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    • Data Wrangling

    Data Wrangling Courses Online

    Master data wrangling techniques for cleaning and transforming data. Learn to use tools like Python, R, and Excel for data preparation.

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    Explore the Data Wrangling Course Catalog

    • Status: Free Trial
      Free Trial
      M

      Microsoft

      Harnessing the Power of Data with Power BI

      Skills you'll gain: Power BI, Data-Driven Decision-Making, Data Analysis, Data Collection, Business Intelligence, Analytical Skills, Data Transformation, Data Visualization Software, Microsoft 365

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.6K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      M

      Microsoft

      Data Modeling in Power BI

      Skills you'll gain: Data Analysis Expressions (DAX), Data Modeling, Star Schema, Power BI, Database Design, Data Transformation, Time Series Analysis and Forecasting, Performance Tuning

      4.3
      Rating, 4.3 out of 5 stars
      ·
      699 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      G

      Google

      Foundations of Digital Marketing and E-commerce

      Skills you'll gain: Data Storytelling, Customer experience strategy (CX), Performance Measurement, Data-Driven Decision-Making, E-Commerce, Marketing Strategies, Digital Marketing, Branding, Marketing Channel, Marketing Analytics, Search Engine Marketing, Search Engine Optimization, Social Media Marketing, Target Audience

      4.8
      Rating, 4.8 out of 5 stars
      ·
      28K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      S

      Stanford University

      Graph Search, Shortest Paths, and Data Structures

      Skills you'll gain: Data Structures, Graph Theory, Algorithms, Network Model, Network Analysis, Computational Thinking, Theoretical Computer Science, Network Routing

      4.8
      Rating, 4.8 out of 5 stars
      ·
      2K reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of Pennsylvania

      AI Fundamentals for Non-Data Scientists

      Skills you'll gain: Generative AI, Big Data, Machine Learning, Customer Data Management, Tensorflow, Artificial Intelligence, Deep Learning, Algorithms, Process Optimization, Data Analysis, Artificial Neural Networks, Natural Language Processing

      4.8
      Rating, 4.8 out of 5 stars
      ·
      738 reviews

      Mixed · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      ETL and Data Pipelines with Shell, Airflow and Kafka

      Skills you'll gain: Extract, Transform, Load, Apache Airflow, Data Pipelines, Apache Kafka, Data Warehousing, Data Transformation, Data Migration, Web Scraping, Data Integration, Shell Script, Data Processing, Real Time Data, Data Cleansing, Big Data, Performance Tuning, Scalability

      4.5
      Rating, 4.5 out of 5 stars
      ·
      412 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Python for Genomic Data Science

      Skills you'll gain: Bioinformatics, Data Structures, Jupyter, Python Programming, Programming Principles, Scripting Languages, Scripting, Data Processing, Computer Programming, Data Manipulation, File Management

      4.3
      Rating, 4.3 out of 5 stars
      ·
      1.8K reviews

      Mixed · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Getting and Cleaning Data

      Skills you'll gain: Data Manipulation, Data Cleansing, Data Wrangling, Data Integration, Data Quality, Data Transformation, Data Import/Export, Data Collection, Data Management, Web Scraping, Data Access, R Programming, Exploratory Data Analysis, MySQL, File Management, SQL, Application Programming Interface (API)

      4.5
      Rating, 4.5 out of 5 stars
      ·
      8.1K reviews

      Mixed · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of California, Davis

      Healthcare Data Quality and Governance

      Skills you'll gain: Data Governance, Data Quality, Data Validation, Data Management, Data Cleansing, Health Information Management, Metadata Management, Health Informatics, Technical Communication, Change Control

      4.6
      Rating, 4.6 out of 5 stars
      ·
      128 reviews

      Intermediate · Course · 1 - 4 Weeks

    • N

      Northeastern University

      Data Privacy Fundamentals

      Skills you'll gain: Information Privacy, Personally Identifiable Information, Data Ethics, Law, Regulation, and Compliance, Journalism, Emerging Technologies, Media and Communications, Internet Of Things, Artificial Intelligence

