What are the best data science courses online?

Browse the data science courses below—popular starting points on Coursera. Python for Data Science, AI & Development: IBM What is Data Science?: IBM IBM Data Science Professional Certificates: IBM Data Science Fundamentals Part 1: Unit 1: Pearson Databases and SQL for Data Science with Python: IBM Foundations of Data Science: Google Python Project for Data Science: IBM Applied Data Science with Python: University of Michigan

What skills can I learn in data science courses on Coursera?

Data science courses on Coursera cover a comprehensive array of essential skills including: Fundamentals of data manipulation and data analysis using tools like Python and R Statistical analysis and probability modeling Machine learning techniques, including supervised and unsupervised learning Data visualization and communication using platforms like Tableau and PowerBI Big data technologies such as Hadoop and Spark Deep learning and artificial intelligence concepts Time series analysis for forecasting and trend analysis Data ethics and data privacy best practices

Do I need prior experience in programming to start these data science courses?

No prior programming experience is required to begin beginner data science courses . The curriculum is designed to support learners at various skill levels: Beginners can start with introductory courses on data analysis and basic programming. Intermediate learners can advance to more complex statistical methods and machine learning models. Advanced professionals can specialize in areas like artificial intelligence , deep learning , or big data technologies.

Ready to start learning data science but not sure which course to choose?

Take a short quiz to find the data science course that best fits your goals—whether you're exploring data analysis, Python programming, machine learning, or tools like SQL and Tableau. Take the quiz to discover your ideal starting point.

What data science certifications and credentials are available?

Data science courses on Coursera offer a variety of credentialing options: Professional certificates that demonstrate comprehensive data science skills Specialized course certificates in areas such as machine learning, business analytics, or data engineering Certifications from leading technology companies and academic institutions These certificates can help demonstrate data science skills, employability and career progression.

What career opportunities are available with skills in data science?

Skills in data science can lead to a wide range of career opportunities in various sectors including technology, healthcare, finance, and more: Data Scientist Data Analyst Machine Learning Engineer Business Intelligence Analyst Quantitative Analyst Data Engineers and Database Administrators Professionals in these roles utilize data science skills to extract insights from data, support decision-making, and innovate with new algorithms and predictive models. Discover which data science role suits you best by taking our career quiz !

How can I purchase data science training courses for my team?

Looking to enhance your team's data science skills? Coursera provides tailored enterprise solutions for teams ranging of 5-125 employees. Our offerings include advanced analytics, customized learning paths, and collaborative tools. To explore our data science training options and make a purchase, please visit our Coursera for Teams page.

Best Data Science Courses & Certificates [2026]

Browse
Data Science

Data Science Courses

Data Science courses can help you learn data analysis, statistical modeling, machine learning, and data visualization. You can build skills in programming with Python or R, data cleaning, and interpreting complex datasets. Many courses introduce tools like SQL for database management, Tableau for visual storytelling, and TensorFlow for developing AI models, showing how these skills are applied in real-world projects.

Popular Data Science Courses and Certifications

Status: Free Trial
IBM
Python for Data Science, AI & Development
Skills you'll gain: Data Import/Export, Programming Principles, Web Scraping, Python Programming, Jupyter, Data Structures, Data Processing, Pandas (Python Package), Data Manipulation, JSON, Computer Programming, Restful API, NumPy, Object Oriented Programming (OOP), Scripting, Application Programming Interface (API), Automation, Data Analysis
4.6
Rating, 4.6 out of 5 stars
43K reviews
Beginner · Course · 1 - 3 Months
Status: Free Trial
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
77K reviews
Beginner · Course · 1 - 4 Weeks
Status: Free Trial
Status: AI skills
IBM
IBM Data Science
Skills you'll gain: Exploratory Data Analysis, Data Wrangling, Dashboard, Data Visualization Software, Data Visualization, SQL, Unsupervised Learning, Plotly, Interactive Data Visualization, Peer Review, Supervised Learning, Data Transformation, Feature Engineering, Jupyter, Data Analysis, Data Cleansing, Data Literacy, Generative AI, Professional Networking, Data Import/Export
Build toward a degree
4.6
Rating, 4.6 out of 5 stars
148K reviews
Beginner · Professional Certificate · 3 - 6 Months
Status: Free Trial
Google
Foundations of Data Science
Skills you'll gain: Data Ethics, Data-Driven Decision-Making, Data Analysis, Analytics, Business Analytics, Data Storytelling, Big Data, Data Science, Communication, Stakeholder Communications, Workflow Management, Project Management, Artificial Intelligence
4.7
Rating, 4.7 out of 5 stars
3.6K reviews
Advanced · Course · 1 - 3 Months
Status: Free Trial
IBM
Databases and SQL for Data Science with Python
Skills you'll gain: SQL, Relational Databases, Stored Procedure, Databases, Query Languages, Jupyter, Data Manipulation, Data Analysis, Pandas (Python Package), Transaction Processing, Python Programming
4.7
Rating, 4.7 out of 5 stars
22K reviews
Beginner · Course · 1 - 3 Months
Status: Free Trial
IBM
Introduction to Data Science
Skills you'll gain: SQL, Peer Review, Jupyter, Data Literacy, Data Mining, Data Modeling, Data Collection, Business Analysis, Relational Databases, Stored Procedure, Databases, Data Science, Big Data, Computer Programming Tools, Query Languages, Data Visualization Software, Decision Tree Learning, Predictive Modeling, Cloud Computing, Python Programming
Build toward a degree
4.6
Rating, 4.6 out of 5 stars
101K reviews
Beginner · Specialization · 3 - 6 Months

What brings you to Coursera today?

