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온라인 학위경력 찾기기업용 Coursera대학교용
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    • Big Data Analytics
    Related topics:빅 데이터hadoophadoop mapreduceHiveApache Sparksql 데이터베이스

    필터링 기준

    "big data analytics"에 대한 390개의 결과

    • 무료

      The University of Sydney

      The University of Sydney

      Life, Health and Radiation

      획득할 기술: Big Data, Scientific Visualization, Data Visualization, Physics, Medicine, Data Management, Computer Graphic Techniques, Communication, Computer Graphics, Marketing, Social Media

      4.8

      (213개의 검토)

      Mixed · Course

    • IBM

      IBM

      Data Engineering Capstone Project

      획득할 기술: SQL, Big Data, Data Visualization, Python Programming, Data Visualization Software, Bash (Unix Shell), NoSQL, Databases, Computer Programming, Data Management, Apache Spark, Computer Architecture, PostgreSQL, Statistical Programming, Information Engineering, Distributed Computing Architecture, Mongodb, Business Analysis, Apache, Extract, Transform, Load, Data Warehousing

      4.4

      (20개의 검토)

      Beginner · Course

    • Microsoft

      Microsoft

      Data Integration with Microsoft Azure Data Factory

      획득할 기술: Data Management, Cloud Computing, Analytics, Application Development, Continuous Integration, Software Engineering Tools, Big Data, Microsoft Azure, Software Engineering, Accounting, DevOps, Extract, Transform, Load

      3.9

      (40개의 검토)

      Intermediate · Course

    • University of California San Diego

      University of California San Diego

      Hadoop Platform and Application Framework

      획득할 기술: Big Data, Data Management, Apache, Apache Spark, Distributed Computing Architecture, Computer Architecture

      4.0

      (3.3k개의 검토)

      Mixed · Course

    • IE Business School

      IE Business School

      Legal Tech & Startups

      획득할 기술: Entrepreneurship, Big Data, Customer Relationship Management, Virtual Reality, Market (Economics), Strategy and Operations, Research and Design, Data Management, Human Computer Interaction, Web Development, Marketing, Business Development, Sales, Market Research, Finance, Modeling, Computer Graphics

      4.5

      (201개의 검토)

      Intermediate · Course

    • 무료

      University of California, Irvine

      University of California, Irvine

      Emergent Phenomena in Science and Everyday Life

      획득할 기술: Data Visualization, Big Data, Scientific Visualization, Data Analysis, Mathematics, General Statistics, Statistical Analysis, Epidemiology, Probability & Statistics, Data Management, Mathematical Theory & Analysis, Business Analysis

      4.3

      (139개의 검토)

      Mixed · Course

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      Coursera Project Network

      Coursera Project Network

      Building Machine Learning Pipelines in PySpark MLlib

      획득할 기술: Big Data, Theoretical Computer Science, Data Management, Random Forest, Computer Programming, Machine Learning, Computational Thinking, Apache

      4.3

      (49개의 검토)

      Intermediate · Guided Project

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      Universidad Austral

      Universidad Austral

      Pilares de Marketing Digital

      획득할 기술: Big Data, Financial Analysis, Strategy and Operations, Market (Economics), Digital Marketing, Web, Sales, Leadership and Management, Research and Design, Entrepreneurship, Market Research, Data Analysis, Communication, Analytics, Email, Strategy, Data Management, Accounting, Business Analysis, Marketing, Market Analysis, Social Media, Supply Chain and Logistics, E-Commerce

      4.8

      (1.9k개의 검토)

      Beginner · Course

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      CFA Institute

      CFA Institute

      Data and Statistics Foundation for Investment Professionals

      획득할 기술: Python Programming, Data Analysis, Probability & Statistics, Computer Programming, Investment Management, Business Analysis, Data Visualization, Basic Descriptive Statistics, Statistical Tests, General Statistics, Statistical Analysis, Statistical Programming, Risk Management, Finance, Probability Distribution

      4.4

      (14개의 검토)

      Beginner · Course

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      University of California, Davis

      University of California, Davis

      Healthcare Data Literacy

      획득할 기술: Big Data, Clinical Data Management, Health Care, Data Management, Leadership and Management

      4.5

      (88개의 검토)

      Intermediate · Course

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      Google Cloud

      Google Cloud

      Google Cloud Fundamentals: Core Infrastructure 日本語版

      획득할 기술: Cloud Storage, Big Data, Machine Learning, Cloud Computing, Data Management, Google App Engine, Google Cloud Platform, Kubernetes

      4.5

      (582개의 검토)

      Intermediate · Course

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      Google

      Google

      Fazer perguntas para tomar decisões com base em dados

      획득할 기술: Big Data, Data Analysis, Financial Analysis, Cloud Computing, Data Management, Small Data, Accounting, Spreadsheet Software, Business Analysis, Process Analysis

      4.3

      (10개의 검토)

      Beginner · Course

    big data analytics과(와) 관련된 검색

    大數據分析:商業應用與策略管理 (big data analytics: business applications and strategic decisions)
    graph analytics for big data
    big data analytical platform on alibaba cloud
    big data analysis with scala and spark
    big data analysis with scala and spark (scala 2 version)
    big data analysis deep dive
    big data analysis to a slide presentation
    modern big data analysis with sql
    1…212223…33

    요약하자면, 여기에 가장 인기 있는 big data analytics 강좌 10개가 있습니다.

