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    • Data Engineering

    Data Engineering Courses Online

    Learn data engineering for building data pipelines and infrastructure. Understand data integration, storage, and processing technologies.

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    Explore the Data Engineering Course Catalog

    • Status: AI skills
      AI skills

      IBM

      IBM Data Engineering

      Skills you'll gain: NoSQL, Data Warehousing, Apache Hadoop, Extract, Transform, Load, Apache Airflow, Web Scraping, Linux Commands, Database Design, SQL, IBM Cognos Analytics, MySQL, Apache Spark, Data Pipelines, Apache Kafka, Database Management, Bash (Scripting Language), Data Store, Jupyter, Generative AI, Professional Networking

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      58K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Multiple educators

      DeepLearning.AI Data Engineering

      Skills you'll gain: Apache Airflow, Data Modeling, Data Pipelines, Data Storage, Data Architecture, Data Transformation, Requirements Analysis, Data Processing, Data Warehousing, Query Languages, Apache Hadoop, Extract, Transform, Load, Data Lakes, Amazon Web Services, File Systems, Apache Spark, Database Systems, Data Integration, Infrastructure as Code (IaC), Terraform

      4.8
      Rating, 4.8 out of 5 stars
      ·
      432 reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • IBM

      Data Engineering Foundations

      Skills you'll gain: Web Scraping, Database Design, SQL, MySQL, Data Transformation, Data Store, Extract, Transform, Load, IBM DB2, Relational Databases, Data Architecture, Jupyter, Data Pipelines, Big Data, Data Warehousing, Data Governance, Data Manipulation, Stored Procedure, Databases, Automation, Python Programming

      4.6
      Rating, 4.6 out of 5 stars
      ·
      56K reviews

      Beginner · Specialization · 3 - 6 Months

    • IBM

      Introduction to Data Engineering

      Skills you'll gain: Data Store, Extract, Transform, Load, Data Architecture, Data Pipelines, Big Data, Data Warehousing, Data Governance, Apache Hadoop, Relational Databases, Apache Spark, Data Lakes, Databases, SQL, NoSQL, Data Security

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.1K reviews

      Beginner · Course · 1 - 4 Weeks

    • Google Cloud

      Data Engineering, Big Data, and Machine Learning on GCP

      Skills you'll gain: Data Pipelines, Dataflow, Google Cloud Platform, Real Time Data, Data Lakes, MLOps (Machine Learning Operations), Dashboard, Data Warehousing, Extract, Transform, Load, Cloud Engineering, Data Infrastructure, Cloud Infrastructure, Cloud Storage, Big Data, Tensorflow, Unstructured Data, Data Integration, Data Migration, Data Processing, Data Visualization Software

      4.6
      Rating, 4.6 out of 5 stars
      ·
      18K reviews

      Intermediate · Specialization · 3 - 6 Months

    • DeepLearning.AI

      Introduction to Data Engineering

      Skills you'll gain: Data Pipelines, Data Architecture, Requirements Analysis, Amazon Web Services, Data Warehousing, Data Modeling, Data Processing, System Requirements, Performance Tuning, Security Controls, Data Transformation, Scalability

      4.8
      Rating, 4.8 out of 5 stars
      ·
      359 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Duke University

      Python, Bash and SQL Essentials for Data Engineering

      Skills you'll gain: Pandas (Python Package), Bash (Scripting Language), Version Control, Jupyter, Linux Commands, Git (Version Control System), Shell Script, Linux, Web Scraping, Linux Administration, Data Manipulation, MySQL, Microservices, AWS SageMaker, SQL, JSON, Scripting, Cloud Engineering, Command-Line Interface, Software Development Tools

      4.5
      Rating, 4.5 out of 5 stars
      ·
      428 reviews

      Beginner · Specialization · 3 - 6 Months

    • Snowflake

      Introduction to Modern Data Engineering with Snowflake

      Skills you'll gain: Data Pipelines, Data Transformation, Extract, Transform, Load, Data Integration, Data Warehousing, Real Time Data, Data Import/Export, Stored Procedure, Data Sharing, SQL, Automation, Command-Line Interface

      4.8
      Rating, 4.8 out of 5 stars
      ·
      97 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free
      Free

      Amazon Web Services

      Data Engineering on AWS - Foundations

      Skills you'll gain: Infrastructure as Code (IaC), Cloud Engineering, Serverless Computing, CI/CD, Data Infrastructure, Amazon Web Services, Data Architecture, AWS Identity and Access Management (IAM), AWS CloudFormation, Infrastructure Architecture, Security Controls, Cloud Applications, Amazon CloudWatch, Terraform