Start my career

Change my career

Grow in my current role

Explore topics outside of work

Status: Free Trial
Multiple educators
Data Science Foundations
Skills you'll gain: Dashboard, Pseudocode, Jupyter, Algorithms, Data Literacy, Data Mining, Pandas (Python Package), Data Presentation, Correlation Analysis, Web Scraping, NumPy, Data Import/Export, Probability & Statistics, Programming Principles, Predictive Modeling, Computer Programming Tools, Data Science, Unsupervised Learning, Machine Learning, Project Management
4.6
Rating, 4.6 out of 5 stars
116K reviews
Beginner · Specialization · 3 - 6 Months
Status: Free Trial
Johns Hopkins University
Data Science
Skills you'll gain: Shiny (R Package), Rmarkdown, Exploratory Data Analysis, Regression Analysis, Version Control, Statistical Analysis, R Programming, Data Manipulation, Data Cleansing, Data Science, Statistical Inference, Predictive Modeling, Statistical Hypothesis Testing, Data Wrangling, Machine Learning Algorithms, Plotly, Plot (Graphics), Interactive Data Visualization, Machine Learning, GitHub
4.5
Rating, 4.5 out of 5 stars
51K reviews
Beginner · Specialization · 3 - 6 Months
Status: Free Trial
IBM
Data Analysis with Python
Skills you'll gain: Exploratory Data Analysis, Data Wrangling, Data Transformation, Data Analysis, Data Cleansing, Data Manipulation, Data Import/Export, Predictive Modeling, Regression Analysis, Statistical Analysis, Pandas (Python Package), Scikit Learn (Machine Learning Library), Data-Driven Decision-Making, Matplotlib, Feature Engineering, Data Visualization, Data Pipelines, NumPy, Python Programming
4.7
Rating, 4.7 out of 5 stars
19K reviews
Intermediate · Course · 1 - 3 Months
Status: Free Trial
IBM
Python Project for Data Science
Skills you'll gain: Dashboard, Pandas (Python Package), Data Presentation, Web Scraping, Jupyter, Data Analysis, Data Science, Data Processing, Data Manipulation, Python Programming, Data Collection
4.5
Rating, 4.5 out of 5 stars
4.8K reviews
Intermediate · Course · 1 - 4 Weeks
Status: Free Trial
University of California, Davis
SQL for Data Science
Skills you'll gain: Data Governance, SQL, Data Quality, Database Design, Query Languages, Data Manipulation, Data Modeling, Relational Databases, Data Science, Data Analysis, Data Transformation
4.6
Rating, 4.6 out of 5 stars
17K reviews
Beginner · Course · 1 - 4 Weeks
Status: Free Trial
IBM
Data Science Fundamentals with Python and SQL
Skills you'll gain: Dashboard, SQL, Descriptive Statistics, Jupyter, Statistical Analysis, Data Analysis, Probability Distribution, Pandas (Python Package), Data Presentation, Statistics, Data Visualization, Relational Databases, Stored Procedure, Data Import/Export, Data Science, Programming Principles, Computer Programming Tools, Web Scraping, Data Visualization Software, Python Programming
Build toward a degree
4.6
Rating, 4.6 out of 5 stars
74K reviews
Beginner · Specialization · 3 - 6 Months

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

Python for Data Science, AI & Development: IBM
What is Data Science? : IBM
IBM Data Science: IBM
Foundations of Data Science: Google
Databases and SQL for Data Science with Python: IBM
Introduction to Data Science: IBM
Data Science Foundations: IBM
Data Science: Johns Hopkins University
Data Analysis with Python: IBM
Python Project for Data Science: IBM

Frequently Asked Questions about Data Science

Browse the data science courses below—popular starting points on Coursera.

Data science courses on Coursera cover a comprehensive array of essential skills including:

Fundamentals of data manipulation and data analysis using tools like Python and R
Statistical analysis and probability modeling
Machine learning techniques, including supervised and unsupervised learning
Data visualization and communication using platforms like Tableau and PowerBI
Big data technologies such as Hadoop and Spark
Deep learning and artificial intelligence concepts
Time series analysis for forecasting and trend analysis
Data ethics and data privacy best practices ‎

No prior programming experience is required to begin beginner data science courses. The curriculum is designed to support learners at various skill levels:

Beginners can start with introductory courses on data analysis and basic programming.
Intermediate learners can advance to more complex statistical methods and machine learning models.
Advanced professionals can specialize in areas like artificial intelligence, deep learning, or big data technologies.‎

Data science courses on Coursera offer a variety of credentialing options:

Professional certificates that demonstrate comprehensive data science skills
Specialized course certificates in areas such as machine learning, business analytics, or data engineering
Certifications from leading technology companies and academic institutions
These certificates can help demonstrate data science skills, employability and career progression.‎

Skills in data science can lead to a wide range of career opportunities in various sectors including technology, healthcare, finance, and more:

Data Scientist
Data Analyst
Machine Learning Engineer
Business Intelligence Analyst
Quantitative Analyst
Data Engineers and Database Administrators
Professionals in these roles utilize data science skills to extract insights from data, support decision-making, and innovate with new algorithms and predictive models.

Discover which data science role suits you best by taking our career quiz!‎

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.