    • Life, Health and Radiation: The University of Sydney
    • Data Engineering Capstone Project: IBM
    • Data Integration with Microsoft Azure Data Factory: Microsoft
    • Hadoop Platform and Application Framework: University of California San Diego
    • Legal Tech & Startups: IE Business School
    • Emergent Phenomena in Science and Everyday Life: University of California, Irvine
    • Building Machine Learning Pipelines in PySpark MLlib: Coursera Project Network
    • Pilares de Marketing Digital: Universidad Austral
    • Data and Statistics Foundation for Investment Professionals: CFA Institute
    • Healthcare Data Literacy: University of California, Davis

    Machine Learning에서 학습할 수 있는 스킬

    Python 프로그래밍 (33)
    TensorFlow (32)
    심층 학습 (30)
    인공 신경 회로망 (24)
    빅 데이터 (18)
    통계 분류 (17)
    강화 학습 (13)
    대수학 (10)
    베이지안 (10)
    선형 대수 (10)
    선형 회귀 (9)
    Numpy (9)

    Big Data Analytics에 대한 자주 묻는 질문

    • Big data analytics refers to the application of advanced data analysis techniques to datasets that are very large, diverse (including structured and unstructured data), and often arriving in real time. The ability to process data at this scale is increasingly essential to navigating today’s business world, and it is at the core of important applications such as machine learning, business intelligence, financial engineering, and other software tools to enable data-informed decision-making.

      Computer programs have been used to assist with data analysis for decades, but tools like Microsoft Excel and traditional relational database management systems (RDBMS) queried with SQL are not capable of handling today’s high-volume, high-velocity datasets. Instead, today’s data management professionals rely on high-powered data infrastructure designed to work with distributed file systems and cloud computing resources - particularly the open-source Apache Hadoop ecosystem, including high-speed data processing with Apache Spark and distributed SQL engines like Apache Hive.‎

    • Organizations of all types and sizes are seeking ways to leverage the possibilities of big data to improve operations through reduced costs and faster decision-making, create new products and services, or advance our knowledge about the world. Big data analytics skills can thus open up a wide range of career opportunities, from working as a “quant” on Wall Street to developing navigation systems for autonomous vehicles to helping to discover more effective medicines and drugs in health science.

      Two of the most broadly-applicable roles in this field are data engineers, who build the data infrastructure needed to deliver big data-scale datasets efficiently and reliably, and the data scientists responsible for analyzing them. These roles are in high demand, and are highly-paid as well; according to Glassdoor, data engineers earn an average annual salary of $102,864, and data scientists earn an average annual salary of $113,309.‎

    • Absolutely! Data science is one of the most popular topics to learn about on Coursera, and there are a variety of options to build your skills in big data analytics. You can take online courses and Specializations from top-ranked schools like the University of Pennsylvania and the University of California San Diego, as well as leading companies like IBM, PwC, Cloudera, and Google Cloud. And regardless of where you choose to learn from, Coursera gives you the ability to access course materials and complete assignments on a flexible schedule, making this a great fit for students and mid-career professionals alike.‎

    • Before you start learning big data analytics, it’s helpful to have an understanding of database management and the fundamentals of how programming languages work. Specifically, experience with SQL, Python, Java, or R can be useful when studying big data analytics. You also may find it beneficial to know how to work with Hadoop and Linux and use basic math and statistics. Additionally, strong analytical skills and a curiosity about playing with data come in handy when you learn big data analytics.‎

    • The right people for roles in big data analytics are inquisitive problem solvers who like working with numbers and using statistics to sort through large amounts of data. They typically have work experience or coursework in high-level math or computer programming. A background in behavioral analysis can also be useful for roles in big data analytics because individuals often seek to understand or predict what influences the behavior represented by data. Big data analysts may often need soft skills, such as communication and collaboration skills they use when explaining what they see in the data and working with team members on projects.‎

    • If you like working with numbers and are comfortable using statistical techniques, learning big data analytics may be right for you. The amount of data collected on a daily basis is already massive and continues to grow, so organizations need analysts who can curate and prepare data for businesses, governments, and other groups to use. Learning big data analytics may interest you if you possess strong analytical and problem-solving skills and want to apply those skills to sorting and analyzing data to find what’s useful for a client. You may be able to use the knowledge you gain to land an internship or seek a career in data science filling roles in a variety of industries.‎

    이 FAQ 콘텐츠는 정보 전달 목적만으로 사용할 수 있습니다. 학습자는 과정 및 기타 학점 정보가 개인적, 직업적 및 재정적 목표에 부합하는지 확인하기 위해 추가 조사를 수행하는 것이 좋습니다.
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