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    • Data Engineering

    Data Engineering Courses Online

    Learn data engineering for building data pipelines and infrastructure. Understand data integration, storage, and processing technologies.

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    Explore the Data Engineering Course Catalog

    • D

      DeepLearning.AI

      Natural Language Processing

      Skills you'll gain: Natural Language Processing, Supervised Learning, Markov Model, Text Mining, Dimensionality Reduction, Artificial Intelligence and Machine Learning (AI/ML), Artificial Neural Networks, PyTorch (Machine Learning Library), Deep Learning, Tensorflow, Machine Learning Methods, Data Processing, Feature Engineering, Machine Learning Algorithms, Artificial Intelligence, Algorithms, Keras (Neural Network Library), Linear Algebra, Data Cleansing, Probability & Statistics

      4.6
      Rating, 4.6 out of 5 stars
      ·
      6.1K reviews

      Intermediate · Specialization · 3 - 6 Months

    • I

      IBM

      IBM Introduction to Machine Learning

      Skills you'll gain: Exploratory Data Analysis, Feature Engineering, Unsupervised Learning, Supervised Learning, Dimensionality Reduction, Regression Analysis, Statistical Inference, Machine Learning Algorithms, Data Processing, Machine Learning, Data Access, Anomaly Detection, Classification And Regression Tree (CART), Scikit Learn (Machine Learning Library), Statistical Analysis, Data Analysis, Applied Machine Learning, Data Cleansing, Data Manipulation, Predictive Modeling

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2.9K reviews

      Intermediate · Specialization · 3 - 6 Months

    • T

      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
      ·
      117 reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of California, Davis

      Geographic Information Systems (GIS)

      Skills you'll gain: ArcGIS, GIS Software, Spatial Data Analysis, Spatial Analysis, Data Storytelling, Geographic Information Systems, Data Presentation, Data Sharing, Geospatial Mapping, Public Health, Land Management, Heat Maps, Metadata Management, Data Quality, Community Health, Data Mapping, Data Visualization Software, File Management, Network Analysis, Data Modeling

      4.8
      Rating, 4.8 out of 5 stars
      ·
      6.3K reviews

      Beginner · Specialization · 3 - 6 Months

    • R

      Rice University

      Introduction to Electricity and Magnetism

      Skills you'll gain: Basic Electrical Systems, Electrical Engineering, Torque (Physics), Physics, Electrical Systems, Engineering Analysis, Electronic Components, Mechanics, Electronic Systems, Mathematical Modeling, Applied Mathematics, Engineering Calculations, Calculus, Advanced Mathematics, Trigonometry, Linear Algebra

      4.7
      Rating, 4.7 out of 5 stars
      ·
      208 reviews

      Intermediate · Specialization · 3 - 6 Months

    • I

      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
      ·
      432 reviews

      Mixed · Course · 1 - 3 Months

    • M

      Meta

      Introduction to Social Media Marketing

      Skills you'll gain: Social Media Marketing, Social Media, Target Audience, Social Media Strategy, Social Media Management, Marketing, Key Performance Indicators (KPIs), Goal Setting, Facebook, Customer Analysis, Marketing Strategies, Marketing Channel, Instagram, Digital Marketing

      4.8
      Rating, 4.8 out of 5 stars
      ·
      15K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free
      Free
      T

      The Hong Kong University of Science and Technology

      Mastering Statics

      Skills you'll gain: Structural Analysis, Mechanics, Engineering Calculations, Mechanical Engineering, Civil Engineering, Engineering Analysis, Engineering Drawings, Geometry, Algebra, Applied Mathematics

      4.8
      Rating, 4.8 out of 5 stars
      ·
      223 reviews

      Intermediate · Course · 1 - 3 Months

    • I

      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

    • U

      University of Michigan

      Python Basics

      Skills you'll gain: Debugging, Programming Principles, Python Programming, Data Structures, Scripting Languages, Computer Programming, Pseudocode, Computer Graphics

      4.8
      Rating, 4.8 out of 5 stars
      ·
      18K reviews

      Beginner · Course · 1 - 4 Weeks

    • I

      IBM

      Data Analysis with R

      Skills you'll gain: Data Wrangling, Exploratory Data Analysis, Data Analysis, Data Transformation, R Programming, Data Manipulation, Data Visualization, Box Plots, Predictive Analytics, Statistical Analysis, Regression Analysis, Statistical Modeling, Correlation Analysis, Data Cleansing, Tidyverse (R Package), Supervised Learning

      4.7
      Rating, 4.7 out of 5 stars
      ·
      332 reviews

      Intermediate · Course · 1 - 3 Months

    • U

      University of California, Davis

      Big Data, Artificial Intelligence, and Ethics

      Skills you'll gain: Data Ethics, Artificial Intelligence, Research, Natural Language Processing, Big Data, Research Methodologies, Social Sciences, Machine Learning, Data Mining, Algorithms

      4.6
      Rating, 4.6 out of 5 stars
      ·
      598 reviews

      Beginner · Course · 1 - 4 Weeks

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

    • Natural Language Processing: DeepLearning.AI
    • IBM Introduction to Machine Learning: IBM
    • Data Visualization with Tableau: Tableau Learning Partner
    • Geographic Information Systems (GIS): University of California, Davis
    • Introduction to Electricity and Magnetism: Rice University
    • Statistics for Data Science with Python: IBM
    • Introduction to Social Media Marketing: Meta
    • Mastering Statics: The Hong Kong University of Science and Technology
    • Introduction to Artificial Intelligence (AI): IBM
    • Python Basics: University of Michigan

    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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