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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
      I

      IBM

      Generative AI and LLMs: Architecture and Data Preparation

      Skills you'll gain: Large Language Modeling, Generative AI, PyTorch (Machine Learning Library), Text Mining, Natural Language Processing, Artificial Intelligence and Machine Learning (AI/ML), Artificial Neural Networks, Data Processing

      4.7
      Rating, 4.7 out of 5 stars
      ·
      205 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      D

      DeepLearning.AI

      Natural Language Processing with Classification and Vector Spaces

      Skills you'll gain: Natural Language Processing, Supervised Learning, Dimensionality Reduction, Feature Engineering, Machine Learning Algorithms, Artificial Intelligence, Tensorflow, Linear Algebra, Probability & Statistics

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

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of Michigan

      Using Databases with Python

      Skills you'll gain: Relational Databases, Database Design, SQL, Databases, Web Scraping, Data Modeling, Database Management, Data Visualization Software, Object-Relational Mapping, Object Oriented Programming (OOP), Data Processing, Python Programming, Application Programming Interface (API)

      4.8
      Rating, 4.8 out of 5 stars
      ·
      21K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      SQL: A Practical Introduction for Querying Databases

      Skills you'll gain: SQL, Relational Databases, Microsoft SQL Servers, MySQL, Query Languages, Database Systems, Databases, Database Management, Stored Procedure, IBM DB2, Data Manipulation, Data Analysis, Transaction Processing

      4.7
      Rating, 4.7 out of 5 stars
      ·
      594 reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      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

    • Status: Free Trial
      Free Trial
      I

      IBM

      Applied Data Science Capstone

      Skills you'll gain: Plotly, Exploratory Data Analysis, Predictive Modeling, Data Science, Data-Driven Decision-Making, Data Presentation, Data Analysis, Pandas (Python Package), Web Scraping, Statistical Modeling, Data Wrangling, Machine Learning Methods, Data Collection

      4.7
      Rating, 4.7 out of 5 stars
      ·
      7.3K reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      Generative AI: Introduction and Applications

      Skills you'll gain: Generative AI, ChatGPT, OpenAI, Prompt Engineering, Large Language Modeling, Artificial Intelligence, Program Development, Content Creation, Image Analysis, Virtual Environment

      4.7
      Rating, 4.7 out of 5 stars
      ·
      2.6K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      P

      PwC

      Problem Solving with Excel

      Skills you'll gain: Excel Formulas, Microsoft Excel, Data Cleansing, Spreadsheet Software, Data Analysis Expressions (DAX), Data Validation, Complex Problem Solving, Statistical Analysis, Financial Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      5.4K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      D

      Duke University

      Introduction to Probability and Data with R

      Skills you'll gain: Sampling (Statistics), Exploratory Data Analysis, Statistical Inference, Probability Distribution, Bayesian Statistics, R Programming, Data Analysis, Probability, Statistics, Statistical Software, Descriptive Statistics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      5.8K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      G

      Google

      Foundations of Business Intelligence

      Skills you'll gain: Stakeholder Engagement, Business Intelligence, Data Integration, Dashboard, Business Analytics, Real Time Data, Data Modeling, Data-Driven Decision-Making, Data Analysis, Requirements Elicitation, Business Metrics, Key Performance Indicators (KPIs), Data Pipelines, Project Documentation

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.8K reviews

      Advanced · Course · 1 - 4 Weeks

    • G

      Georgia Institute of Technology

      Introduction to User Experience Design

      Skills you'll gain: User Experience Design, Prototyping, User Centered Design, Usability, Requirements Analysis, UI/UX Research, Interaction Design, User Interface (UI) Design, Usability Testing, User Research

      4.6
      Rating, 4.6 out of 5 stars
      ·
      8.9K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      D

      DeepLearning.AI

      AI for Medicine

      Skills you'll gain: Deep Learning, Statistical Analysis, Clinical Trials, Feature Engineering, Risk Modeling, Treatment Planning, Data Analysis, Precision Medicine, Decision Tree Learning, Predictive Modeling, Patient Treatment, Image Analysis, Machine Learning Methods, Applied Machine Learning, AI Personalization, Machine Learning, Random Forest Algorithm, Artificial Intelligence and Machine Learning (AI/ML), Data Processing, Medical Imaging

      4.7
      Rating, 4.7 out of 5 stars
      ·
      2.4K reviews

      Intermediate · Specialization · 1 - 3 Months

    Data Wrangling learners also search

    Data
    R
    Data Science
    Data Analytics
    Data Analysis
    R Programming
    Applied Data Science
    Beginner Data Science
    1…272829…601

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

    • Generative AI and LLMs: Architecture and Data Preparation: IBM
    • Natural Language Processing with Classification and Vector Spaces: DeepLearning.AI
    • Using Databases with Python: University of Michigan
    • SQL: A Practical Introduction for Querying Databases: IBM
    • Python Basics: University of Michigan
    • Applied Data Science Capstone: IBM
    • Generative AI: Introduction and Applications: IBM
    • Problem Solving with Excel : PwC
    • Introduction to Probability and Data with R: Duke University
    • Foundations of Business Intelligence: Google

    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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