      4.6
      Rating, 4.6 out of 5 stars
      ·
      84 reviews

      Beginner · Course · 1 - 4 Weeks

    • Duke University

      Applied Python Data Engineering

      Skills you'll gain: Data Visualization Software, PySpark, Data Visualization, Snowflake Schema, Data Storytelling, Site Reliability Engineering, Docker (Software), Databricks, Containerization, Interactive Data Visualization, Plotly, Data Pipelines, Kubernetes, Matplotlib, Apache Spark, Dashboard, Virtualization, MLOps (Machine Learning Operations), Devops Tools, Apache Hadoop

      3.8
      Rating, 3.8 out of 5 stars
      ·
      94 reviews

      Intermediate · Specialization · 1 - 3 Months

    • IBM

      Python Project for Data Engineering

      Skills you'll gain: Web Scraping, Data Transformation, Extract, Transform, Load, Data Manipulation, SQL, Integrated Development Environments, Data Processing, Databases, Application Programming Interface (API), Code Review, Restful API, Python Programming, Unit Testing, Style Guides

      4.6
      Rating, 4.6 out of 5 stars
      ·
      760 reviews

      Intermediate · Course · 1 - 4 Weeks

    • IBM

      IBM Data Warehouse Engineer

      Skills you'll gain: Data Warehousing, SQL, Extract, Transform, Load, Apache Airflow, Linux Commands, Database Design, IBM Cognos Analytics, MySQL, Data Pipelines, Apache Kafka, Database Management, Bash (Scripting Language), Shell Script, Database Architecture and Administration, Data Store, IBM DB2, Relational Databases, Microsoft SQL Servers, Dashboard, File Management

      4.7
      Rating, 4.7 out of 5 stars
      ·
      6K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    Data Engineering learners also search

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    1234…721

    In summary, here are 10 of our most popular data engineering courses

    • IBM Data Engineering: IBM
    • DeepLearning.AI Data Engineering: DeepLearning.AI
    • Data Engineering Foundations: IBM
    • Introduction to Data Engineering: IBM
    • Data Engineering, Big Data, and Machine Learning on GCP: Google Cloud
    • Introduction to Data Engineering: DeepLearning.AI
    • Python, Bash and SQL Essentials for Data Engineering: Duke University
    • Introduction to Modern Data Engineering with Snowflake: Snowflake
    • Data Engineering on AWS - Foundations: Amazon Web Services
    • Applied Python Data Engineering: Duke University

    Skills you can learn in Software Development

    Programming Language (34)
    Google (25)
    Computer Program (21)
    Software Testing (21)
    Web (19)
    Google Cloud Platform (18)
    Application Programming Interfaces (17)
    Data Structure (16)
    Problem Solving (14)
    Object-oriented Programming (13)
    Kubernetes (10)
    List & Label (10)

    Frequently Asked Questions about Data Engineering

    Coursera’s Data Engineering courses offer learners a deep dive into the technical skills required to design, build, and manage data infrastructure:

    • Techniques for designing data models and databases.
    • Skills in data warehousing and data lake construction and management.
    • Proficiency in big data technologies such as Hadoop, Spark, and Apache Kafka.
    • Best practices for data integration, ETL (extract, transform, load) processes, and pipeline construction.
    • Understanding of data quality management and data governance.
    • Application of automation and monitoring tools to maintain data systems.‎

    Data Engineering courses on Coursera cater to learners of all backgrounds:

    • Beginners can start with introductory courses that teach the basics of data infrastructure and SQL.
    • Those with some technical experience can focus on advanced topics like big data processing or cloud data services.
    • Advanced learners can explore specialized areas such as machine learning data pipelines or real-time data processing.‎

    Learners who complete Data Engineering courses on Coursera can earn credentials that may enhance their professional profiles:

    • Professional certificates that demonstrate a foundational understanding and practical skills in data engineering.
    • Specializations that focus on detailed aspects of data engineering, such as performance tuning, scalability, or security.
    • Certificates that can potentially be recognized by technology companies and other employers as evidence of expertise in data engineering.‎

    Skills in data engineering can lead to a variety of roles within the technology and analytics sectors:

    • Data Engineer, responsible for designing and managing scalable data systems.
    • Database Administrator, maintaining and optimizing database performance.
    • Cloud Solutions Architect, focusing on cloud storage and data services.
    • Data Architect, shaping strategic data practices and architectures.
    • Machine Learning Engineer, preparing data infrastructure for predictive models.‎

    Yes, Coursera offers a variety of free courses across many topics, including data engineering. While you can access most course materials for free by auditing the courses, this does not include graded assignments or a completion certificate. For those looking to obtain a certificate to showcase their learning or enhance their professional profile, Coursera provides the option to purchase the course. Additionally, Coursera offers free trials or financial aid to learners who qualify, making certifications more accessible to everyone.‎

    This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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