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    • Data Collection

    Data Collection Courses Online

    Explore data collection methods for research and analysis. Learn to design surveys, conduct interviews, and gather accurate data.

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    Explore the Data Collection Course Catalog

    • Status: Free Trial
      Free Trial
      G

      Google

      Foundations: Data, Data, Everywhere

      Skills you'll gain: Data Ethics, Data Analysis, Data-Driven Decision-Making, Google Sheets, Spreadsheet Software, Analytical Skills, Data Sharing, Data Cleansing, Data Processing, Data Visualization Software, SQL, Data Management

      4.8
      Rating, 4.8 out of 5 stars
      ·
      115K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      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
      ·
      770 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      G

      Google

      Share Data Through the Art of Visualization

      Skills you'll gain: Data Storytelling, Data Literacy, Data Visualization, Data Presentation, Interactive Data Visualization, Tableau Software, Presentations, Data Visualization Software, Dashboard, Web Content Accessibility Guidelines

      4.6
      Rating, 4.6 out of 5 stars
      ·
      9.6K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      G

      Google

      Google Data Analytics Capstone: Complete a Case Study

      Skills you'll gain: Interviewing Skills, Data Analysis, Data Processing, Analytical Skills, Artificial Intelligence, Recruitment, Data-Driven Decision-Making, Data Storytelling, Project Documentation, Presentations, Portfolio Management

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

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of Michigan

      Applied Data Science with Python

      Skills you'll gain: Matplotlib, Network Analysis, Feature Engineering, Data Visualization Software, Interactive Data Visualization, Scientific Visualization, Pandas (Python Package), Applied Machine Learning, Supervised Learning, Text Mining, Visualization (Computer Graphics), Statistical Visualization, Scikit Learn (Machine Learning Library), Network Model, Jupyter, NumPy, Graph Theory, Data Manipulation, Natural Language Processing, Data Analysis

      4.5
      Rating, 4.5 out of 5 stars
      ·
      34K reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Data Science

      Skills you'll gain: Shiny (R Package), Rmarkdown, Exploratory Data Analysis, Regression Analysis, Leaflet (Software), Version Control, Statistical Analysis, R Programming, Data Manipulation, Data Cleansing, Data Science, Statistical Inference, Predictive Modeling, Statistical Hypothesis Testing, Data Wrangling, Data Visualization, Plotly, Machine Learning Algorithms, Plot (Graphics), Knitr

      4.5
      Rating, 4.5 out of 5 stars
      ·
      51K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      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

    • Status: Free Trial
      Free Trial
      Status: New AI skills
      New AI skills
      G

      Google

      Google Digital Marketing & E-commerce

      Skills you'll gain: Media Planning, Search Engine Marketing, Email Marketing, Data Storytelling, Social Media Strategy, Search Engine Optimization, Social Media Marketing, Content Creation, Order Fulfillment, Google Ads, Professional Networking, Online Advertising, A/B Testing, Social Media Campaigns, E-Commerce, Customer Retention, Customer experience strategy (CX), Customer Relationship Management, Campaign Management, Interviewing Skills

      Build toward a degree

      4.8
      Rating, 4.8 out of 5 stars
      ·
      39K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      Data Engineering Foundations

      Skills you'll gain: Web Scraping, Database Design, SQL, MySQL, Data Transformation, Data Store, Extract, Transform, Load, IBM DB2, Relational Databases, Data Architecture, Jupyter, Data Pipelines, Big Data, Data Warehousing, Data Governance, Data Manipulation, Stored Procedure, Databases, Automation, Python Programming

      4.6
      Rating, 4.6 out of 5 stars
      ·
      56K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      Tools for Data Science

      Skills you'll gain: Jupyter, Computer Programming Tools, Data Science, GitHub, Big Data, R Programming, Statistical Programming, Application Programming Interface (API), Machine Learning, Cloud Computing, Git (Version Control System), Development Environment, Version Control, Other Programming Languages, Query Languages, Open Source Technology

