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    Results for "data manipulation"

    • U

      University of California San Diego

      Big Data

      Skills you'll gain: Data Analysis, Big Data, Data Management, Databases, Data Model, Exploratory Data Analysis, Machine Learning, Data Structures, Data Analysis Software, Data Visualization, SQL, Data Mining, Distributed Computing Architecture, Apache, Database Design, Extract, Transform, Load, Graph Theory, Probability & Statistics, Statistical Programming, Mathematics, Data Architecture, Data Warehousing, Machine Learning Algorithms, Leadership and Management, Cloud Computing, Database Theory, PostgreSQL, Statistical Machine Learning, Statistical Visualization, Algorithms, Human Learning

      4.5
      Rating, 4.5 out of 5 stars
      ·
      14K reviews

      Beginner · Specialization · 3 - 6 Months

    • U

      University of California San Diego

      Code Free Data Science

      Skills you'll gain: Data Analysis, Big Data, Data Analysis Software, Data Management, Data Mining, Machine Learning, Algorithms, Data Model, Data Visualization Software, Decision Making

      4.3
      Rating, 4.3 out of 5 stars
      ·
      205 reviews

      Beginner · Course · 1 - 4 Weeks

    • I

      IBM

      Data Science Methodology

      Skills you'll gain: Data Analysis, Data Mining, Data Model, Data Science, Python Programming

      4.6
      Rating, 4.6 out of 5 stars
      ·
      20K reviews

      Beginner · Course · 1 - 4 Weeks

    • I

      IBM

      Introduction to Data Analytics

      Skills you'll gain: Data Analysis, Databases, Python Programming, SQL, Data Management, Data Mining, Data Science, Data Visualization, NoSQL, R Programming, Big Data, Microsoft Excel

      4.8
      Rating, 4.8 out of 5 stars
      ·
      17K reviews

      Beginner · Course · 1 - 3 Months

    • I

      IBM

      Data Analysis and Visualization Foundations

      Skills you'll gain: Microsoft Excel, Data Visualization, Spreadsheet Software, Plot (Graphics), Data Analysis, Databases, Python Programming, SQL, Statistical Visualization, Data Management, Data Mining, Data Science, NoSQL, R Programming, Big Data, Business Analysis, Data Visualization Software, Interactive Data Visualization

      Build toward a degree

      4.7
      Rating, 4.7 out of 5 stars
      ·
      25K reviews

      Beginner · Specialization · 3 - 6 Months

    • U

      University of Colorado Boulder

      Data Understanding and Visualization

      Skills you'll gain: Data Visualization, Python Programming

      4.8
      Rating, 4.8 out of 5 stars
      ·
      6 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Placeholder
      U

      University of California, Davis

      SQL for Data Science

      Skills you'll gain: Data Analysis, Data Management, Data Model, Databases, SQL

      4.6
      Rating, 4.6 out of 5 stars
      ·
      17K reviews

      Beginner · Course · 1 - 4 Weeks

    • Placeholder
      J

      Johns Hopkins University

      Data Science: Foundations using R

      Skills you'll gain: Data Analysis, R Programming, Statistical Programming, Exploratory Data Analysis, Computer Programming, Computer Programming Tools, Data Management, Programming Principles, Data Structures, Statistical Analysis, Critical Thinking, Problem Solving, General Statistics, Statistical Tests, Computational Thinking, Big Data, Data Mining, Data Visualization, Databases, Extract, Transform, Load, Plot (Graphics), Communication, Computer Graphic Techniques, Computer Graphics, Interactive Data Visualization, Knitr, Visualization (Computer Graphics)

      4.6
      Rating, 4.6 out of 5 stars
      ·
      48K reviews

      Beginner · Specialization · 3 - 6 Months

    • Placeholder
      U

      University of California, Davis

      Data Visualization with Tableau

      Skills you'll gain: Data Visualization, Data Analysis, Data Analysis Software, Data Visualization Software, Tableau Software, Business Analysis, Business Intelligence, Statistical Visualization, Exploratory Data Analysis, Interactive Data Visualization, Interactive Design, Software Visualization, Storytelling, Visualization (Computer Graphics), Plot (Graphics), Computer Graphics

