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Data Engineering Courses

Data engineering courses can help you learn data modeling, ETL (extract, transform, load) processes, and data warehousing techniques. You can build skills in data pipeline construction, database management, and ensuring data quality and integrity. Many courses introduce tools like Apache Spark, Hadoop, and SQL, that support processing large datasets and optimizing data workflows. You’ll also explore cloud platforms such as AWS and Azure, which facilitate scalable data solutions and enhance your ability to manage data in various environments.


Popular Data Engineering Courses and Certifications


  • Status: Free Trial
    Free Trial
    I

    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, Data Science

    4.7
    Rating, 4.7 out of 5 stars
    ·
    3.5K reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    Status: AI skills
    AI skills
    I

    IBM

    IBM Data Engineering

    Skills you'll gain: NoSQL, Apache Spark, Data Warehousing, Database Administration, Apache Hadoop, Extract, Transform, Load, Apache Airflow, Web Scraping, Relational Databases, Linux Commands, Database Design, SQL, IBM Cognos Analytics, Data Store, Generative AI, Professional Networking, Data Import/Export, Python Programming, Data Analysis, Data Science

    Build toward a degree

    4.6
    Rating, 4.6 out of 5 stars
    ·
    62K reviews

    Beginner · Professional Certificate · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    S

    Snowflake

    Snowflake Data Engineering

    Skills you'll gain: Data Engineering, Data Pipelines, Database Management, Data Manipulation, Databases, Data Transformation, Extract, Transform, Load, Data Warehousing, Change Control, DevOps, Cloud Development, SQL, Data Integration, CI/CD, Application Development, Artificial Intelligence and Machine Learning (AI/ML), Role-Based Access Control (RBAC), Software Development Tools, Stored Procedure, Data Analysis

    4.8
    Rating, 4.8 out of 5 stars
    ·
    312 reviews

    Beginner · Professional Certificate · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    I

    IBM

    Data Engineering Foundations

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

    4.6
    Rating, 4.6 out of 5 stars
    ·
    59K reviews

    Beginner · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    I

    IBM

    Python for Data Science, AI & Development

    Skills you'll gain: Data Import/Export, Programming Principles, Web Scraping, File I/O, Python Programming, Jupyter, Data Structures, Pandas (Python Package), Data Manipulation, JSON, Computer Programming, Restful API, NumPy, Object Oriented Programming (OOP), Application Programming Interface (API), Automation, Data Analysis

    4.6
    Rating, 4.6 out of 5 stars
    ·
    43K reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free
    Free
    A

    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
    ·
    240 reviews

    Beginner · Course · 1 - 4 Weeks

What brings you to Coursera today?

  • Status: Free Trial
    Free Trial
    D

    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, Cloud Engineering, Python Programming, Big Data, Data Science

    4.5
    Rating, 4.5 out of 5 stars
    ·
    464 reviews

    Beginner · Specialization · 3 - 6 Months

  • Next level skills. New Year savings.

    Save on Coursera Plus
  • Status: Free Trial
    Free Trial
    M

    Meta

    Meta Database Engineer

    Skills you'll gain: MySQL, Database Management, Database Administration, Data Warehousing, Linux Commands, Data Integrity, Unit Testing, Algorithms, Software Versioning, Command-Line Interface, Software Visualization, Linux, Pseudocode, Query Languages, Collaborative Software, Django (Web Framework), Database Architecture and Administration, Programming Principles, Computational Thinking, Test Driven Development (TDD)

    4.6
    Rating, 4.6 out of 5 stars
    ·
    7.6K reviews

    Beginner · Professional Certificate · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    I

    IBM

    Generative AI: Prompt Engineering Basics

    Skills you'll gain: Prompt Engineering, Prompt Patterns, ChatGPT, Generative AI, AI Workflows, Context Management, Decision Making

    4.8
    Rating, 4.8 out of 5 stars
    ·
    7.7K reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    I

    IBM

    Databases and SQL for Data Science with Python

    Skills you'll gain: SQL, Relational Databases, Stored Procedure, Databases, Query Languages, Jupyter, Data Manipulation, Data Analysis, Pandas (Python Package), Transaction Processing, Python Programming

    4.7
    Rating, 4.7 out of 5 stars
    ·
    23K reviews

    Beginner · Course · 1 - 3 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    L

