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    • Data Manipulation

    Data Manipulation Courses Online

    Master data manipulation techniques for transforming data. Learn to clean, merge, and reshape datasets using tools like SQL and Python.

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    Explore the Data Manipulation Course Catalog

    • Placeholder
      C

      Coursera Project Network

      Introduction to Data Analysis using Microsoft Excel

      Skills you'll gain: Microsoft Excel, Excel Formulas, Spreadsheet Software, Pivot Tables And Charts, Data Analysis, Data Manipulation, Data Mining

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.9K reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • I

      IBM

      Tools for Data Science

      Skills you'll gain: Jupyter, Data Visualization Software, Software Development Tools, Data Science, GitHub, Big Data, R Programming, Statistical Programming, Application Programming Interface (API), Machine Learning, Cloud Computing, Git (Version Control System), Python Programming, SQL

      4.5
      Rating, 4.5 out of 5 stars
      ·
      30K reviews

      Beginner · Course · 1 - 3 Months

    • G

      Google

      Data Analysis with R Programming

      Skills you'll gain: Rmarkdown, Ggplot2, R Programming, Data Analysis, Tidyverse (R Package), Data Visualization Software, Statistical Programming, Data Cleansing, Data Manipulation, Programming Principles, Data Transformation, Integrated Development Environments, Data Import/Export

      4.8
      Rating, 4.8 out of 5 stars
      ·
      11K reviews

      Beginner · Course · 1 - 3 Months

    • P

      PwC

      Data Analysis and Presentation Skills: the PwC Approach

      Skills you'll gain: Analytics, Business Analytics, Data Analysis, Microsoft PowerPoint, Data Presentation, Presentations, Excel Formulas, Data-Driven Decision-Making, Dashboard, Data Storytelling, Business Intelligence, Microsoft Excel, Customer Analysis, Data Visualization, Data Visualization Software, Big Data, Target Market, Data Cleansing, Public Speaking, Spreadsheet Software

      4.6
      Rating, 4.6 out of 5 stars
      ·
      11K reviews

      Beginner · Specialization · 3 - 6 Months

    • U

      University of Michigan

      Introduction to Data Science in Python

      Skills you'll gain: Pandas (Python Package), Jupyter, NumPy, Data Manipulation, Data Science, Data Analysis, Statistical Analysis, Pivot Tables And Charts, Data Cleansing, Data Import/Export, Probability & Statistics, Python Programming, Programming Principles

      4.5
      Rating, 4.5 out of 5 stars
      ·
      27K reviews

      Intermediate · Course · 1 - 4 Weeks

    • I

      IBM

      IBM AI Developer

      Skills you'll gain: Generative AI, Software Development Life Cycle, Unit Testing, ChatGPT, HTML and CSS, Development Environment, Web Design and Development, Jupyter, Hypertext Markup Language (HTML), Software Engineering, Artificial Intelligence, Cascading Style Sheets (CSS), Web Development, Data Ethics, Application Deployment, Web Applications, Automation, Interviewing Skills, CI/CD, Professional Networking

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      67K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Placeholder
      I

      IBM

      Introduction to Data Engineering

      Skills you'll gain: Extract, Transform, Load, Data Architecture, Data Pipelines, Big Data, Data Warehousing, Data Governance, Data Storage Technologies, Apache Hadoop, Relational Databases, Apache Spark, Data Lakes, Databases, SQL, Data Mart, Data Security

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.1K reviews

      Beginner · Course · 1 - 4 Weeks

    • Placeholder
      I

      IBM

      Generative AI for Data Analysts

      Skills you'll gain: Generative AI, ChatGPT, Data Storytelling, OpenAI, Analytics, Data Analysis, Dashboard, Data Ethics, Artificial Intelligence, IBM Cloud, Data Visualization Software, Artificial Intelligence and Machine Learning (AI/ML), SQL, Python Programming, Software Development Tools, Data Cleansing, Augmented and Virtual Reality (AR/VR), Deep Learning, Image Analysis, Technical Communication

      4.7
      Rating, 4.7 out of 5 stars
      ·
      6K reviews

      Intermediate · Specialization · 1 - 3 Months

    • Placeholder
      G

      Google

      Foundations of Data Science

      Skills you'll gain: Data Storytelling, Data Ethics, Data Analysis, Workflow Management, Data-Driven Decision-Making, Analytical Skills, Data Science, Communication, Business, Business Workflow Analysis, Project Management, Stakeholder Communications, Professional Networking

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.1K reviews

      Advanced · Course · 1 - 3 Months

    • Placeholder
      C

      Coursera Project Network

      Data Manipulation and Management using MYSQL Workbench

      Skills you'll gain: MySQL Workbench, MySQL, Database Management Systems, Database Management, Data Manipulation, SQL, Databases, Query Languages, Data Integration

      4.5
      Rating, 4.5 out of 5 stars
      ·
      17 reviews

      Beginner · Guided Project · Less Than 2 Hours

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      Status: New
      New
      I

      IBM

      IBM Relational Database Administrator

      Skills you'll gain: Data Warehousing, SQL, Extract, Transform, Load, Apache Airflow, Web Scraping, Linux Commands, Database Administration, Data Pipelines, Apache Kafka, Database Management, Bash (Scripting Language), Shell Script, Database Architecture and Administration, Data Transformation, Data Architecture, Jupyter, Generative AI, Relational Databases, Database Design, Automation

      4.6
      Rating, 4.6 out of 5 stars
      ·
      57K reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • Placeholder
      C

      Coursera Project Network

      Data Manipulation with dplyr in R

      Skills you'll gain: Data Manipulation, Tidyverse (R Package), Data Analysis, R Programming, Exploratory Data Analysis, Data Transformation

      4.6
      Rating, 4.6 out of 5 stars
      ·
      21 reviews

      Beginner · Guided Project · Less Than 2 Hours

    Data Manipulation learners also search

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    1…678…583

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

    • Introduction to Data Analysis using Microsoft Excel: Coursera Project Network
    • Tools for Data Science: IBM
    • Data Analysis with R Programming: Google
    • Data Analysis and Presentation Skills: the PwC Approach: PwC
    • Introduction to Data Science in Python: University of Michigan
    • IBM AI Developer: IBM
    • Introduction to Data Engineering: IBM
    • Generative AI for Data Analysts: IBM
    • Foundations of Data Science: Google
    • Data Manipulation and Management using MYSQL Workbench: Coursera Project Network

    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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