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    • Data Engineering

    Data Engineering Courses

    Data engineering courses can help you learn how to design, build, and maintain data systems and pipelines that support analytics, machine learning, and business intelligence.

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    Find the Best Data Engineering Course for Your Goals

    • Status: Free Trial
      Free Trial
      I

      IBM

      Data Science Methodology

      Skills you'll gain: Jupyter, Peer Review, Data Modeling, Data Science, Data Cleansing, Business Analysis, Data Mining, Predictive Modeling, Data Quality, Data Storytelling, Analytical Skills, User Feedback, Decision Tree Learning, Stakeholder Engagement

      4.6
      Rating, 4.6 out of 5 stars
      ·
      21K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      I

      IBM

      Introduction to Data Science

      Skills you'll gain: SQL, Jupyter, Data Literacy, Data Mining, Peer Review, Data Modeling, Databases, Stored Procedure, Relational Databases, Database Design, Query Languages, Data Science, Database Management, Big Data, Data Cleansing, Data Visualization Software, GitHub, Business Analysis, Cloud Computing, Data Analysis

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      99K reviews

      Beginner · Specialization · 3 - 6 Months

    • D

      Duke University

      Data Science Math Skills

      Skills you'll gain: Probability, Bayesian Statistics, General Mathematics, Calculus, Graphing, Statistics, Data Science, Data Analysis, Plot (Graphics), Algebra, Geometry, Arithmetic, Derivatives

      4.5
      Rating, 4.5 out of 5 stars
      ·
      13K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Michigan

      Python Data Structures

      Skills you'll gain: Data Structures, Python Programming, Programming Principles, Data Import/Export, Data Manipulation, Development Environment, File Management

      4.9
      Rating, 4.9 out of 5 stars
      ·
      97K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Data Science: Foundations using R

      Skills you'll gain: Rmarkdown, Exploratory Data Analysis, Version Control, Statistical Analysis, R Programming, Data Manipulation, Data Cleansing, Data Science, Data Wrangling, Data Visualization, Plot (Graphics), Statistical Programming, Ggplot2, Big Data, Git (Version Control System), Data Integration, Knitr, Data Analysis, Data Sharing, Statistical Reporting

      4.6
      Rating, 4.6 out of 5 stars
      ·
      48K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      U

      University of Colorado Boulder

      Embedding Sensors and Motors

      Skills you'll gain: Control Systems, Process Control, Embedded Systems, Electronic Systems, Machine Controls, Embedded Software, Programmable Logic Controllers, Electronics, Hardware Design, Automation Engineering, Laboratory Experience, Electronics Engineering, Electrical Engineering, Three-Phase, Power Electronics, Manufacturing Processes, Electrical Equipment, Manufacturing and Production, Electronic Components, Electrical Systems

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2.8K reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      U

      University of Michigan

      Introduction to Data Science in Python

      Skills you'll gain: Pandas (Python Package), Jupyter, NumPy, Data Manipulation, Data Science, Data Structures, Data Analysis, Statistical Analysis, Pivot Tables And Charts, Data Cleansing, Data Import/Export, Probability & Statistics, Python Programming, Programming Principles

      4.5
      Rating, 4.5 out of 5 stars
      ·
      27K reviews

      Intermediate · Course · 1 - 4 Weeks

    • U

      UNSW Sydney (The University of New South Wales)

      Introduction to Systems Engineering

      Skills you'll gain: Systems Engineering, Conceptual Design, Systems Design, Requirements Analysis, Systems Development Life Cycle, Requirements Elicitation, Systems Architecture, Systems Integration, Engineering Design Process, System Design and Implementation, Concept Of Operations, Configuration Management, Prototyping, System Requirements, Design Reviews, Verification And Validation

      4.7
      Rating, 4.7 out of 5 stars
      ·
      807 reviews

      Mixed · Course · 1 - 3 Months

    • G

      Georgia Institute of Technology

      Applications in Engineering Mechanics

      Skills you'll gain: Structural Analysis, Structural Engineering, Engineering Analysis, Mechanical Engineering, Mechanics, Engineering

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.2K reviews

      Mixed · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of California San Diego

      Introduction to Big Data

      Skills you'll gain: Big Data, Apache Hadoop, Scalability, Data Processing, Data Science, Distributed Computing, Unstructured Data, Data Analysis, Real Time Data, Data Storage

      4.6
      Rating, 4.6 out of 5 stars
      ·
      11K reviews

      Mixed · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      The Data Scientist’s Toolbox

      Skills you'll gain: Rmarkdown, Version Control, Data Science, Big Data, Git (Version Control System), GitHub, Data Analysis, R Programming, Statistical Programming, Development Environment, Integrated Development Environments, Software Installation

      4.6
      Rating, 4.6 out of 5 stars
      ·
      34K reviews

      Mixed · Course · 1 - 4 Weeks

    • É

      École Nationale des Ponts et Chaussées

      Mastering bitumen for better roads and innovative applications

      Skills you'll gain: Environmental Engineering, Environment Health And Safety, Civil Engineering, Transportation Operations, Construction, Market Dynamics, Transportation, Supply Chain, and Logistics, Material Handling, Chemical Engineering, Product Testing, Technical Standard, Performance Testing, Manufacturing Processes, Laboratory Testing

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.3K reviews

      Intermediate · Course · 1 - 4 Weeks

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    1…91011…738

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

    • Data Science Methodology: IBM
    • Introduction to Data Science: IBM
    • Data Science Math Skills: Duke University
    • Python Data Structures: University of Michigan
    • Data Science: Foundations using R: Johns Hopkins University
    • Embedding Sensors and Motors: University of Colorado Boulder
    • Introduction to Data Science in Python: University of Michigan
    • Introduction to Systems Engineering: UNSW Sydney (The University of New South Wales)
    • Applications in Engineering Mechanics: Georgia Institute of Technology
    • Introduction to Big Data: University of California San Diego

    Why Learn Data Engineering?

    Data engineering focuses on preparing and structuring data so it can be accessed and analyzed efficiently. It involves working with databases, cloud platforms, ETL processes, and big data tools. Learning data engineering can help you manage complex data workflows, ensure data quality, and support data-driven decision-making in tech-driven organizations.

    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

    Top courses include the Data Engineering Foundations from IBM, Introduction to Data Engineering with DeepLearning.AI, and Data Engineering, Big Data, and Machine Learning on GCP from Google Cloud. These programs teach how to design, build, and manage data pipelines using modern tools and cloud platforms.‎

    Yes. Many data engineering courses offer a free audit option, allowing learners to access video lessons and reading materials at no cost. To complete assignments or earn a certificate, you’ll need to upgrade or apply for financial aid.‎

    You’ll learn how to build and manage data processing systems, work with data warehouses and data lakes, use tools like SQL, Apache Spark, and Airflow, and understand how to design reliable and scalable data pipelines.‎

    Not necessarily. Many beginner-friendly courses start with the fundamentals and explain data engineering concepts clearly. However, some familiarity with programming and data analysis can be helpful as you progress to more advanced topics.‎

    Yes. Data engineering is a fast-growing field with high demand in tech, finance, healthcare, and many other industries. Coursera’s data engineering courses can help you build job-ready skills, prepare for certification exams, and earn certificates that showcase your expertise to employers.‎

    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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