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    • Data Engineering

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    1283 résultats pour ''data engineering'

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      IBM Skills Network

      IBM Data Engineering

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

      4.6

      (40.3k avis)

      Beginner · Professional Certificate · 3-6 Months

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      IBM Skills Network

      Data Engineering Foundations

      Compétences que vous acquerrez : Data Structures, Data Management, Databases, SQL, Python Programming, Database Theory, Data Engineering, Data Analysis, Data Model, Database Application, Programming Principles, Extract, Transform, Load, Data Architecture, Database Administration, Algebra, Database Design, PostgreSQL, Statistical Programming, Basic Descriptive Statistics, Exploratory Data Analysis, Apache, Big Data, Data Science, Data Warehousing, Leadership and Management, Network Security, Professional Development, Security Engineering, Computational Logic, Computer Architecture, Computer Networking, Computer Programming, Computer Programming Tools, Distributed Computing Architecture, Mathematical Theory & Analysis, Mathematics, NoSQL, Project Management, Security Strategy, Strategy and Operations, Theoretical Computer Science

      4.6

      (39.6k avis)

      Beginner · Specialization · 3-6 Months

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      Duke University

      Python, Bash and SQL Essentials for Data Engineering

      Compétences que vous acquerrez : Computer Programming, Statistical Programming, Python Programming, Data Management, Theoretical Computer Science, Cloud Computing, Databases, Software Engineering, Computer Programming Tools, Human Computer Interaction, Software Architecture, User Experience, Operating Systems, Amazon Web Services, Linux, Extract, Transform, Load, Data Structures, SQL, Cloud Platforms, Apache, Application Development, Big Data, Data Analysis, Data Engineering, DevOps, Programming Principles, Software Engineering Tools, Database Administration, Database Application, Applied Machine Learning, Cloud Applications, Cloud Engineering, Machine Learning, Machine Learning Algorithms, Systems Design, Data Mining

      4.5

      (151 avis)

      Beginner · Specialization · 3-6 Months

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      Google Cloud

      Data Engineering, Big Data, and Machine Learning on GCP

      Compétences que vous acquerrez : 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 avis)

      Intermediate · Specialization · 3-6 Months

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      Meta

      Meta Database Engineer

      Compétences que vous acquerrez : Statistical Programming, Computer Programming, Data Management, Databases, Python Programming, SQL, Programming Principles, Software Engineering, Theoretical Computer Science, Database Administration, Database Application, Application Development, Computer Programming Tools, Software Architecture, Software Engineering Tools, Database Design, Database Theory, Software Testing, Data Analysis, Data Structures, Human Computer Interaction, Javascript, User Experience, Web Development, Applied Machine Learning, Business Analysis, Collaboration, Communication, Entrepreneurship, Exploratory Data Analysis, Leadership and Management, Linux, Machine Learning, Market Research, Operating Systems, Probability & Statistics, Research and Design, Accounting, Algorithms, Computer Science, Data Model, Data Warehousing, Django (Web Framework), Financial Analysis, Journalism, Mathematics, Operations Research, Other Programming Languages, Project Management, Strategy and Operations

      4.7

      (1.8k avis)

      Beginner · Professional Certificate · 3-6 Months

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      Microsoft

      Microsoft Azure Data Engineering Associate (DP-203)

      Compétences que vous acquerrez : Cloud Computing, Microsoft Azure, Data Management, Extract, Transform, Load, Big Data, Data Warehousing, Cloud Storage, Statistical Programming, Apache, Cloud Infrastructure, Databases, SQL, Data Analysis, Accounting, Business Analysis, Financial Analysis, Computer Programming, Continuous Integration, DevOps, NoSQL, Business Psychology, Entrepreneurship, Leadership and Management, Organizational Development, Application Development, Computer Networking, Data Architecture, Network Security, Security Engineering, Security Strategy, Software Engineering, Software Engineering Tools

      4.3

      (496 avis)

      Intermediate · Professional Certificate · 3-6 Months

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      IBM Skills Network

      Introduction to Data Engineering

      Compétences que vous acquerrez : Data Engineering, Data Management, Extract, Transform, Load, Databases, Apache, Big Data, Data Analysis, Data Architecture, Data Warehousing, Leadership and Management, Network Security, Professional Development, SQL, Security Engineering, Computer Architecture, Computer Networking, Data Science, Database Administration, Distributed Computing Architecture, NoSQL, Project Management, Security Strategy, Statistical Programming, Strategy and Operations

      4.8

      (1.5k avis)