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

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      G

      Google

      The Power of Statistics

      Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Descriptive Statistics, Data Analysis, Statistical Analysis, Probability Distribution, Statistical Methods, Advanced Analytics, Analytics, Statistics, Data Literacy, Statistical Inference, Probability, Statistical Software, Statistical Programming, A/B Testing, Sample Size Determination, Jupyter, Technical Communication

      4.8
      Rating, 4.8 out of 5 stars
      ·
      787 reviews

      Advanced · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      D

      Duke University

      Data Analysis with R

      Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Statistical Inference, Exploratory Data Analysis, Regression Analysis, Statistical Reporting, Probability Distribution, Statistical Methods, Data Analysis Software, R Programming, Bayesian Statistics, Statistical Analysis, Data Analysis, Statistical Software, Statistical Modeling, Probability & Statistics, Probability, Statistics, Correlation Analysis, Data Literacy

      4.7
      Rating, 4.7 out of 5 stars
      ·
      7.5K reviews

      Beginner · Specialization · 3 - 6 Months

    Data Collection learners also search

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    Data Science
    Data Analytics
    Data Analysis
    R Programming
    Applied Data Science
    Beginner Data Science
    1…567…607

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

    • Foundations: Data, Data, Everywhere: Google
    • Python Project for Data Engineering: IBM
    • Share Data Through the Art of Visualization: Google
    • Google Data Analytics Capstone: Complete a Case Study: Google
    • Applied Data Science with Python: University of Michigan
    • Data Science: Johns Hopkins University
    • Exploratory Data Analysis for Machine Learning: IBM
    • Google Digital Marketing & E-commerce: Google
    • Data Engineering Foundations: IBM
    • Tools for Data Science: IBM

    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 Collection

    Data collection is the systematic process of gathering information like observations or measurements while doing research. When you’re performing research, you’re likely looking for answers to a question you have. When it comes to data collection, digging beyond the surface tells an intriguing story. Collecting data about what you’re researching can help you gain more insight into the details and information that’ll help you answer that question. Although it’s particularly useful in science-related applications, the beauty of data collection is that you can use it to discover answers to almost any query you dream up.‎

    Data are important for helping you (and others, and even computers) make all sorts of different decisions. It helps scientists learn whether their studies are working and assists marketers in sending the right messages to the right people. It's what lets us know if something new we tried is really working. As information becomes digitized, it becomes data that we can use in a variety of ways to accomplish whatever we’ve set out to do. But in order to do that, we need to gather the data first. Without data collection to compile that information, we can’t be truly efficient in analyzing those details — what if something is missing? If you’re aiming to understand how research is conducted and decisions are made, it’s essential to learn about data collection’s role.‎

    Almost every career that involves data provides opportunities for collecting those data, even if the primary focus isn’t only collecting data. A multitude of different analyst roles require plenty of time spent gathering data, whether you choose to work in fields like marketing, human resources or business or you’re specifically interested in working as a data scientist — someone who directs their efforts toward compiling data and translating it into information that others can use to make decisions. Even working as an actuary — a professional who assesses risks, often in insurance fields — allows you to focus much of your time on dealing with data. But these careers are just the beginning; dozens more give you the opportunity to collect data, so it’s an important skill to have and concept to understand even if it’s not the primary focus of your work.‎

    If you’re looking to boost your data literacy, taking our online classes provides a worthwhile opportunity to pursue your goals whenever it’s most convenient for you. Online courses give you the time and space you need to complete coursework from home while also providing you access to learning materials created by accomplished instructors and other field experts. You’ll enjoy learning the basic frameworks of data collection and analysis as you’re getting started learning about this topic by discovering the role of research, analysis and collection techniques. As you advance, you might choose to study more complex topics like utilizing the Python programming language to create programs that fetch and analyze data. And with a variety of learning programs, from certificates to specializations to course credits for college degrees, you can formalize your data analysis accomplishments as you continue to build skills.‎

    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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