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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 Cloud

      Data Engineering, Big Data, and Machine Learning on GCP

      Skills you'll gain: Data Pipelines, Dataflow, Google Cloud Platform, Real Time Data, Data Lakes, MLOps (Machine Learning Operations), Dashboard, Data Warehousing, Extract, Transform, Load, Cloud Engineering, Data Infrastructure, Cloud Infrastructure, Cloud Storage, Big Data, Tensorflow, Unstructured Data, Data Integration, Data Migration, Data Processing, Data Visualization Software

      4.6
      Rating, 4.6 out of 5 stars
      ·
      18K reviews

      Intermediate · Specialization · 3 - 6 Months

    • D

      Duke University

      Data Science Math Skills

      Skills you'll gain: Probability, Bayesian Statistics, General Mathematics, Calculus, Graphing, Statistics, Data Science, Data Analysis, Plot (Graphics), Algebra, Geometry, Arithmetic, Derivatives

      4.5
      Rating, 4.5 out of 5 stars
      ·
      13K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      Data Analysis and Visualization Foundations

      Skills you'll gain: Data Storytelling, Big Data, Data Visualization Software, Data Analysis, Dashboard, IBM Cognos Analytics, Statistical Analysis, Data Mining, Apache Hadoop, Tree Maps, Excel Formulas, Data Wrangling, Apache Hive, Data Collection, Data Mart, Microsoft Excel, Data Warehousing, Data Quality, Data Cleansing, Data Import/Export

      Build toward a degree

      4.7
      Rating, 4.7 out of 5 stars
      ·
      28K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      D
      S

      Multiple educators

      Machine Learning

      Skills you'll gain: Unsupervised Learning, Supervised Learning, Machine Learning Methods, Classification And Regression Tree (CART), Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Machine Learning Algorithms, Machine Learning, Jupyter, Data Ethics, Decision Tree Learning, Tensorflow, Scikit Learn (Machine Learning Library), Artificial Intelligence, NumPy, Predictive Modeling, Deep Learning, Reinforcement Learning, Random Forest Algorithm, Feature Engineering

      Build toward a degree

      4.9
      Rating, 4.9 out of 5 stars
      ·
      34K reviews

      Beginner · Specialization · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      G

      Google

      Ask Questions to Make Data-Driven Decisions

      Skills you'll gain: Spreadsheet Software, Stakeholder Communications, Dashboard, Data-Driven Decision-Making, Data Analysis, Analytical Skills, Data Presentation, Business Analysis, Expectation Management, Quantitative Research, Communication

      4.7
      Rating, 4.7 out of 5 stars
      ·
      34K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      I

      IBM

      Tools for Data Science

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

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

      Beginner · 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

    • Status: Free Trial
      Free Trial
      I

      IBM

      Applied Data Science

      Skills you'll gain: Dashboard, Data Visualization Software, Plotly, Data Visualization, Predictive Modeling, Interactive Data Visualization, Exploratory Data Analysis, Data Wrangling, Data Analysis, Jupyter, Matplotlib, Pandas (Python Package), Seaborn, Data Presentation, Data Import/Export, Web Scraping, Python Programming, Data Structures, Data Science, Data-Driven Decision-Making

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      58K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      U

      University of California San Diego

      Big Data

      Skills you'll gain: Apache Spark, Apache Hadoop, Data Integration, Exploratory Data Analysis, Big Data, Graph Theory, Data Pipelines, Database Design, Data Modeling, Regression Analysis, Applied Machine Learning, Data Presentation, Scalability, Data Mining, Data Processing, Statistical Analysis, Data Management, NoSQL, Database Management Systems, Network Analysis

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

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Data Science: Foundations using R

      Skills you'll gain: Rmarkdown, Exploratory Data Analysis, Version Control, Statistical Analysis, R Programming, Data Manipulation, Data Cleansing, Data Science, Data Wrangling, Data Visualization, Plot (Graphics), Statistical Programming, Ggplot2, Big Data, Git (Version Control System), Data Integration, Knitr, Data Analysis, Data Sharing, Statistical Reporting

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

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Genomic Data Science

      Skills you'll gain: Bioinformatics, Unix Commands, Biostatistics, Exploratory Data Analysis, Statistical Analysis, Unix, Data Science, Data Management, Statistical Methods, Molecular Biology, Command-Line Interface, Statistical Hypothesis Testing, Linux Commands, Data Analysis Software, Statistical Modeling, Data Structures, Data Analysis, R Programming, Computational Thinking, Jupyter

      4.5
      Rating, 4.5 out of 5 stars
      ·
      6.6K reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      IBM Data Warehouse Engineer

      Skills you'll gain: Data Warehousing, SQL, Extract, Transform, Load, Apache Airflow, Linux Commands, Database Design, IBM Cognos Analytics, MySQL, Data Pipelines, Apache Kafka, Database Management, Bash (Scripting Language), Shell Script, Database Architecture and Administration, Data Store, IBM DB2, Dashboard, Relational Databases, File Management, Star Schema

      4.7
      Rating, 4.7 out of 5 stars
      ·
      6.1K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    Data Collection learners also search

    Data
    R
    Data Science
    Data Analytics
    Data Analysis
    R Programming
    Applied Data Science
    Beginner Data Science
    1…678…608

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

    • Data Engineering, Big Data, and Machine Learning on GCP: Google Cloud
    • Data Science Math Skills: Duke University
    • Data Analysis and Visualization Foundations: IBM
    • Machine Learning: DeepLearning.AI
    • Ask Questions to Make Data-Driven Decisions: Google
    • Tools for Data Science: IBM
    • Data Analysis with R: Duke University
    • Applied Data Science: IBM
    • Big Data: University of California San Diego
    • Data Science: Foundations using R: Johns Hopkins University

    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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