      Beginner · Course · 1-4 Weeks

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      Google Cloud

      Preparing for Google Cloud Certification: Cloud Data Engineer

      Compétences que vous acquerrez : Cloud Computing, Computer Architecture, Data Management, Google Cloud Platform, Cloud Platforms, Machine Learning, Big Data, Distributed Computing Architecture, Hardware Design, SQL, Information Technology, Data Science, Apache, Cloud Storage, Extract, Transform, Load, Cloud Engineering, Cloud Management, Databases, Full-Stack Web Development, Python Programming, Web Development, Computer Programming, Statistical Programming, Applied Machine Learning, Computer Science, Computer Networking, 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, 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

      (17.7k avis)

      Intermediate · Professional Certificate · 3-6 Months

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      Google

      Google Data Analytics

      Compétences que vous acquerrez : Data Analysis, Statistical Programming, Data Science, Business Analysis, SQL, Spreadsheet Software, Data Visualization, Business, Data Management, Data Visualization Software, R Programming, Leadership and Management, Exploratory Data Analysis, Statistical Visualization, Change Management, Strategy and Operations, Communication, Statistical Analysis, Data Analysis Software, Business Communication, Data Structures, Tableau Software, Big Data, Cloud Computing, Critical Thinking, Customer Analysis, General Statistics, Plot (Graphics), Probability & Statistics, Small Data, Algorithms, Application Development, Budget 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, Theoretical Computer Science, Visual Design, Visualization (Computer Graphics), Web Development

      4.8

      (100.8k avis)

      Beginner · Professional Certificate · 3-6 Months

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      IBM Skills Network

      IBM Data Warehouse Engineer

      Compétences que vous acquerrez : Data Management, Databases, SQL, Database Administration, Data Warehousing, Database Theory, Data Engineering, Statistical Programming, Data Architecture, Database Application, Extract, Transform, Load, Data Model, Operating Systems, System Programming, System Software, Data Structures, Database Design, PostgreSQL, Business Analysis, Apache, Big Data, Leadership and Management, Cloud Computing, Cloud Engineering, Data Visualization, Data Visualization Software, Interactive Data Visualization, Computer Architecture, Computer Programming, Data Analysis, Data Science, DevOps, Hardware Design, Network Security, Professional Development, Security Engineering, Accounting, Computer Networking, Distributed Computing Architecture, Linux, Microarchitecture, NoSQL, Programming Principles, Project Management, Python Programming, Security Strategy, Software Architecture, Software Engineering, Strategy and Operations, Theoretical Computer Science

      4.6

      (19k avis)

      Beginner · Professional Certificate · 3-6 Months

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      DeepLearning.AI

      Machine Learning Engineering for Production (MLOps)

      Compétences que vous acquerrez : Machine Learning, Applied Machine Learning, DevOps, Python Programming, Statistical Programming, Tensorflow, Exploratory Data Analysis, Feature Engineering, Probability & Statistics, Cloud Computing, Data Management, Data Warehousing, Extract, Transform, Load, Computer Programming, Computer Vision, Deep Learning, Business Analysis, Change Management, Computer Networking, Data Analysis, Data Visualization, Estimation, General Statistics, Leadership and Management, Machine Learning Algorithms, Network Security, Security Engineering, Security Strategy, Statistical Visualization, Strategy and Operations

      4.7

      (2.7k avis)

      Advanced · Specialization · 3-6 Months

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      Google Cloud

      Advanced Machine Learning on Google Cloud

      Compétences que vous acquerrez : Machine Learning, Cloud Computing, Google Cloud Platform, Cloud Platforms, Probability & Statistics, Business Psychology, General Statistics, Entrepreneurship, Statistical Programming, Apache, Cloud Applications, Data Management, Deep Learning, Machine Learning Software, Natural Language Processing, Python Programming, Reinforcement Learning, Tensorflow, Performance Management, Strategy and Operations, Applied Machine Learning, Artificial Neural Networks, Cloud API, Computational Thinking, Computer Architecture, Computer Programming, Computer Vision, Data Analysis, Data Engineering, Distributed Computing Architecture, Hardware Design, Machine Learning Algorithms, Other Cloud Platforms and Tools, Theoretical Computer Science

      4.5

      (1.4k avis)

      Advanced · Specialization · 3-6 Months

    Recherches liées à data engineering

    data engineering, big data, and machine learning on gcp
    data engineering foundations
    data engineering and machine learning using spark
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    data engineering, big data and ml on google cloud en español
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    data engineering career guide and interview preparation
    data engineering, big data and ml on google cloud 日本語版
    1234…84

