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    • Big Data Analytics

    필터링 기준

    "big data analytics"에 대한 391개의 결과

    • Google

      Google

      Google Data Analytics

      획득할 기술: Algorithms, Application Development, Big Data, Budget Management, Business Analysis, Business Communication, Change Management, Cloud Computing, Communication, Computational Logic, Computer Networking, Computer Programming, Computer Programming Tools, Cryptography, Data Analysis, Data Analysis Software, Data Management, Data Mining, Data Model, Data Structures, Data Type, Data Visualization, Data Visualization Software, Database Administration, Database Design, Databases, Decision Making, Design and Product, Entrepreneurship, Extract, Transform, Load, Feature Engineering, Finance, Financial Analysis, General Statistics, Interactive Data Visualization, Leadership and Management, Machine Learning, Mathematical Theory & Analysis, Mathematics, Network Security, Other Programming Languages, Plot (Graphics), Privacy, Probability & Statistics, Problem Solving, Product Design, Programming Principles, Project Management, R Programming, Research and Design, SQL, Security, Security Engineering, Security Strategy, Small Data, Software, Software Engineering, Software Security, Spreadsheet Software, Statistical Analysis, Statistical Programming, Storytelling, Strategy and Operations, Theoretical Computer Science, Visual Design

      4.8

      (64k개의 검토)

      Beginner · Professional Certificate

    • University of California San Diego

      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 Clustering Algorithms, 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, Mongodb, NoSQL, PostgreSQL, Probability & Statistics, Python Programming, Regression, SQL, Statistical Programming, Theoretical Computer Science

      4.5

      (13.2k개의 검토)

      Beginner · Specialization

    • IBM

      IBM

      Advanced Data Science with IBM

      획득할 기술: Algorithms, Apache, Applied Machine Learning, Artificial Neural Networks, Basic Descriptive Statistics, Bayesian Statistics, Big Data, Change Management, Cloud Computing, Computer Architecture, Computer Graphic Techniques, Computer Graphics, Computer Programming, Computer Vision, Correlation And Dependence, Data Analysis, Data Management, Data Model, Data Structures, Data Visualization, Databases, Deep Learning, Dimensionality Reduction, Distributed Computing Architecture, Econometrics, Estimation, Experiment, Extract, Transform, Load, General Statistics, IBM Cloud, Leadership and Management, Machine Learning, Machine Learning Algorithms, Natural Language Processing, Plot (Graphics), Probability & Statistics, Probability Distribution, Process, Programming Principles, Python Programming, Regression, SQL, Statistical Machine Learning, Statistical Programming, Statistical Visualization, Strategy and Operations, Theoretical Computer Science

      4.3

      (2.9k개의 검토)

      Advanced · Specialization

    • IBM

      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

      (187개의 검토)

      Beginner · Specialization

    • University of California San Diego

      University of California San Diego

      Introduction to Big Data

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

      4.6

      (10.5k개의 검토)

      Mixed · Course

    • IBM

      IBM

      Introduction to Data Analytics

      획득할 기술: Apache, Data Analysis, Business Analysis, Data Visualization Software, Big Data, Professional Development, Data Mining, Leadership and Management, Analysis, Data Visualization, Extract, Transform, Load, NoSQL, Data Structures, Analytics, Databases, Data Warehousing, General Statistics, Data Management

      4.8

      (6.9k개의 검토)

      Beginner · Course

    • Placeholder

      무료

      National Taiwan University

      National Taiwan University

      大數據分析:商業應用與策略管理 (Big Data Analytics: Business Applications and Strategic Decisions)

      획득할 기술: Data Analysis, Big Data, Analytics, Marketing, Business Analytics, Accounting, Data Management, Digital Marketing

      4.7

      (267개의 검토)

      Beginner · Course

    • Placeholder
      IBM

      IBM

      Introduction to Big Data with Spark and Hadoop

      획득할 기술: Distributed Computing Architecture, Apache, Big Data, Data Management, Cloud Computing, Extract, Transform, Load, Kubernetes, Computer Architecture

      4.2

      (97개의 검토)

      Beginner · Course

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      Cloudera

      Cloudera

      Foundations for Big Data Analysis with SQL

      획득할 기술: Database Application, Big Data, Analysis, Statistical Programming, Distributed Computing Architecture, Data Management, Analytics, Database Design, SQL, Computer Architecture, Databases

      4.8

      (984개의 검토)

      Beginner · Course

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      Arizona State University

      Arizona State University

      Big Data MasterTrack® Certificate

      획득할 기술: Security, Security Engineering, Data Visualization, Theoretical Computer Science, Computer Programming, Statistical Programming, Computer Networking, Software Testing, Software, Finance, Probability & Statistics, Artificial Neural Networks, Machine Learning, SQL, General Statistics, BlockChain, Software Engineering, Programming Principles, Bayesian Network, Network Security, Algorithms, Cryptography, Software Architecture, Data Analysis, Databases, Entrepreneurship, Data Mining, Mobile Development, Communication

      학점 제공

      Mastertrack

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      OP Jindal Global University

      OP Jindal Global University

      M.A. in International Relations, Security, and Strategy

      획득할 기술: Communication, Marketing, Sales

      학위 취득

      Degree

    • Placeholder
      University of Pennsylvania

      University of Pennsylvania

      Business Analytics

      획득할 기술: Accounting, Analysis, Big Data, Business Analysis, Business Psychology, Collaboration, Communication, Computational Logic, Computer Programming, Computer Programming Tools, Customer Analysis, Data Analysis, Data Analysis Software, Data Management, Data Structures, Decision Making, Entrepreneurship, Financial Accounting, Financial Analysis, Forecasting, General Statistics, Human Resources, Leadership and Management, Marketing, Mathematical Theory & Analysis, Mathematics, Network Analysis, People Analysis, People Development, Performance Management, Predictive Analytics, Probability & Statistics, Regression, Sales, Spreadsheet Software, Statistical Analysis, Strategy, Strategy and Operations, Talent Management, Theoretical Computer Science

      4.6

      (16.5k개의 검토)

      Beginner · Specialization

    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
    1234…33

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

    • Google Data Analytics: Google
    • Big Data: University of California San Diego
    • Advanced Data Science with IBM: IBM
    • NoSQL, Big Data, and Spark Foundations: IBM
    • Introduction to Big Data: University of California San Diego
    • Introduction to Data Analytics: IBM
    • 大數據分析:商業應用與策略管理 (Big Data Analytics: Business Applications and Strategic Decisions): National Taiwan University
    • Introduction to Big Data with Spark and Hadoop: IBM
    • Foundations for Big Data Analysis with SQL: Cloudera
    • Big Data MasterTrack® Certificate: Arizona State University

    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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