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  • Data Engineering

Results for "data engineering"


  • I

    IBM

    Introduction to Data Engineering

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

    Coursera Plus

    Included with Coursera Plus

    4.7
    Rating, 4.7 out of 5 stars
    ·
    3.7K reviews

    Beginner · Course · 1 - 4 Weeks

  • D
    A

    Multiple educators

    DeepLearning.AI Data Engineering

    Skills you'll gain: Data Store, Apache Airflow, Data Modeling, Data Pipelines, Data Storage, Data Storage Technologies, Data Architecture, Requirements Analysis, Data Processing, Data Warehousing, Query Languages, Data Preprocessing, Apache Hadoop, Requirements Elicitation, Vector Databases, Extract, Transform, Load, Data Lakes, Data Integration, Infrastructure as Code (IaC), Data Management

    4.7
    Rating, 4.7 out of 5 stars
    ·
    606 reviews

    Intermediate · Professional Certificate · 3 - 6 Months

  • Status: AI skills
    AI skills
    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, Linux Commands, SQL, IBM Cognos Analytics, Data Store, Generative AI, Professional Networking, Data Import/Export, Python Programming, Data Analysis, Data Science

    Coursera Plus

    Included with Coursera Plus

    Build toward a degree

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

    Beginner · Professional Certificate · 3 - 6 Months

  • I

    IBM

    Data Engineering Foundations

    Skills you'll gain: Extract, Transform, Load, Web Scraping, Database Design, SQL, IBM DB2, Database Management, Data Store, Data Architecture, Relational Databases, Database Systems, Apache Hadoop, Databases, Big Data, Unit Testing, Database Development, Data Storage, Apache Spark, Data Import/Export, Python Programming, NumPy

    Coursera Plus

    Included with Coursera Plus

    4.6
    Rating, 4.6 out of 5 stars
    ·
    60K reviews

    Beginner · Specialization · 3 - 6 Months

  • S

    Snowflake

    Snowflake Data Engineering

    Skills you'll gain: Data Engineering, Data Pipelines, Database Management, Data Manipulation, Databases, Data Store, 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), Data Analysis

    Coursera Plus

    Included with Coursera Plus

    4.8
    Rating, 4.8 out of 5 stars
    ·
    370 reviews

    Beginner · Professional Certificate · 1 - 3 Months

  • Status: New
    New
    C

    Coursera

    Open source Data Engineering with Spark, dbt & Airflow

    Skills you'll gain: Data Warehousing, Data Flow Diagrams (DFDs), Data Modeling, Data Pipelines, Ansible, Cloud Security, Diagram Design, Data Validation, Database Design, Apache Airflow, Star Schema, Snowflake Schema, Interviewing Skills, Apache Spark, PySpark, CI/CD, Docker (Software), SQL, Workflow Management, Git (Version Control System)

    Coursera Plus

    Included with Coursera Plus

    Intermediate · Professional Certificate · 3 - 6 Months

  • D

    DeepLearning.AI

    Introduction to Data Engineering

    Skills you'll gain: Data Pipelines, Data Architecture, Requirements Analysis, Requirements Elicitation, Amazon Web Services, Data Infrastructure, Enterprise Architecture, Data Processing, System Requirements, Performance Tuning, Cloud Computing, Data Transformation, Scalability

    4.8
    Rating, 4.8 out of 5 stars
    ·
    496 reviews

    Intermediate · Course · 1 - 4 Weeks

  • I

    IBM

    Python Project for Data Engineering

    Skills you'll gain: Extract, Transform, Load, Web Scraping, Database Management, Databases, Unit Testing, Data Transformation, Data Access, Data Capture, Package and Software Management, Application Programming Interface (API), Data Integration, Data Wrangling, Integrated Development Environments, Data Pipelines, Maintainability, Python Programming, Programming Principles, Style Guides

    Coursera Plus

    Included with Coursera Plus

    4.6
    Rating, 4.6 out of 5 stars
    ·
    855 reviews

    Intermediate · Course · 1 - 4 Weeks

  • 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

    Coursera Plus

    Included with Coursera Plus

    4.5
    Rating, 4.5 out of 5 stars
    ·
    484 reviews

    Beginner · Specialization · 3 - 6 Months

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  • G

    Google Cloud

    Data Engineering, Big Data, and Machine Learning on GCP

    Skills you'll gain: Dashboard Creation, Model Deployment, Feature Engineering, PySpark, Data Import/Export, Big Data, Apache Spark, Data Governance, Apache Hadoop, Dashboard, Apache Kafka, Data Store, Cloud Services, Cloud Deployment, Data Access, Cloud API, Data Architecture, Data Quality, Data Cleansing, Machine Learning Methods

    Coursera Plus

    Included with Coursera Plus

    4.6
    Rating, 4.6 out of 5 stars
    ·
    4.4K reviews

    Intermediate · Specialization · 3 - 6 Months

  • 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

    Coursera Plus

    Included with Coursera Plus

    4.6
    Rating, 4.6 out of 5 stars
    ·
    7.7K reviews

    Beginner · Professional Certificate · 3 - 6 Months

  • 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
    Rating, 4.6 out of 5 stars
    ·
    285 reviews

    Beginner · Course · 1 - 4 Weeks

1234…834

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

  • Introduction to Data Engineering: IBM
  • DeepLearning.AI Data Engineering: DeepLearning.AI
  • IBM Data Engineering: IBM
  • Data Engineering Foundations: IBM
  • Snowflake Data Engineering: Snowflake
  • Open source Data Engineering with Spark, dbt & Airflow: Coursera
  • Introduction to Data Engineering: DeepLearning.AI
  • Python Project for Data Engineering: IBM
  • Python, Bash and SQL Essentials for Data Engineering: Duke University
  • Data Engineering, Big Data, and Machine Learning on GCP: Google Cloud

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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