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590 Best + Free Data Science Courses & Certificates [2026]
Ranked by Michael Kuhlman, CourseDuck's founder, from student reviews across every provider. How we rank · Embed this list
Our guide: The 10 Best Data Analysis Courses on Udemy in 2026
Our top picks
- Tableau A-Z: Hands-On Tableau Training for Data Science [Udemy]
- The Data Science Course: Complete Data Science Bootcamp 2026 [Udemy]
- Python for Data Science and Machine Learning Bootcamp [Udemy]Editor's Choice
- Machine Learning, Data Science & AI Engineering with Python [Udemy]
- R Basics - R Programming Language Introduction [Udemy]
- Data Science A-Z: Hands-On Exercises & ChatGPT Prize [2026] [Udemy]Best Paid Course
- 100 Days of Codeâ„¢: The Complete Python Pro Bootcamp [Udemy]
- Python Mega Course: Build 20 Real-World Apps and AI Agents [Udemy]
- SQL - MySQL for Data Analytics and Business Intelligence [Udemy]
- R Programming A-Zâ„¢: R For Data Science With Real Exercises! [Udemy]
About the best Data Science courses
Frequently asked questions
The most-reviewed Data Science course in this category is The Data Science Course: Complete Data Science Bootcamp 2026 by 365 Careers, with about 162,000 reviews at 4.5 as of October 2026.
Data science is the field of using statistics, programming and domain knowledge to collect, clean and analyze data and draw conclusions from it. Its work includes visualization, machine learning and reporting. Courses here cover Python and R for data science, statistics, Tableau and Power BI, machine learning and natural language processing.
- Average
- $119,031 a year
- Middle half earn
- $61,500 to $163,000 25th to 75th percentile
- Full range
- $23,000 to $221,000
Share of US job postings in each pay band; the dark bar holds the average, the striped bars the 25th and 75th percentiles. Source: ZipRecruiter salary data collected in 2020-21, when this FAQ was first written; pay has moved since, so treat it as a rough guide.
Paid Udemy video courses include a certificate of completion when you finish; free courses and practice-test-only courses do not. It shows you did the work, but it is not an accredited qualification. Coursera and edX usually charge for a certificate, issued with the university or company that made the course.
Provider
University
Tags
Rating
Duration
Difficulty
Publication Year
Language
1
Tableau A-Z: Hands-On Tableau Training for Data Science (2025)
Kirill Eremenko's beginner-friendly Tableau course, 8.6 hours across 77 lectures, refreshed in 2025, with over 100,000 reviews averaging 4.7 stars.
Best for: Complete beginners who want to build charts and dashboards in Tableau from the first lecture, with a new dataset each section.
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- Hands-on from lecture one: each section brings a new dataset and a finished chart or dashboard
- Joins get a clear, careful explanation, which a reviewer singles out
- Short lectures (77 in 8.6 hours) make it easy to stop, rewind and revisit a topic
- Refreshed in February 2025 and 16 caption tracks, with a 4.7 rating over 107,000 reviews
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- Kirill moves fast and clicks without narrating, so beginners pause and rewind a lot
- Some datasets must be fetched from Kaggle or another site instead of Udemy
- The data extract lesson needs paid Tableau, which the video doesn't say
2
The Data Science Course: Complete Data Science Bootcamp 2026
A 32-hour, theory-first path from probability and statistics through Python to regression, clustering and TensorFlow, aimed squarely at people starting from zero.
Best for: Beginners who want the math and statistics explained before touching a machine learning library.
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- Probability and statistics get about seven hours of real teaching before any Python appears
- 274 quizzes and 130 coding exercises; reviewers say the quizzes make the material stick
- Pace is praised as neither too fast nor too slow for absolute beginners
- Updated September 2026; an earlier CourseDuck review found Q&A responses fast and reliable
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- Long and theory-heavy up front; several low-star reviews lost interest before the practical parts
- One reviewer says the coding exercises are strict about exact answers and don't match the video examples
- Machine learning sections lean on running code without the math depth the statistics sections had
3
Python for Data Science and Machine Learning Bootcamp (2020)
Udemy's Bestseller-badged Python data science bootcamp, taking you from pandas through scikit-learn to a first neural net in about 25 hours, if you can live with 2020-era tooling.
Best for: People who already code a little and want one course covering pandas, plotting and every classic ML algorithm.
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- A code notebook for every lecture, so students run the code rather than just watch it
- Pandas section and the visualization libraries are singled out by reviewers as highlights
- Covers regression, trees, SVMs, k-means, NLP, neural nets and Spark in one place
- Q&A section that reviewers call very useful when they get stuck
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- Last updated May 2020; Plotly/Cufflinks, PySpark and some Seaborn calls no longer work as shown
- Long on videos, short on practice: one quiz and no coding exercises across 165 lectures
- Decision trees and the deep learning section feel rushed to several reviewers
4
Machine Learning, Data Science & AI Engineering with Python (2026)
Frank Kane's 20-hour survey runs from a Python and stats refresher through classical ML to GPT, RAG and LLM agents, refreshed August 2026 and rated 4.6 by nearly 37,000 students.
Best for: Working programmers who want one broad, current tour of machine learning plus generative AI before picking a specialty.
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- Covers GPT, the OpenAI API, RAG and LLM agents, with the content refreshed in August 2026
- Reviewers say the instructor speaks slowly and clearly and the setup steps and notebooks just work
- About 20 hours across 148 lectures, from a stats refresher to Spark MLlib and deep learning
- 4.6 stars from nearly 37,000 reviews, roughly 90 percent of them 4 or 5 stars
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- Several reviewers say the instructor reads from notes rather than building intuition
- A long statistics and probability stretch comes before the real projects begin
- Some download links have gone stale, and there is no full LLM or agents project
5
R Basics - R Programming Language Introduction (2018)
A free, four-hour R starter from the R-Tutorials team that walks through RStudio, packages, data import and basic graphs at a slow, beginner-friendly pace.
