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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


  • I

    IBM

    Introduction to Data Engineering

    Skills you'll gain: Extract, Transform, Load, Data Store, Data Architecture, Data Pipelines, Big Data, Data Storage Technologies, Data Storage, Relational Databases, Data Infrastructure, Data Integration, Apache Hadoop, Data Warehousing, Databases, Data Lakes, SQL, Data Governance, Database Design, Apache Spark, NoSQL, Data Science

    ★ 4.7 (3.6K) · Beginner · Course · 1 - 4 Weeks

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • I

    IBM

    IBM Data Engineering

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

    ★ 4.6 (62K) · Beginner · Professional Certificate · 3 - 6 Months

    Status: Free Trial
    Free Trial
    Category: AI skills
    AI skills
    Category: Build toward a degree
    Build toward a degree
  • S

    Snowflake

    Snowflake Data Engineering

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

    ★ 4.8 (354) · Beginner · Professional Certificate · 1 - 3 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • I

    IBM

    Data Engineering Foundations

    Skills you'll gain: Extract, Transform, Load, Web Scraping, Database Design, SQL, IBM DB2, Database Management, Data Store, Relational Databases, Database Systems, Data Architecture, Data Pipelines, Databases, Big Data, Data Storage Technologies, Unit Testing, Data Storage, Database Development, Python Programming, NumPy, Data Analysis

    ★ 4.6 (60K) · Beginner · Specialization · 3 - 6 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • 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, Command-Line Interface, Python Programming, Big Data, Data Science

    ★ 4.5 (478) · Beginner · Specialization · 3 - 6 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • P

    Pragmatic AI Labs

    Enterprise AI and Data Engineering with Databricks

    Skills you'll gain: Prompt Engineering, MLOps (Machine Learning Operations), Data Pipelines, Databricks, Generative AI, Data Lakes, Generative AI Agents, Data Governance, Data Architecture, AI Enablement, Data Modeling, Data Management, Data Processing, Data Strategy, Data Quality, Scala Programming, SQL, Python Programming, Data Visualization, Data Literacy

    Beginner · Specialization · 3 - 6 Months

    Category: New
    New
    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered

What brings you to Coursera today?

  • M

    Meta

    Meta Database Engineer

    Skills you'll gain: MySQL, Database Software, Database Management, Database Theory, Data Warehousing, Interactive Data Visualization, Dashboard, Database Administration, Data Visualization Software, Star Schema, Dashboard Creation, Linux Commands, Unix, Data Integrity, Unit Testing, Algorithms, Analytics, Database Architecture and Administration, Software Versioning, Command-Line Interface

    ★ 4.6 (7.7K) · Beginner · Professional Certificate · 3 - 6 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • A

    Amazon Web Services

    Data Engineering on AWS - Foundations

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

    ★ 4.6 (275) · Beginner · Course · 1 - 4 Weeks

    Category: Free
    Free
    Category: Credit offered
    Credit offered
  • C

    Coursera

    Data Modeling & Warehousing Fundamentals in Data Engineering

    Skills you'll gain: Data Warehousing, Star Schema, Data Modeling, Database Design, Extract, Transform, Load, Database Development, Data Integration, Data Infrastructure, Database Architecture and Administration, Database Software, Relational Databases, Database Management, Business Intelligence, Database Theory, Performance Tuning, PostgreSQL, SQL

    Beginner · Course · 1 - 3 Months

    Category: New
    New
    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • L

    LearnKartS

    AWS Certified Data Engineer Associate Exam Prep

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

    ★ 4.3 (8) · Beginner · Specialization · 1 - 3 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • K

    KodeKloud

    Data Engineering Essentials

    Skills you'll gain: MLOps (Machine Learning Operations), Apache Kafka, Apache Airflow, Apache Spark, Extract, Transform, Load, Data Lakes, Data Pipelines, Distributed Computing, Real Time Data, DevOps, Data Processing, Feature Engineering, CI/CD, Pandas (Python Package), Continuous Integration

    Beginner · Course · 1 - 4 Weeks

    Category: New
    New
    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • G

    Google Cloud

    Introduction to Data Engineering on Google Cloud

    Skills you'll gain: Metadata Management, Data Sharing, Data Pipelines, Extract, Transform, Load, Google Cloud Platform, Data Migration, Data Warehousing, Data Infrastructure, Apache Airflow, Data Processing, Big Data, Data Import/Export, Data Storage, Data Management, IT Automation, Cloud Storage, Apache Spark, Automation

    ★ 5 (6) · Beginner · Course · 1 - 3 Months

    Category: Credit offered
    Credit offered
1234…565

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, Bash and SQL Essentials for Data Engineering: Duke University
  • Enterprise AI and Data Engineering with Databricks: Pragmatic AI Labs
  • Meta Database Engineer: Meta
  • Data Engineering on AWS - Foundations: Amazon Web Services
  • Data Modeling & Warehousing Fundamentals in Data Engineering: Coursera
  • AWS Certified Data Engineer Associate Exam Prep: LearnKartS

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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