      4.8
      Rating, 4.8 out of 5 stars
      ·
      676 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      D

      DeepLearning.AI

      Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

      Skills you'll gain: Tensorflow, Deep Learning, Artificial Intelligence and Machine Learning (AI/ML), Performance Tuning, Artificial Neural Networks, Machine Learning Algorithms, Analysis, Debugging

      4.9
      Rating, 4.9 out of 5 stars
      ·
      63K reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of Colorado System

      Clinical Data Science

      Skills you'll gain: Tidyverse (R Package), Clinical Data Management, Extract, Transform, Load, Data Modeling, Clinical Research, R Programming, Data Manipulation, Predictive Modeling, Database Design, Google Cloud Platform, Intensive Care Unit, Data Ethics, Data Quality, Risk Modeling, Natural Language Processing, Health Informatics, Statistical Modeling, Bioinformatics, Text Mining, Data Processing

      4.5
      Rating, 4.5 out of 5 stars
      ·
      469 reviews

      Intermediate · Specialization · 3 - 6 Months

    Data Wrangling learners also search

    Data
    R
    Data Science
    Data Analytics
    Data Analysis
    R Programming
    Applied Data Science
    Beginner Data Science
    1…121314…599

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

    • Harnessing the Power of Data with Power BI: Microsoft
    • Data Modeling in Power BI: Microsoft
    • Foundations of Digital Marketing and E-commerce: Google
    • Graph Search, Shortest Paths, and Data Structures: Stanford University
    • AI Fundamentals for Non-Data Scientists: University of Pennsylvania
    • ETL and Data Pipelines with Shell, Airflow and Kafka: IBM
    • Python for Genomic Data Science: Johns Hopkins University
    • Getting and Cleaning Data: Johns Hopkins University
    • Healthcare Data Quality and Governance: University of California, Davis
    • Data Privacy Fundamentals: Northeastern University

    Skills you can learn in Machine Learning

    Python Programming (33)
    Tensorflow (32)
    Deep Learning (30)
    Artificial Neural Network (24)
    Big Data (18)
    Statistical Classification (17)
    Reinforcement Learning (13)
    Algebra (10)
    Bayesian (10)
    Linear Algebra (10)
    Linear Regression (9)
    Numpy (9)

    Frequently Asked Questions about Data Wrangling

    Data wrangling is important to learn if you want to be able to gather, select, and transform data to answer a question or solve a problem. This is essential for two reasons. First, the work of data wrangling can speed the time to develop and test models. Second, it allows for faster analysis and more accurate conclusions. Data wrangling makes data more usable in an organization. Understanding it can help your work better and make sounder decisions based on the data. Understanding it can help you with other data science courses, lead to professional certifications, or simply help you do better at your job.‎

    Careers that use data wrangling are usually in data science, data analysis, or data engineering. Data wrangling is usually part of an operational role that includes A/B testing, data visualization, model selection, and debugging. Some people who learn data wrangling go on to study advanced computer science, and others just want to understand how and why data is segmented and analyzed. Jobs in data wrangling call for the use of many different programming languages. Some organizations use SQL, others use Python, and some use pivot tables and other advanced Microsoft Excel spreadsheet functions. As more and more work will be using big data, the ability to clean and manipulate data will become more important.‎

    People who are best suited for roles in data wrangling at the entry-level have basic computer literacy, high-school math, comfort with numbers, and willingness to learn. Cleaning and manipulating data call for a sense of logic and order, too. Many people manage data for presentations to others, so the ability to design slide decks and reports may come into play. Data wrangling is a form of communication with others in the organization who want problems solved and need the information to do it. Good data wranglers have an interest in helping others use data better. Their work in debugging and data visualization contributes to the overall organization's success.‎

    Online Data Wrangling courses offer a convenient and flexible way to enhance your knowledge or learn new Data Wrangling skills. Choose from a wide range of Data Wrangling courses offered by top universities and industry leaders tailored to various skill levels.‎

    When looking to enhance your workforce's skills in Data Wrangling, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here.‎

    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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