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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
      Status: AI skills
      AI skills
      I

      IBM

      IBM Data Analyst

      Skills you'll gain: Data Storytelling, Dashboard, Data Visualization Software, Plotly, Data Visualization, SQL, Predictive Modeling, Generative AI, Interactive Data Visualization, Exploratory Data Analysis, Data Wrangling, Data Analysis, Big Data, Jupyter, Matplotlib, Statistical Analysis, Pandas (Python Package), IBM Cognos Analytics, Excel Formulas, Professional Networking

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      92K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      G

      Google

      Google Advanced Data Analytics

      Skills you'll gain: Exploratory Data Analysis, Data Storytelling, Statistical Hypothesis Testing, Data Ethics, Data Visualization Software, Sampling (Statistics), Data Presentation, Regression Analysis, Feature Engineering, Data Transformation, Descriptive Statistics, Professional Networking, Data Visualization, Tableau Software, Data Manipulation, Statistical Analysis, Statistical Machine Learning, Object Oriented Programming (OOP), Data Analysis, Interviewing Skills

      Build toward a degree

      4.7
      Rating, 4.7 out of 5 stars
      ·
      6.2K reviews

      Advanced · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      Introduction to Data Analytics

      Skills you'll gain: Big Data, Data Analysis, Statistical Analysis, Apache Hadoop, Data Wrangling, Apache Hive, Data Collection, Data Mart, Data Warehousing, Analytics, Apache Spark, Data Cleansing, Data Lakes, Extract, Transform, Load, Data Visualization Software

      4.8
      Rating, 4.8 out of 5 stars
      ·
      19K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      Databases and SQL for Data Science with Python

      Skills you'll gain: SQL, Databases, Stored Procedure, Relational Databases, Database Design, Query Languages, Database Management, Data Analysis, Jupyter, Data Manipulation, Pandas (Python Package), Transaction Processing

      4.7
      Rating, 4.7 out of 5 stars
      ·
      22K reviews

      Beginner · Course · 1 - 3 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
      Status: AI skills
      AI skills
      M

      Microsoft

      Microsoft Power BI Data Analyst

      Skills you'll gain: Data Storytelling, Dashboard, Excel Formulas, Extract, Transform, Load, Power BI, Data Analysis Expressions (DAX), Microsoft Excel, Microsoft Copilot, Data Modeling, Data-Driven Decision-Making, Star Schema, Data Analysis, Data Presentation, Data Visualization Software, Spreadsheet Software, Data Validation, Interactive Data Visualization, Data Transformation, Data Cleansing, Data Storage

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      7.3K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      What is Data Science?

      Skills you'll gain: Data Literacy, Data Mining, Big Data, Cloud Computing, Data Analysis, Data Science, Digital Transformation, Data-Driven Decision-Making, Deep Learning, Machine Learning, Artificial Intelligence

      4.7
      Rating, 4.7 out of 5 stars
      ·
      76K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      I

      IBM

      Excel Basics for Data Analysis

      Skills you'll gain: Excel Formulas, Microsoft Excel, Data Cleansing, Data Analysis, Data Import/Export, Spreadsheet Software, Data Wrangling, Data Quality, Pivot Tables And Charts, Google Sheets, Data Manipulation, Data Visualization Software, Information Privacy

      4.8
      Rating, 4.8 out of 5 stars
      ·
      9.6K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      Status: AI skills
      AI skills
      I

      IBM

      IBM Data Engineering

      Skills you'll gain: NoSQL, Data Warehousing, SQL, Apache Hadoop, Extract, Transform, Load, Apache Airflow, Web Scraping, Linux Commands, Database Design, IBM Cognos Analytics, MySQL, Apache Spark, Data Pipelines, Apache Kafka, Database Management, Bash (Scripting Language), Data Store, Jupyter, Generative AI, Professional Networking

      Build toward a degree

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

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      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

    • 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

    • Status: Free Trial
      Free Trial
      I

      IBM

      IBM Data Management

      Skills you'll gain: Dashboard, Data Storytelling, Data Warehousing, SQL, Data Governance, Data Security, Data Migration, Database Design, Data Literacy, Descriptive Statistics, Extract, Transform, Load, Data Mining, Cloud Storage, Data Visualization Software, Data Store, IBM DB2, Data Management, Relational Databases, MySQL, Excel Formulas

      4.7
      Rating, 4.7 out of 5 stars
      ·
      17K 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
    1234…606

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

    • IBM Data Analyst: IBM
    • Google Advanced Data Analytics: Google
    • Introduction to Data Analytics: IBM
    • Databases and SQL for Data Science with Python: IBM
    • Big Data: University of California San Diego
    • Microsoft Power BI Data Analyst: Microsoft
    • What is Data Science? : IBM
    • Excel Basics for Data Analysis: IBM
    • IBM Data Engineering: IBM
    • IBM Business Analyst: 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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