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

      Beginner · Specialization · 3 - 6 Months

    • Placeholder
      G

      Google

      Google Advanced Data Analytics

      Skills you'll gain: Communication, Computer Programming, Data Analysis, Data Visualization, Exploratory Data Analysis, General Statistics, Machine Learning, Planning, Probability Distribution, Project Management, Python Programming, Regression, Statistical Analysis, Tableau Software

      Build toward a degree

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

      Advanced · Professional Certificate · 3 - 6 Months

    • Placeholder
      J

      Johns Hopkins University

      Executive Data Science

      Skills you'll gain: Data Analysis, Exploratory Data Analysis, Probability & Statistics, Data Management, Critical Thinking, General Statistics, Leadership and Management, Data Model, Decision Making, Experiment, Statistical Analysis, Data Analysis Software, Machine Learning, Problem Solving, Correlation And Dependence, Machine Learning Algorithms, Statistical Tests, Strategy and Operations, Human Resources, Talent Management, Communication, Human Learning, Organizational Development, People Management

      4.5
      Rating, 4.5 out of 5 stars
      ·
      11K reviews

      Beginner · Specialization · 1 - 3 Months

    • Placeholder
      Status: Free
      Free
      C

      Coursera Instructor Network

      Data Science for Professionals

      Skills you'll gain: Data Visualization, Statistical Analysis

      Beginner · Course · 1 - 4 Weeks

    Searches related to data manipulation

    data manipulation and management using mysql workbench
    data manipulation at scale: systems and algorithms
    data manipulation with dplyr in r
    data manipulation in javascript
    data manipulation in rpa
    intermediate data manipulation and machine learning
    foundations of r programming and basic data manipulation
    data processing and manipulation
    1…111213…415

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

    • Big Data: University of California San Diego
    • Code Free Data Science: University of California San Diego
    • Data Science Methodology: IBM
    • Introduction to Data Analytics: IBM
    • Data Analysis and Visualization Foundations: IBM
    • Data Understanding and Visualization: University of Colorado Boulder
    • SQL for Data Science: University of California, Davis
    • Data Science: Foundations using R: Johns Hopkins University
    • Data Visualization with Tableau: University of California, Davis
    • Google Advanced Data Analytics: Google

    Frequently Asked Questions about Data Manipulation

    Data manipulation is the part of data science that organizes or changes data into formatting that's easier to read and use for analytical purposes. It may involve advanced techniques and tools, such as relational algebra or SQL to manage the data. It may also require less advanced skills, such as alphabetization or spreadsheets to compile the data for the end user. This type of data analysis makes it possible for a data scientist to pull pertinent information for decision-making purposes out of a large, otherwise disorganized mass of data.‎

    If you have a passion for using computers and solving complex problems and puzzles, learning data manipulation may lead to a variety of opportunities as a data scientist. These opportunities include becoming a data analyst, a data engineer, or a machine learning engineer. Tasks you might encounter during a typical workday in these fields include cluster analysis and creating a pivot table or a lookup table. If you want a very hands-on career that puts you in control of finding the most essential items in a company's data, learning data manipulation will help you get started in the field.‎

    Taking online data manipulation courses on Coursera can help you advance in your data science career by improving the skills and tools you have at your disposal, making the information you're able to provide for your employer more accurate and valuable. If you aren't already working in the data science field, taking online courses in data manipulation can serve as a place to begin your industry-specific data analysis education. Courses are available to match your current knowledge base, so whether you're a beginner learning about data manipulation and data science for the first time, or you're approaching courses from an intermediate or advanced level, you can jump in and start learning at your convenience.‎

    You need to have strong math skills and at least some computer skills to begin learning data manipulation. Solid reading and critical thinking skills will also help you when you delve into these courses. The data manipulation courses are set up for beginners in the data science field, providing knowledge that's needed to build on as you advance in the data analysis field. Some specific skills you can expect to develop while learning about data manipulation at your own include data visualization, SQL, and Python.‎

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

    When looking to enhance your workforce's skills in Data Manipulation, 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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