Data analytics courses can help you learn data visualization, statistical analysis, and data cleaning techniques. You can build skills in interpreting complex datasets, making data-driven decisions, and communicating insights effectively. Many courses introduce tools like Excel, SQL, and Tableau, that support analyzing data and presenting findings. You'll also explore methods such as regression analysis and A/B testing, which are crucial for evaluating performance and optimizing strategies.
Skills you'll gain: Interactive Data Visualization, Statistics, Descriptive Statistics, Logistic Regression, Decision Tree Learning, Advanced Analytics, Probability & Statistics, Probability Distribution, Statistical Inference, Applied Machine Learning, Data-Driven Decision-Making, Supervised Learning, Workflow Management, Statistical Methods, Statistical Modeling, Data Cleansing, Data Structures, Interviewing Skills, NumPy, Professional Development
★ 4.8 (13K) · Advanced · Professional Certificate · 3 - 6 Months
Skills you'll gain: Data Visualization, Data Presentation, Regression Analysis, Advanced Analytics, Analytics, Statistical Analysis, Data Analysis, Statistical Modeling, Applied Machine Learning, Analytical Skills, Data Science, Machine Learning Methods, Artificial Intelligence, Python Programming, AI literacy, Machine Learning, Portfolio Management
★ 4.8 (1.4K) · Advanced · Course · 1 - 4 Weeks
Skills you'll gain: Data Modeling, Stakeholder Engagement, Dashboard, Business Intelligence, Tableau Software, Extract, Transform, Load, Data Warehousing, Database Systems, Interactive Data Visualization, Data Visualization, Data Pipelines, Interviewing Skills, Business Process, Business Analysis, Database Design, Data Mart, Applicant Tracking Systems, Data Analysis, SQL, Stakeholder Communications
★ 4.8 (9.4K) · Advanced · Professional Certificate · 3 - 6 Months

Corporate Finance Institute
Skills you'll gain: Classification Algorithms, Data Preprocessing, Matplotlib, Feature Engineering, Data Visualization, Model Evaluation, Data Import/Export, Exploratory Data Analysis, Plot (Graphics), Pandas (Python Package), Data Presentation, Data Science, NumPy, Regression Analysis, Data Analysis, Data Structures, Data Wrangling, Correlation Analysis, Portfolio Management, Predictive Analytics
★ 4.7 (21) · Advanced · Specialization · 3 - 6 Months

ESSEC Business School
Skills you'll gain: Data-Driven Marketing, Marketing Analytics, Business Analytics, Statistical Programming, Forecasting, Peer Review, Statistical Methods, Data Presentation, Predictive Analytics, Customer Analysis, Case Studies, R (Software), Information Technology, Analytical Skills, Digital Transformation, Business Marketing, Advanced Analytics, Complex Problem Solving, Data Synthesis, R Programming
★ 4.4 (1.3K) · Advanced · Specialization · 3 - 6 Months
Skills you'll gain: Data Modeling, Database Design, Extract, Transform, Load, Databases, Data Warehousing, Database Systems, Data Pipelines, Business Intelligence, Data Integrity, Data Validation, Data Mart, Business Process, Data Integration, Data Management, Data Quality, Data Transformation, Performance Testing
★ 4.7 (730) · Advanced · Course · 1 - 4 Weeks
Skills you'll gain: A/B Testing, Sampling (Statistics), Data Analysis, Analytics, Statistics, Descriptive Statistics, Statistical Analysis, Statistical Hypothesis Testing, Probability & Statistics, Advanced Analytics, Probability Distribution, Data Science, Statistical Inference, Statistical Programming, Statistical Methods, Probability, Python Programming
★ 4.8 (912) · Advanced · Course · 1 - 3 Months

Skills you'll gain: Data Warehousing, MongoDB, IBM Cognos Analytics, Extract, Transform, Load, NoSQL, Apache Spark, IBM DB2, Big Data, Dashboard Creation, Data Integration, Dashboard, Business Intelligence, Database Architecture and Administration, PySpark, Data Pipelines, Analytics, Databases, Relational Databases, SQL, Python Programming
★ 4.7 (143) · Advanced · Course · 1 - 3 Months
Skills you'll gain: Stakeholder Engagement, Business Intelligence, Stakeholder Communications, Data-Driven Decision-Making, Dashboard, Real Time Data, Data Integration, Data Modeling, Data Compilation, Data Analysis, Business Metrics, Plan Execution, Business Process Improvement, Business Process, Project Implementation, Continuous Monitoring
★ 4.8 (2.2K) · Advanced · Course · 1 - 4 Weeks