    LearnKartS

    AWS Certified Data Engineer Associate Exam Prep

    Skills you'll gain: AWS Kinesis, AWS SageMaker, AWS CloudFormation, Data Quality, Docker (Software), Data Pipelines, AWS Identity and Access Management (IAM), Data Security, Database Systems, Databases, Cloud-Native Computing, Version Control, Apache Spark, Cloud Engineering, Apache Airflow, Data Modeling, Cloud Security, Data Storage, Cloud Storage, Data Processing

    4.1
    Rating, 4.1 out of 5 stars
    ·
    7 reviews

    Beginner · Specialization · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    I

    IBM

    IBM Data Warehouse Engineer

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

    4.7
    Rating, 4.7 out of 5 stars
    ·
    6.7K reviews

    Beginner · Professional Certificate · 3 - 6 Months

What brings you to Coursera today?

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

  • Introduction to Data Engineering: IBM
  • IBM Data Engineering: IBM
  • Snowflake Data Engineering: Snowflake
  • Data Engineering Foundations: IBM
  • Python for Data Science, AI & Development: IBM
  • Data Engineering on AWS - Foundations: Amazon Web Services
  • Python, Bash and SQL Essentials for Data Engineering: Duke University
  • Meta Database Engineer: Meta
  • Generative AI: Prompt Engineering Basics: IBM
  • Databases and SQL for Data Science with Python: IBM

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

Data engineering is the practice of designing, building, and maintaining the systems and architecture that enable organizations to collect, store, and analyze data effectively. It plays a crucial role in today's data-driven world, where businesses rely on data to make informed decisions, optimize operations, and enhance customer experiences. By ensuring that data is accessible, reliable, and secure, data engineers empower organizations to harness the full potential of their data assets.‎

In the field of data engineering, a variety of job roles are available, including Data Engineer, Data Architect, ETL Developer, and Data Warehouse Engineer. These positions often involve working with large datasets, developing data pipelines, and collaborating with data scientists and analysts to ensure that data is structured and available for analysis. With the growing demand for data professionals, opportunities in this field are expanding across industries such as finance, healthcare, technology, and retail.‎

To pursue a career in data engineering, you should focus on developing a range of technical skills. Key competencies include proficiency in programming languages such as Python and SQL, knowledge of data warehousing solutions, and familiarity with cloud platforms like AWS or Google Cloud. Additionally, understanding data modeling, ETL processes, and big data technologies like Hadoop and Spark can be beneficial. Soft skills such as problem-solving and effective communication are also important for collaborating with cross-functional teams.‎

There are several excellent online courses available for those interested in data engineering. Notable options include the DeepLearning.AI Data Engineering Professional Certificate and the IBM Data Engineering Professional Certificate. These programs provide a comprehensive curriculum that covers essential skills and tools needed in the field, making them great choices for learners at various stages of their careers.‎

Yes. You can start learning data engineering on Coursera for free in two ways:

  1. Preview the first module of many data engineering courses at no cost. This includes video lessons, readings, graded assignments, and Coursera Coach (where available).
  2. Start a 7-day free trial for Specializations or Coursera Plus. This gives you full access to all course content across eligible programs within the timeframe of your trial.

If you want to keep learning, earn a certificate in data engineering, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.‎

To learn data engineering effectively, start by identifying your current skill level and areas for improvement. Begin with foundational courses that cover programming and database management. Gradually progress to more specialized topics such as data warehousing and cloud technologies. Engage in hands-on projects to apply what you learn, and consider joining online communities or forums to connect with other learners and professionals in the field.‎

Data engineering courses typically cover a range of topics, including data modeling, ETL (Extract, Transform, Load) processes, data warehousing, and big data technologies. You may also explore cloud computing platforms, data pipeline design, and data governance. Courses often include practical exercises and projects to help reinforce your understanding and application of these concepts in real-world scenarios.‎

For training and upskilling employees in data engineering, programs like the IBM Data Warehouse Engineer Professional Certificate and the Snowflake Data Engineering Professional Certificate are excellent choices. These courses are designed to equip professionals with the necessary skills to manage and analyze data effectively, making them suitable for organizations looking to enhance their workforce's capabilities in data engineering.‎

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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