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    Results for "data engineering"

    • Status: Free
      Free

      Duke University

      Introduction to Genetics and Evolution

      Skills you'll gain: Life Sciences, Molecular Biology, Biology, Biostatistics, Bioinformatics, Environment, Laboratory Research, Taxonomy, Scientific Methods, Experimentation, Mathematical Modeling

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.7K reviews

      Mixed · Course · 1 - 3 Months

    • Tableau Learning Partner

      Data Visualization with Tableau

      Skills you'll gain: Data Visualization Software, Interactive Data Visualization, Tableau Software, Data Presentation, Tree Maps, Dashboard, Heat Maps, Geospatial Mapping, Data Storytelling, Data Manipulation, Data Mapping, Business Analytics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      118 reviews

      Beginner · Course · 1 - 3 Months

    • Google Cloud

      Google Cloud Fundamentals: Core Infrastructure

      Skills you'll gain: Google Cloud Platform, Cloud Infrastructure, Prompt Engineering, Kubernetes, Containerization, Cloud Storage, Cloud Services, Identity and Access Management, Application Deployment, Virtual Machines, Cloud Computing, Application Development, Generative AI, Network Infrastructure, NoSQL, Scalability

      4.7
      Rating, 4.7 out of 5 stars
      ·
      49K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free
      Free

      Nanjing University

      Data Processing Using Python

      Skills you'll gain: Data Processing, Data Mining, Data Structures, Data Presentation, Object Oriented Programming (OOP), Web Scraping, Data Analysis, Python Programming, Pandas (Python Package), NumPy, Data Visualization, Data Import/Export, Data Manipulation, Matplotlib, User Interface (UI) Design

      4.1
      Rating, 4.1 out of 5 stars
      ·
      372 reviews

      Beginner · Course · 1 - 3 Months

    • DeepLearning.AI

      Machine Learning in Production

      Skills you'll gain: MLOps (Machine Learning Operations), Application Deployment, Continuous Deployment, Software Development Life Cycle, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Applied Machine Learning, Data Validation, Feature Engineering, Data Quality, Debugging, Continuous Monitoring, Data Pipelines

      4.8
      Rating, 4.8 out of 5 stars
      ·
      3.2K reviews

      Intermediate · Course · 1 - 4 Weeks

    • IBM

      Introduction to Artificial Intelligence (AI)

      Skills you'll gain: Large Language Modeling, Artificial Intelligence, Generative AI, Data Ethics, Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Deep Learning, Artificial Neural Networks, Governance, Prompt Engineering, Machine Learning, Automation, Digital Transformation, Business Transformation, Business Technologies, Ethical Standards And Conduct, Computer Vision, Emerging Technologies, Natural Language Processing

      4.7
      Rating, 4.7 out of 5 stars
      ·
      19K reviews

      Beginner · Course · 1 - 4 Weeks

    • Google Cloud

      Preparing for Google Cloud Certification: Machine Learning Engineer

      Skills you'll gain: Feature Engineering, MLOps (Machine Learning Operations), Prompt Engineering, Google Cloud Platform, Generative AI, Tensorflow, Keras (Neural Network Library), Apache Airflow, Cloud Infrastructure, CI/CD, Artificial Intelligence and Machine Learning (AI/ML), Data Pipelines, Dataflow, Systems Design, Cloud Platforms, Data Management, Data Governance, Hybrid Cloud Computing, Workflow Management, Application Deployment

      4.4
      Rating, 4.4 out of 5 stars
      ·
      4.8K reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • Coursera Project Network

      Python for Data Analysis: Pandas & NumPy

      Skills you'll gain: Pandas (Python Package), NumPy, Data Analysis, Data Science, Python Programming, Data Structures, Data Manipulation, Computer Programming

      4.5
      Rating, 4.5 out of 5 stars
      ·
      334 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • Status: Free
      Free

      Technical University of Denmark (DTU)

      Global Environmental Management

      Skills you'll gain: Water Resources, Energy and Utilities, Environmental Engineering, Natural Resource Management, Civil Engineering, Environment, Environmental Management Systems, Land Management, Environmental Resource Management, Sanitation, Environmental Monitoring, Cultural Responsiveness, Waste Minimization

      4.7
      Rating, 4.7 out of 5 stars
      ·
      2.2K reviews

      Intermediate · Course · 1 - 3 Months

    • IBM

      Statistics for Data Science with Python

      Skills you'll gain: Descriptive Statistics, Statistical Analysis, Data Analysis, Probability Distribution, Statistics, Data Visualization, Statistical Hypothesis Testing, Regression Analysis, Probability & Statistics, Data Science, Matplotlib, Exploratory Data Analysis, Probability, Correlation Analysis, Pandas (Python Package), Jupyter

      4.5
      Rating, 4.5 out of 5 stars
      ·
      433 reviews

      Mixed · Course · 1 - 3 Months

    • Status: New
      New

      University of Michigan

      AI for Mechanical Engineers

      Skills you'll gain: Machine Learning Methods, Artificial Intelligence and Machine Learning (AI/ML), Precision Medicine, Generative AI, Machine Learning, Artificial Intelligence, Machine Learning Algorithms, Energy and Utilities, Image Analysis, Computer-Aided Design, Design Thinking, Technical Design, Computer Vision, Deep Learning, Medical Imaging, Statistical Machine Learning, Reinforcement Learning, Electric Power Systems, Bioinformatics, Artificial Neural Networks

      4.2
      Rating, 4.2 out of 5 stars
      ·
      38 reviews

      Intermediate · Specialization · 1 - 3 Months

    • IBM

      Data Visualization with R

      Skills you'll gain: Data Storytelling, Interactive Data Visualization, Data Visualization Software, Dashboard, Ggplot2, Plot (Graphics), Shiny (R Package), R Programming, Leaflet (Software), Graphing, Scatter Plots, Box Plots, Spatial Data Analysis, Histogram, UI Components, User Interface (UI)

      4.6
      Rating, 4.6 out of 5 stars
      ·
      260 reviews

      Beginner · Course · 1 - 4 Weeks

    Searches related to data engineering

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    1…343536…731

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

    • Introduction to Genetics and Evolution: Duke University
    • Data Visualization with Tableau: Tableau Learning Partner
    • Google Cloud Fundamentals: Core Infrastructure: Google Cloud
    • Data Processing Using Python: Nanjing University
    • Machine Learning in Production: DeepLearning.AI
    • Introduction to Artificial Intelligence (AI): IBM
    • Preparing for Google Cloud Certification: Machine Learning Engineer: Google Cloud
    • Python for Data Analysis: Pandas & NumPy: Coursera Project Network
    • Global Environmental Management: Technical University of Denmark (DTU)
    • Statistics 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

    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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