Skills you'll gain: Star Schema, Data Infrastructure, Data Governance, Data Modeling, Data Strategy, Data Architecture, Data Migration, Cloud Management, Database Design, Correlation Analysis, Stored Procedure, Data Pipelines, Infrastructure as Code (IaC), Data Validation, Disaster Recovery, Role-Based Access Control (RBAC), Compliance Auditing, CI/CD, Resource Management, Performance Management
Advanced · Specialization · 3 - 6 Months
Skills you'll gain: Data Storytelling, Data Ethics, Data Analysis, Data-Driven Decision-Making, Analytics, Workflow Management, Data Science, Advanced Analytics, Analytical Skills, Business Solutions, Technical Communication, Process Design, Project Management, Communication, Stakeholder Communications, Machine Learning
★ 4.7 (4K) · Advanced · Course · 1 - 3 Months

Coursera
Skills you'll gain: SQL, PostgreSQL, Query Languages, Database Management, Database Systems, Data Manipulation
★ 4.6 (42) · Advanced · Guided Project · Less Than 2 Hours
Data analytics is the process of collecting, cleaning, analyzing, and interpreting data to support better decisions. It often involves working with spreadsheets, databases, visualization tools, and statistical methods to find patterns or answer practical questions. Courses such as Introduction to Data Analytics from IBM and Foundations: Data, Data, Everywhere from Google introduce core concepts like data types, data-driven decision-making, and the analytics workflow. On Coursera, you can start with foundational courses and then move into tools like SQL, Excel, R, and Power BI as your confidence grows.‎
Data analytics is used in roles such as data analyst, business analyst, operations analyst, marketing analyst, financial analyst, and product analyst. These jobs often involve organizing data, creating reports or dashboards, identifying trends, and communicating insights to teams or stakeholders. Courses on this page, such as Google Data Analytics and Microsoft Data Analysis with SQL, Excel & Power BI, focus on practical skills that connect to common workplace analysis tasks. Exploring different courses can help you understand which tools and applications fit the type of role or industry you are considering.‎
Before learning data analytics, it helps to be comfortable with basic math, spreadsheets, and logical problem-solving. You do not need an advanced technical background to begin, but familiarity with tables, charts, percentages, and simple formulas can make early lessons easier to follow. Beginner-friendly options like Foundations: Data, Data, Everywhere from Google and Introduction to Data Analytics from IBM are designed to introduce the field step by step. If you are new to the topic, starting with general analytics concepts before moving into SQL, R, or visualization tools can be a useful path.‎
Skills that complement data analytics include SQL, spreadsheet analysis, data visualization, statistics, programming, and communication. SQL helps you work with databases, while Excel and visualization tools can help you organize findings and present them clearly. Courses in the page context include Microsoft Data Analysis with SQL, Excel & Power BI, Excel Skills for Data Analytics and Visualization from Macquarie University, and IBM Data Analytics with Excel and R. Building a mix of technical and communication skills can help you turn data into insights that others can understand and use.‎
You can start learning data analytics by taking an introductory course that explains the analytics process and basic tools. A good first step is to learn how data is collected, cleaned, analyzed, visualized, and used to support decisions. Courses such as Google Data Analytics, IBM Introduction to Data Analytics, and DeepLearning.AI Data Analytics offer structured ways to build from foundational concepts into applied practice. As you progress, you can choose courses focused on tools like Excel, SQL, Power BI, or R depending on your goals and comfort level.‎
Yes. You can start learning data analytics on Coursera for free in two ways:
If you want to keep learning, earn a certificate in data analytics, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.‎
Strong beginner courses for data analytics include Introduction to Data Analytics from IBM, Foundations: Data, Data, Everywhere from Google, and Google Data Analytics. These courses introduce core ideas such as asking data-informed questions, preparing data, analyzing results, and sharing insights. If you want to build tool-specific skills early, Excel Skills for Data Analytics and Visualization from Macquarie University or Microsoft Data Analysis with SQL, Excel & Power BI may also be helpful. Comparing course descriptions, skill lists, and difficulty levels on Coursera can help you choose a starting point that matches your background.‎
Data analytics courses typically cover data collection, data cleaning, exploratory analysis, visualization, basic statistics, and communicating insights. Many courses also introduce tools such as spreadsheets, SQL, R, Power BI, or other analytics platforms used to work with real datasets. For example, IBM Data Analytics with Excel and R focuses on Excel and R, while Microsoft Data Analysis with SQL, Excel & Power BI emphasizes common business analysis tools. Coursera course selections let you choose between broad introductions, tool-focused training, and more advanced analytics topics as your skills develop.‎