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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

    • U

      University of California, Davis

      Data Visualization with Tableau

      Skills you'll gain: Data Storytelling, Data Presentation, Data Visualization Software, Key Performance Indicators (KPIs), Data Visualization, Dashboard, Interactive Data Visualization, Data Mapping, Tableau Software, Proposal Development, Graphing, Histogram, Scatter Plots, Tree Maps, Exploratory Data Analysis, Statistical Visualization, Storytelling, Performance Metric, Geospatial Mapping, Heat Maps

      4.5
      Rating, 4.5 out of 5 stars
      ·
      8.2K reviews

      Beginner · Specialization · 3 - 6 Months

    • P

      PwC

      Data-driven Decision Making

      Skills you'll gain: Analytics, Business Analytics, Data Analysis, Data-Driven Decision-Making, Business Intelligence, Data Literacy, Big Data, Data Storytelling, Statistical Analysis, Microsoft Excel, Data Visualization Software, R Programming

      4.6
      Rating, 4.6 out of 5 stars
      ·
      6.1K reviews

      Beginner · Course · 1 - 4 Weeks

    • I

      IBM

      Python Project for Data Engineering

      Skills you'll gain: Web Scraping, Data Transformation, Extract, Transform, Load, Data Manipulation, SQL, Integrated Development Environments, Data Processing, Databases, Application Programming Interface (API), Code Review, Restful API, Python Programming, Unit Testing, Style Guides

      4.6
      Rating, 4.6 out of 5 stars
      ·
      765 reviews

      Intermediate · Course · 1 - 4 Weeks

    • U

      University of Michigan

      Introduction to Data Science in Python

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

    • G

      Google

      The Path to Insights: Data Models and Pipelines

      Skills you'll gain: Data Modeling, Database Design, Extract, Transform, Load, Data Warehousing, Performance Tuning, Data Pipelines, Data Integrity, Business Intelligence, Business Process, Data Mart, Data Validation, Data Quality, SQL, Performance Testing

      4.7
      Rating, 4.7 out of 5 stars
      ·
      636 reviews

      Advanced · Course · 1 - 4 Weeks

    • U

      University of Michigan

      Python Data Structures

      Skills you'll gain: Data Structures, Python Programming, Programming Principles, Data Import/Export, Data Manipulation, Development Environment, File Management

      4.9
      Rating, 4.9 out of 5 stars
      ·
      97K reviews

      Beginner · Course · 1 - 3 Months

    • I

      IBM

      Exploratory Data Analysis for Machine Learning

      Skills you'll gain: Exploratory Data Analysis, Feature Engineering, Statistical Inference, Data Processing, Data Access, Anomaly Detection, Statistical Analysis, Data Analysis, Data Cleansing, Data Manipulation, Machine Learning, Probability & Statistics, Data Transformation, Workflow Management, Scalability

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2.2K reviews

      Intermediate · Course · 1 - 3 Months

    • U

      University of Virginia Darden School Foundation

      IBM & Darden Digital Strategy

      Skills you'll gain: Strategic Thinking, Digital Transformation, Business Strategy, Cloud Computing Architecture, Competitive Analysis, Cloud Services, Large Language Modeling, Business Transformation, Cloud Security, Cloud Infrastructure, Big Data, Cloud Platforms, Data Analysis, Statistical Analysis, Cloud Computing, Artificial Intelligence, Generative AI, Data Ethics, Product Lifecycle Management, Business Technologies

      4.7
      Rating, 4.7 out of 5 stars
      ·
      45K reviews

      Beginner · Specialization · 3 - 6 Months

    • I

      IBM

      IBM Business Analyst

      Skills you'll gain: Data Storytelling, Requirements Elicitation, Risk Mitigation, Business Analysis, Business Process Modeling, Risk Analysis, Process Mapping, Process Optimization, Requirements Management, Risk Management, Business Requirements, Stakeholder Management, Work Breakdown Structure, Scope Management, Process Analysis, Stakeholder Engagement, Data Visualization Software, Excel Formulas, Microsoft Excel, Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      12K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • U

      University of California, Davis

      SQL for Data Science

      Skills you'll gain: Data Governance, SQL, Data Quality, Database Design, Query Languages, Data Manipulation, Data Modeling, Relational Databases, Data Analysis, Data Cleansing

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

      Beginner · Course · 1 - 4 Weeks

    • 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, Data Literacy, Big Data, Verbal Communication Skills, Data Cleansing, Spreadsheet Software

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

      Beginner · Specialization · 3 - 6 Months

    • J

      Johns Hopkins University

      The Data Scientist’s Toolbox

      Skills you'll gain: Rmarkdown, Version Control, Data Science, Big Data, Git (Version Control System), GitHub, Data Analysis, R Programming, Statistical Programming, Development Environment, Integrated Development Environments, Software Installation

      4.6
      Rating, 4.6 out of 5 stars
      ·
      34K reviews

      Mixed · Course · 1 - 4 Weeks

    Data Manipulation learners also search

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

    • Data Visualization with Tableau: University of California, Davis
    • Data-driven Decision Making: PwC
    • Python Project for Data Engineering: IBM
    • Introduction to Data Science in Python: University of Michigan
    • The Path to Insights: Data Models and Pipelines: Google
    • Python Data Structures: University of Michigan
    • Exploratory Data Analysis for Machine Learning: IBM
    • IBM & Darden Digital Strategy: University of Virginia Darden School Foundation
    • IBM Business Analyst: IBM
    • SQL for Data Science: University of California, Davis

    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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