Affiliate Disclosure: Some Coursera links in this article use an affiliate identifier, which may earn RIA LLC a commission at no extra cost to you. Our conclusions remain independent, and we do not accept payment for a positive conclusion. See our editorial policy and affiliate disclosure.
Part of our Online Learning and Career Change Guides library.
Pricing and verdict · Verified August 24, 2026
Coursera is the safest first platform for most beginners (Google Data Analytics at about $49 a month, or Plus at $399 a year); DataCamp, 365 Data Science, edX and Udacity each win for one specific gap.
Five platforms, five gaps. Coursera gives a recognised credential and a capstone; DataCamp (roughly $25 a month billed annually) gives typing-first practice; 365 Data Science ($29 a month billed annually, 30-day money-back guarantee) gives one structured curriculum; edX gives university theory at per-course prices with free audit; Udacity is the premium-priced option for project review. None guarantees a job, and the 30-day plan below uses the free tiers so you pay for at most one.
The best platform to learn data science: the short answer
For most people starting out, Coursera is the safest first platform, because the Google Data Analytics Professional Certificate gives you a recognised credential, a capstone project and a clear finish line for about $49 a month, or as part of Coursera Plus at $399 a year. It is not the best at everything. DataCamp is better for daily coding practice, 365 Data Science is better for a single structured data-science curriculum, edX is better when you want a university course and per-course pricing, and Udacity is the premium-priced option for project-heavy programs with human feedback.
There is no platform that is best for everyone, and the honest first step is to decide what you are missing: a credential, coding fluency, structure, theory or reviewed projects. The comparison table below maps each platform to one of those gaps, and the 30-day starter plan uses the free tiers so that you pay for at most one of them, and only after you have evidence you will keep going.
See the Google Data Analytics certificate on Coursera →
How this roundup was prepared
This is a documentation-based roundup. We did not complete a data-science program on each of the five platforms and grade them against each other. The prices and features below are based on the official pricing and product pages checked on August 23–24, 2026, together with the vendors' public help pages. Where a figure was not available on the same date, we describe the platform qualitatively and tell you to check the vendor's pricing page.
Coursera is the brand with affiliate links in this roundup. DataCamp, 365 Data Science, edX and Udacity links are plain. That has not shaped the "best for" labels: three of the five gaps in the table below point away from Coursera. Prices are US list prices; all five platforms use regional pricing or promotions, so the checkout figure may differ.
Five gaps, five platforms
Data-science learners usually stall for one of five reasons, and each platform is built around one of them.
- No credential. You can do the work but have nothing an employer recognises. Coursera's Professional Certificates from Google, IBM and Meta are the answer here.
- No fluency. You understand the concepts and freeze at a blank script. DataCamp's typing-first exercises address this directly.
- No structure. You have bookmarks, not a path. 365 Data Science's career tracks sequence statistics, Python, SQL and machine learning for you.
- No theory. You can run a model and cannot explain it. edX's university courses, often free to audit, fill that gap at per-course prices.
- No reviewed projects. You have built things and nobody qualified has looked at them. Udacity's project-based programs position human feedback as the product, at a premium price.
Most people have two of these gaps. Pick the platform for the bigger one first.
Comparison table
| Platform | Best for | US list price | Free way in | Credential weight |
|---|---|---|---|---|
| Coursera | A recognised credential and a structured program | About $49/month per Professional Certificate (typically 3–6 months); Coursera Plus $59/month or $399/year | 7-day free trial on certificates and Plus Monthly | Google, IBM, Meta and university names |
| DataCamp | Daily, typing-first coding practice | Premium roughly $25/month billed annually (about $300/year); month-to-month meaningfully higher | First chapter of every course free | Platform certifications, respected within data roles |
| 365 Data Science | One structured data-science curriculum | Self-Study $29/month billed annually or $36/month monthly | Free plan with previews, 51 projects, 1 mock interview; 30-day money-back guarantee | Platform certificates |
| edX | University courses and theory at per-course prices | Audit free; verified certificates roughly $50–$300 per course; programs roughly $200–$1,000+ | Free audit of most courses | University names such as Harvard and MIT on verified certificates |
| Udacity | Project-heavy programs with human review | Premium-priced: roughly $249/month monthly or lower on longer terms at the time of writing | Check the vendor's page | Nanodegree credential |
Coursera: best for a recognised credential
Coursera is a catalogue of 10,000+ courses, Guided Projects, Specializations and Professional Certificates from university partners including Stanford, Yale, Michigan and Imperial, and from companies including Google, Meta and IBM. For data-science beginners, the entry point is the Google Data Analytics Professional Certificate: 9 courses covering data cleaning, analysis, visualisation, spreadsheets, SQL, R and Python basics, data ethics and storytelling, with a capstone case study for a portfolio. Google states it takes about 6 months at 10 hours a week and that most learners finish for less than $300.
