Data collection courses can help you learn survey design, sampling techniques, data cleaning, and statistical analysis. You can build skills in qualitative and quantitative research methods, data visualization, and ethical considerations in data handling. Many courses introduce tools like Excel for data manipulation, R for statistical analysis, and software like Qualtrics for survey creation, showing how these skills are applied in real-world research settings.

University of Michigan
Skills you'll gain: Sampling (Statistics), Sample Size Determination, Surveys, Survey Creation, Data Collection, Statistical Analysis, Data Analysis Software, Statistical Software, Interviewing Skills, Research Design, STATA (Software), R (Software), Data Integration, Data Validation, Data Ethics, Data Analysis, Stata, Data Quality, Statistical Programming, R Programming
Beginner · Specialization · 3 - 6 Months

University of Maryland, College Park
Skills you'll gain: Surveys, Data Collection, Survey Creation, Research Design, Data Quality, Data Analysis, Analysis, Data Validation, Big Data
Intermediate · Course · 1 - 4 Weeks
University of Michigan
Skills you'll gain: Surveys, Survey Creation, Interviewing Skills, Data Collection, Research Methodologies, Data Quality, Social Media Analytics
Beginner · Course · 1 - 4 Weeks

University of Michigan
Skills you'll gain: JSON, Data Processing, Data Wrangling, Restful API, Data Manipulation, Data Access, Application Programming Interface (API), Python Programming, Data Transformation, Data Structures, Data Collection
Intermediate · Course · 1 - 4 Weeks

Skills you'll gain: Microsoft Excel, Excel Formulas, Pivot Tables And Charts, Data Analysis, Data Manipulation, Microsoft Office, Data Mining
Intermediate · Guided Project · Less Than 2 Hours

Skills you'll gain: Data Management, Data Presentation, Data Storytelling, Data Collection, Data Governance, Data Analysis, Information Privacy, Data Quality, Data Storage, Data Storage Technologies, Data Security, Exploratory Data Analysis, Data-Driven Decision-Making, Data Architecture, Data Visualization Software, Big Data, Applied Machine Learning, Machine Learning Methods, Machine Learning
Beginner · Course · 1 - 4 Weeks

University of Colorado Boulder
Skills you'll gain: Web Scraping, Data Integration, Data Cleansing, Data Import/Export, Data Quality, Data Preprocessing, Data Processing, Data Collection, SQL, Databases, Query Languages, Extensible Markup Language (XML), Pandas (Python Package), Application Programming Interface (API)
Intermediate · Course · 1 - 3 Months

Skills you'll gain: Data Cleansing, Data Wrangling, Surveys, Survey Creation, Data Transformation, Data Collection, Data Quality, Data Preprocessing, Data Integrity, ChatGPT, Cloud Technologies, Statistical Analysis, Real Time Data
Intermediate · Course · 3 - 6 Months

Skills you'll gain: Customer Retention, Customer Analysis, Customer Insights, Driving engagement, Sample Size Determination, Analytics, User Research, Product Management, Trend Analysis, Statistical Inference, Data-Driven Decision-Making, Unsupervised Learning, Analysis, Statistical Hypothesis Testing, Statistical Analysis, Performance Measurement, Scikit Learn (Machine Learning Library), Strategic Decision-Making, Algorithms
Intermediate · Course · 1 - 3 Months

Skills you'll gain: Tidyverse (R Package), Rmarkdown, Predictive Modeling, Model Evaluation, File Management, R (Software), Data Governance, Responsible AI, Data Manipulation, R Programming, Research Reports, Metadata Management, Data Quality, Predictive Analytics, Data Wrangling, Data Ethics, Business Research, Statistical Reporting, Market Research, Statistical Analysis
Beginner · Course · 1 - 3 Months

Skills you'll gain: Root Cause Analysis, Correlation Analysis, Regression Analysis, Statistical Methods, Statistics, Data Collection, Descriptive Statistics, Statistical Hypothesis Testing, Data Literacy, Probability & Statistics, Statistical Analysis, Process Analysis, Six Sigma Methodology, Lean Six Sigma, Quantitative Research, Business Process Improvement, Data Analysis, Process Improvement, Statistical Inference, Operational Efficiency
Beginner · Course · 1 - 4 Weeks

Coursera
Skills you'll gain: Business Research, General Data Protection Regulation (GDPR), Data Ethics, Strategic Decision-Making, Market Research, Business Ethics, Case Studies, Research Design, Research, Research Methodologies, Compliance Management, Law, Regulation, and Compliance, Information Privacy, Data Collection, Informed Consent, Ethical Standards And Conduct, Project Design, Data Capture, Data Analysis
Beginner · Course · 1 - 4 Weeks
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.‎