…57

    要約して、big data の人気コース10選をご紹介します。

    • Big Data: University of California San Diego
    • IBM Data Engineering: IBM Skills Network
    • Google Data Analytics: Google
    • Introduction to Big Data with Spark and Hadoop: IBM Skills Network
    • Big Data – Introducción al uso práctico de datos masivos: Universitat Autònoma de Barcelona
    • Modern Big Data Analysis with SQL: Cloudera
    • IBM Data Science: IBM Skills Network
    • Data Engineering, Big Data, and Machine Learning on GCP: Google Cloud
    • NoSQL, Big Data, and Spark Foundations: IBM Skills Network
    • Software Architecture for Big Data: University of Colorado Boulder

    Machine Learningで学べるスキル

    Pythonプログラミング (33)
    TensorFlow (32)
    ディープラーニング (30)
    人工ニューラルネットワーク (24)
    統計的分類 (17)
    強化学習 (13)
    代数 (10)
    ベイズ (10)
    線型代数学 (10)
    線形回帰 (9)
    NumPy (9)

    ビッグデータに関するよくある質問

    • “Big data” is a term widely used to describe our data-rich world, in which virtually every activity generates a digital data footprint that can be collected and analyzed. While data and data analysis are not necessarily new, the effective use of the extremely large - and rapidly-growing - datasets of today require new approaches to data management.

      In order to harness big data for important applications like machine learning and artificial intelligence, you need more than an Excel spreadsheet or a traditional relational database and SQL. Instead, an entire data infrastructure is necessary to collect and process this data at scale, including data pipelines, data lakes, and data warehouses.

      To make this possible, data engineers rely on new approaches to data processing such as MapReduce, developed by Google, the open-source Apache Hadoop ecosystem including Apache Spark and Apache Hive, and, increasingly, cloud computing and cloud database platforms like Cloudera.‎

    • With companies in practically every industry eager to discover ways to harness the power of big data in their operations, having a background in this area can open doors to a wide range of careers. Operations managers at manufacturing or logistics companies may harness data to improve their demand forecasting, inventory planning, and process efficiency; digital marketers use marketing analytics to better understand their customers and the effectiveness of their messaging; and “quants” at hedge funds rely on data-based financial engineering approaches to move millions of dollars in milliseconds.

      Understanding how big data applications are built and what they are capable of can thus be incredibly valuable even if you aren’t a data engineer or data scientist yourself. However, if you have the expertise and desire to work directly with big data yourself, data engineers are responsible for building the data infrastructure capable of reliably and efficiently delivering big data at scale, and data scientists are responsible for using a wide range of analytic and programming approaches to uncover insights from it.

      These two roles are in extremely high demand, and command salaries to match. According to Glassdoor, data engineers earn an average annual salary of $102,864, and data scientists earn an average annual salary of $113,309.‎

    • Yes - in fact, Coursera is one of the best places to learn about big data. You can take individual courses and Specializations spanning multiple courses on big data, data science, and related topics from top-ranked universities from all over the world, from the University California San Diego to Universitat Autònoma de Barcelona. Coursera also offers the opportunity to learn from industry leaders in the field like Google Cloud, Cloudera, and IBM, including options to get professional certificates.‎

    • The skills and experience that you might need to already have before starting to learn big data may include software programming knowledge as well as top skills in math, algebra, data science, and related areas. The types of programming languages that are common in big data environments include Python, SQL, Java, C, and overall data structure and algorithm insights. Working with structured and unstructured data may likely require knowledge and background in discrete mathematics, statistics, and linear algebra. Of course, learning about big data roles would also require you to bring good soft skills like listening, focus, communication, and flexibility to the table. Finally, what would also play a part before starting to learn big data might include a good education in data science or mathematics.‎

    • The kind of people best suited for work that involves big data are those who are keenly interested in data sciences, statistical modeling, data analysis, and the move to a big data future with the internet. People who love to work with data are best suited for roles in big data. This would likely include persons who may have quantitative experience in data technology, or a background and a skill set working with accounting, finance, ratios, and percentages. Big data enthusiasts may also be adventurous types, who take big risks and want to work at the forefront of technology and society.‎

    • Learning big data may be right for you if you have strong analytical insights, a data science background, a head for numbers, and a familiarity with internet tools, cloud platforms, and data analysis software. Working in big data is one of the most in-demand jobs now, and the opportunity to work in a relevant field is very alluring. If you're flexible in your work roles, are a creative thinker, and have the discipline and right background, then learning big data may be right for you to advance your career forward.‎

    このFAQの内容は、情報提供のみを目的としています。受講生は、自分の個人的、職業的、経済的な目標に合ったコースやその他の資格を取得するために、さらに調べることをお勧めします。
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