    En résumé, voici 10 de nos cours data engineering les plus populaires

    • IBM Data Engineering: IBM Skills Network
    • Data Engineering Foundations: IBM Skills Network
    • Python, Bash and SQL Essentials for Data Engineering: Duke University
    • Data Engineering, Big Data, and Machine Learning on GCP: Google Cloud
    • Meta Database Engineer: Meta
    • Microsoft Azure Data Engineering Associate (DP-203): Microsoft
    • Introduction to Data Engineering: IBM Skills Network
    • Preparing for Google Cloud Certification: Cloud Data Engineer: Google Cloud
    • Google Data Analytics: Google
    • IBM Data Warehouse Engineer: IBM Skills Network

    Compétences que vous avez acquises en Software Development

    Langage De Programmation (34)
    Google (25)
    Programme Informatique (21)
    Test De Logiciels (21)
    Web (19)
    Google Cloud Platform (18)
    Interfaces De Programmation Applicatives (17)
    Structure Des Données (16)
    Résolution De Problèmes (14)
    Programmation Orientée Objet (13)
    Kubernetes (10)
    List & Label (10)

    Questions fréquentes sur Ingénierie des données

    • Data engineering is a subfield of data science responsible for designing, building, and maintaining data infrastructure to collect, process, store, and deliver data so that it can be used and analyzed at scale. Data engineering is extremely important for navigating today’s big data landscape because it enables organizations to generate timely data analysis to guide more effective decision-making.

      Data engineers are tasked with the responsibility of preparing massive amounts of data for analysis by data scientists. By using frameworks like Apache Spark to pull data from Hadoop data lakes, data engineers can deliver data for analysis quickly. With the use of machine learning platforms such as TensorFlow, they can train and use neural networks to help decipher unstructured data like video, audio, and image files. And, by using cloud database platforms like Cloudera, data engineers can leverage the power and scalability of cloud-based approaches for their work.

      Big data is changing the way we do business and creating a need for data engineers who can collect and manage large quantities of data. Learn more about the role of a data engineer and find out how to become one.‎

    • Data engineering is one of the fastest growing careers in tech, and salaries in this field are highly competitive. According to Glassdoor, the average base salary for data engineers is $102,864 per year.

      Data engineers are in high demand across many industries, and the nature of their work may vary depending on the size of their company. At small companies, data engineers may be a one-person team, doing everything from data collection to analysis. At mid-sized companies, data engineers lead teams that focus on building data pipelines and data transformation. And, at large companies, data engineers may spend most of their time tuning databases for fast analysis.‎

    • Yes! Coursera offers a wide range of online courses and Specializations in data engineering and related topics like machine learning and data science. You’ll be taking these courses from top-ranked institutions and organizations like the University of California San Diego, the University of Colorado, Google Cloud, and IBM, so you don’t have to sacrifice the quality of your education to learn online. Coursera also offers the opportunity to get professional certificates in data engineering and data science from Google Cloud and IBM, so you can continue to add to your credentials on your own flexible schedule.‎

    • When starting to learn data engineering, you might need to already have strong experience in working with data projects. A four-year college degree in computer science would be highly beneficial, but more often than not, companies might be more interested in someone who has a strong understanding of the fundamentals of computers, software, coding, and programming languages. You will need to have a comprehension of the data engineering ecosystem, databases, and languages like Python, Sequel, and C. It would also help to possess a keen analytical ability to see through the data weeds to offer some insights and understanding to others in your organization.‎

    • The kind of people best suited for work that involves data engineering are often computer programmers who are also analytical self-starters and problem solvers. They are curious people who can look at the big picture and the small details and manage the testing and validation points of the data. Data engineers love working with distributed systems and large sets of data and are able to understand the fundamentals of data technologies, data pipelines, and the computer frameworks that are used to integrate them together. Data engineers might also know the basics of machine learning algorithms, as well as DevOps, DataOps, and other tools to decide how to manage data in production platforms.‎

    • You might find that learning data engineering appeals to you if you love data sets, have an interest in quantitative and qualitative sciences, and aspire to be in a high-paying engineering role within a data science team that creates and manages the tech infrastructure of a data platform. You might already be dabbling with data projects on your own. If this is the case, then taking the next step to learn computer programming languages or reading up on machine learning might be a natural evolution. If you'd like a career in a growing field in our world’s technology evolution, then learning data engineering may be the right fit for you.‎

    Le contenu de cette FAQ a été mis à disposition à des fins d'information uniquement. Il est conseillé aux étudiants d'effectuer des recherches supplémentaires afin de s'assurer que les cours et autres qualifications suivis correspondent à leurs objectifs personnels, professionnels et financiers.
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