Best for: Total beginners who want a free, slow first look at RStudio, packages and basic plots.
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- Slow, plain-spoken pacing that reviewers say suits true beginners
- Covers RStudio setup, packages, data import, loops and basic graphs in about 4 hours
- Downloadable course script lets students follow along and apply the code
- Free, with about 230,000 students and a 4.6 rating from 19,341 reviews
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- Last updated in 2018, so the tooling and screens are older
- One reviewer found the narrator's articulation and accent hard to follow
- Occasionally rushes into advanced plotting or machine learning without enough setup
![Data Science A-Z: Hands-On Exercises & ChatGPT Prize [2026]](../../programming/data-science/images/513244_b831_4.jpg?v=1789268131)
6
Data Science A-Z: Hands-On Exercises & ChatGPT Prize [2026]
A tool-driven tour of a full analytics project, from Tableau charts and regression in Gretl to SQL Server cleanup and presenting to stakeholders, with no Python or R.
Best for: Beginners or analysts who want the whole project pipeline in Tableau, SQL and regression, not a coding course.
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- Covers the full project flow: Tableau, regression, SQL Server cleanup and presenting
- Step-by-step teaching that beginners say is simple to follow
- Hands-on practicals, and updated as recently as January 2026
- Big, well-rated audience: 4.7 stars from nearly 35,000 reviews
-
- Microsoft and Tableau versions have moved on, so screens may not match the videos
- At 21.2 hours, some reviewers find it padded and slow-going
- Tools are Tableau, Excel, Gretl and SQL Server, with no Python or R coding
7
100 Days of Code: The Complete Python Pro Bootcamp (2026)
A project-a-day Python bootcamp from zero to Flask, APIs and a taste of data science, with 1.9 million students and a 4.7 rating, though reviewers say the later days need a refresh.
Best for: Complete beginners who need a daily habit and a small finished project every session to stay motivated.
-
- A concrete build every day: Hangman, Blackjack, Snake, a password manager, then API and Flask projects.
- Reviewers repeatedly praise Angela Yu's clear explanations and the pep talk at the end of each module.
- 41 quizzes, 23 coding exercises and 19 assignments keep it hands-on instead of watch-only.
- Updated September 2026, and the first 30 or so days draw almost no complaints.
-
- A two-star reviewer says API lessons from around day 33 onward no longer work because the services changed.
- Later web and backend days lean on text articles instead of video walkthroughs, which frustrates some students.
- One beginner finds the pace fast; another reviewer complains about switching IDEs and installing lots of software.
8
Python Mega Course: Build 20 Real-World Apps and AI Agents (2026)
Ardit Sulce teaches Python by having students build 20 real apps, from desktop GUIs to LangChain AI agents, instead of drilling syntax alone.
Best for: Complete beginners who want to build real apps instead of memorizing syntax rules first.
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- 20 real apps built step by step, including AI agents with LangChain
- Nearly 375,000 students and nowhere near typical Udemy-course review counts (73,000+)
- Explanations use analogies that reviewers say make hard concepts click
- Updated September 2026, so tooling and AI content aren't stale
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- Some projects are missing downloadable source code and lecture resources
- The AI agent and LangChain section feels rushed compared to core Python chapters
- Covers a lot of ground quickly, so some topics only get surface treatment
9
SQL - MySQL for Data Analytics and Business Intelligence (2026)
A 12-hour MySQL course from 365 Careers that teaches SQL through business questions on a real employees database, with 157 quizzes and 123 coding exercises along the way.
Best for: Aspiring data analysts and BI people who want SQL practice tied to business questions, not database administration.
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- 157 quizzes and 123 coding exercises spread across 12 hours, so almost every topic gets practiced right away
- Built around one realistic employees database, so joins and subqueries feel like actual analyst work
- Concise explanations with little filler, according to several 4 and 5 star reviews
- Updated September 2026 and still actively maintained nine years after launch
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- Later sections get much harder to follow, and one reviewer says the tutor rushes through the end
- Audio freezes and cut-outs reported in some lectures, plus one dead database download link
- Delivery is scripted and impersonal, and Q&A replies can take over a week
10
R Programming A-Z: R For Data Science With Real Exercises! (2025)
A slow, step-by-step R starter that takes true beginners from RStudio basics through matrices, data frames and ggplot2 charts in about 10 hours, with homework throughout.
Best for: Complete beginners who want R explained slowly, with homework after each new idea.
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- Slow, step-by-step build-up that reviewers say never overwhelms a new learner
- Works for people with no coding background, including first-time programmers
- A 16-lecture ggplot2 section teaches chart building after the basics are in place
- Homework comes with seven solution videos, so stuck learners can check their work
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- Some homework data sets are reported missing or corrupted, which blocks later exercises
- Last updated July 2025, and reviewers say some functions have changed since recording
- Early programming sections and if/else statements lost a few beginners; experienced coders may find it slow
11
Statistics for Data Science and Business Analysis (2024)
A short, visual statistics primer with Excel templates that runs from descriptive stats to hypothesis testing and regression in under five hours.
Best for: Beginners heading into analyst roles who want a fast, visual tour of statistics with no math background.
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- Visual explanations with graphics that reviewers find clear and enjoyable
- Short videos and about 4.9 hours total, so it is easy to finish
- Covers descriptive stats through regression with dummy variables
- No experience required, and Excel templates and course notes are included
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- Fast pace, and some formulas and calculations are not fully explained
- Math is thin, for example no derivation behind SST=SSR+SSE
- Quizzes after short videos break the flow, and some lack context