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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
      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
      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
      I

      IBM

      Data Visualization with Python

      Skills you'll gain: Data Visualization Software, Plotly, Data Visualization, Dashboard, Interactive Data Visualization, Matplotlib, Seaborn, Data Presentation, Data Analysis, Geospatial Information and Technology, Pandas (Python Package), Scatter Plots, Histogram, Heat Maps, Box Plots

      4.5
      Rating, 4.5 out of 5 stars
      ·
      12K reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      Status: AI skills
      AI skills
      M

      Meta

      Meta Data Analyst

      Skills you'll gain: Data Storytelling, Business Metrics, Key Performance Indicators (KPIs), Data Management, Data Collection, Data Governance, Bayesian Statistics, Data Analysis, Descriptive Statistics, Statistical Hypothesis Testing, Information Privacy, Data Cleansing, Pandas (Python Package), Data Visualization Software, Statistical Inference, Spreadsheet Software, Correlation Analysis, Google Sheets, Exploratory Data Analysis, Data Modeling

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.4K reviews

      Beginner · Professional Certificate · 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, Data Cleansing, Data Access, Data Analysis, Statistical Inference, Statistical Hypothesis Testing, Data Quality, Data Science, Probability & Statistics, Jupyter, Machine Learning, Data Manipulation, Pandas (Python Package), Statistical Analysis, Data Transformation, Artificial Intelligence

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

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      D
      A

      Multiple educators

      DeepLearning.AI Data Engineering

      Skills you'll gain: Apache Airflow, Data Modeling, Data Pipelines, Data Storage, Data Storage Technologies, Data Architecture, Data Transformation, Requirements Analysis, Data Processing, Data Warehousing, Query Languages, Apache Hadoop, Extract, Transform, Load, Data Lakes, Amazon Web Services, Apache Spark, Database Systems, Data Integration, Infrastructure as Code (IaC), Terraform

      4.8
      Rating, 4.8 out of 5 stars
      ·
      447 reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      S

      Stanford University

      Algorithms

      Skills you'll gain: Data Structures, Graph Theory, Algorithms, Bioinformatics, Theoretical Computer Science, Network Model, Computational Thinking, Network Analysis, Analysis, Programming Principles, Probability & Statistics, Network Routing, Probability, Operations Research, Design Strategies

      4.8
      Rating, 4.8 out of 5 stars
      ·
      5.9K reviews

      Intermediate · Specialization · 3 - 6 Months

    • D

      DeepLearning.AI

      AI For Everyone

      Skills you'll gain: Data Ethics, Market Opportunities, Artificial Intelligence and Machine Learning (AI/ML), Artificial Intelligence, Team Building, Machine Learning, Strategic Thinking, Data Science, Needs Assessment, Deep Learning, Business Ethics, Artificial Neural Networks, Engineering Management

      4.8
      Rating, 4.8 out of 5 stars
      ·
      48K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      I

      Imperial College London

      Mathematics for Machine Learning

      Skills you'll gain: Linear Algebra, Dimensionality Reduction, NumPy, Regression Analysis, Calculus, Applied Mathematics, Probability & Statistics, Feature Engineering, Data Transformation, Jupyter, Data Science, Advanced Mathematics, Statistics, Machine Learning Algorithms, Machine Learning Methods, Statistical Analysis, Artificial Neural Networks, Algorithms, Data Manipulation, Python Programming

      4.6
      Rating, 4.6 out of 5 stars
      ·
      15K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      IBM AI Developer

      Skills you'll gain: Prompt Engineering, HTML and CSS, Software Development Life Cycle, Software Architecture, Large Language Modeling, Unit Testing, Generative AI, Artificial Intelligence, Software Design, ChatGPT, Jupyter, Scrum (Software Development), Software Engineering, Agile Methodology, Bootstrap (Front-End Framework), Web Design, Application Deployment, Automation, Interviewing Skills, Professional Networking

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      69K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • 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
      U

      University of Pennsylvania

      Business Analytics

      Skills you'll gain: People Analytics, Data-Driven Decision-Making, Human Capital, Business Analytics, Descriptive Analytics, Business Intelligence, Financial Data, Marketing Analytics, Analytics, Talent Management, Financial Analysis, Predictive Analytics, Human Resources Management and Planning, Peer Review, Business Analysis, Financial Statement Analysis, Financial Forecasting, Customer Insights, Workforce Planning, Demand Planning

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

      Beginner · Specialization · 3 - 6 Months

    Data Collection learners also search

    Data
    R
    Data Science
    Data Analytics
    Data Analysis
    R Programming
    Applied Data Science
    Beginner Data Science
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    In summary, here are 10 of our most popular data collection courses

    • Data Science: Johns Hopkins University
    • Machine Learning: DeepLearning.AI
    • Data Visualization with Python: IBM
    • Meta Data Analyst: Meta
    • Exploratory Data Analysis for Machine Learning: IBM
    • DeepLearning.AI Data Engineering: DeepLearning.AI
    • Algorithms: Stanford University
    • AI For Everyone: DeepLearning.AI
    • Mathematics for Machine Learning: Imperial College London
    • IBM AI Developer: 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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