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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

    • 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

    • 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
      ·
      408 reviews

      Intermediate · Course · 1 - 3 Months

    • U

      University of California, Davis

      Fundamentals of Visualization with Tableau

      Skills you'll gain: Data Visualization Software, Data Visualization, Interactive Data Visualization, Dashboard, Tableau Software, Data Presentation, Tree Maps, Data Analysis, Data Import/Export

      4.5
      Rating, 4.5 out of 5 stars
      ·
      6.7K reviews

      Beginner · Course · 1 - 4 Weeks

    • U

      University of California San Diego

      Big Data Integration and Processing

      Skills you'll gain: Apache Spark, Apache Hadoop, Data Integration, Big Data, Data Pipelines, Data Processing, Data Management, NoSQL, Analytics, Splunk, Database Systems, MongoDB, Pandas (Python Package), SQL, PostgreSQL

      4.4
      Rating, 4.4 out of 5 stars
      ·
      2.4K reviews

      Beginner · Course · 1 - 3 Months

    • I

      IBM

      Developing Mobile Apps with React Native

      Skills you'll gain: React Native, Flutter (Software), Mobile Development, React Redux, React.js, Front-End Web Development, JavaScript Frameworks, Ajax, Cross Platform Development, Javascript, Apple iOS, UI Components, Data Structures, Back-End Web Development, Debugging, iOS Development, User Story, Full-Stack Web Development, Web Applications, Android Development

      4.4
      Rating, 4.4 out of 5 stars
      ·
      801 reviews

      Beginner · Specialization · 3 - 6 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

    • U

      University of California, Irvine

      An Introduction to Programming the Internet of Things (IOT)

      Skills you'll gain: Test Planning, Embedded Systems, Linux, Internet Of Things, Embedded Software, Functional Requirement, Debugging, General Networking, Hardware Design, Systems Design, Operating Systems, Requirements Analysis, Electronic Hardware, System Design and Implementation, C (Programming Language), Basic Electrical Systems, Application Programming Interface (API), TCP/IP, Wireless Networks, Integrated Development Environments

      4.7
      Rating, 4.7 out of 5 stars
      ·
      20K reviews

      Beginner · Specialization · 3 - 6 Months

    • C

      Coursera Project Network

      Python for Data Analysis: Pandas & NumPy

      Skills you'll gain: Pandas (Python Package), NumPy, Data Analysis, Data Science, Python Programming, Data Structures, Data Manipulation, Computer Programming

      4.5
      Rating, 4.5 out of 5 stars
      ·
      333 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • U

      University of Michigan

      Python Basics

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

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

      Beginner · Course · 1 - 4 Weeks

    • M

      Microsoft

      Data for Business Analysts Using Microsoft Excel

      Skills you'll gain: Excel Formulas, Microsoft Excel, Pivot Tables And Charts, Spreadsheet Software, Data Analysis, Data Presentation, Business Metrics, Data Cleansing, Data Manipulation

      4.7
      Rating, 4.7 out of 5 stars
      ·
      195 reviews

      Beginner · Course · 1 - 3 Months

    • T

      Tableau Learning Partner

      Introduction to Tableau

      Skills you'll gain: Tableau Software, Data Presentation, Interactive Data Visualization, Data Visualization Software, Business Analytics, Business Intelligence, Data Integration, Data Analysis, Data Cleansing, Data Processing, Performance Tuning

      4.8
      Rating, 4.8 out of 5 stars
      ·
      256 reviews

      Beginner · Course · 1 - 4 Weeks

    • 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

    Data Manipulation learners also search

    Data
    R
    Data Science
    Data Analytics
    Data Analysis
    R Programming
    Applied Data Science
    Beginner Data Science
    1…252627…594

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

    • Data Analysis with R: IBM
    • ETL and Data Pipelines with Shell, Airflow and Kafka: IBM
    • Fundamentals of Visualization with Tableau: University of California, Davis
    • Big Data Integration and Processing: University of California San Diego
    • Developing Mobile Apps with React Native: IBM
    • Introduction to Social Media Marketing: Meta
    • An Introduction to Programming the Internet of Things (IOT): University of California, Irvine
    • Python for Data Analysis: Pandas & NumPy: Coursera Project Network
    • Python Basics: University of Michigan
    • Data for Business Analysts Using Microsoft Excel: Microsoft

    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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