Pricing is $49 a month for the single certificate after a 7-day free trial, or $399 a year for Coursera Plus, which includes most Professional Certificates with unlimited certificates on completion; Plus excludes degrees, MasterTrack certificates and certain programs. Our Coursera Plus guide runs the break-even maths: Plus pays off if you will complete three or more programs in a year.
Honest caveats
Google's claims, which we report as Google's claims, are that graduates can apply directly to jobs with Google and 150+ US employers and that 75% of certificate graduates report a positive career outcome within six months, from a self-reported survey. What the certificate does not do is guarantee a job; the entry-level analyst market is competitive, and the certificate is recognised but not a substitute for a portfolio and SQL fluency. The hands-on share of each hour is lower than on DataCamp, and an analytics certificate is not a data-science curriculum: statistics and machine learning are thinner here than on 365 Data Science or edX.
DataCamp: best for daily coding practice
DataCamp is built around an in-browser code editor. Every course puts you in it within minutes, with exercises checked automatically. Premium includes 790+ courses, projects, career tracks such as Data Analyst with Python, certifications, skill assessments and a mobile app. The first chapter of every course is free on the Basic plan, without certificates. US buyers pay roughly $25 a month billed annually, about $300 a year, at the time of writing; month-to-month is meaningfully higher, with sources varying between $39 and $49, and a student plan is advertised at over 50% off.
Honest caveats
DataCamp is weak on theory depth; you can complete a regression course and not know when not to use one. Its certificates carry little weight outside data roles. And because exercises are scaffolded, some learners finish tracks and still struggle with an empty script, so you must build projects outside the platform. It is a gym, not a school, and it is excellent as a gym.
365 Data Science: best for one structured curriculum
365 Data Science takes the opposite approach to a catalogue. The Self-Study plan includes 133 courses sequenced into 12 career tracks, 51 projects, certificates, AI mock interviews, portfolio feedback, priority support and a learning-break option that pauses the subscription. It costs $29 a month billed annually, advertised as a 20% saving, or $36 a month monthly, with a 30-day money-back guarantee. The free plan costs nothing, needs no card, and includes course previews, all 51 projects, exercises, practice exams, career resources and one AI mock interview.
Honest caveats
The catalogue is small next to Coursera's 10,000+ or DataCamp's 790+, the certificates are platform certificates rather than employer-branded credentials, and there is nothing here outside data. For a beginner who wants the order of learning decided for them, it is the most curriculum-like of the five. For someone who needs a brand on the certificate, it is the wrong buy.
edX: best for university courses at per-course prices
edX hosts courses from university partners such as Harvard and MIT, mostly self-paced. Most courses are free to audit; a verified certificate costs roughly $50–$300 per course, and professional or MicroMasters programs run roughly $200–$1,000 or more. Because pricing is per course or program rather than a subscription, abandoning a course costs less than abandoning a year of Coursera Plus. Check the specific course page, as prices vary widely.
Honest caveats
edX is the best place in this list for the theory gap, such as a proper statistics or probability course from a university, but it is not a coherent career path: you assemble your own sequence. The per-course model can also become expensive if you want verified certificates for many courses. It suits learners who already know what they are missing.
Udacity: best for project-heavy programs with human review
Udacity positions its Nanodegree programs as project-based learning with human project review and support, built with industry partners, in fields including data analysis, data science and machine learning. It is premium-priced: roughly $249 a month on monthly billing, or lower on longer terms, at the time of writing, according to our existing guide. We describe it qualitatively here; check the program page for current pricing and inclusions.
Honest caveats
At that price, Udacity only makes sense if you will use what you are paying for: reviewed projects and a structured sprint. For a beginner who is still finding out whether they like data work, it is the expensive way to learn that. For someone who has done a Coursera certificate or a DataCamp track and now needs reviewed portfolio work, it is a rational upgrade. Compare it with the project and feedback features on 365 Data Science first, which cost a fraction as much.
Who should not pay anyone yet
Several readers should close all five checkout pages for now.
- You have not used the free tiers. Coursera's 7-day trial, DataCamp's free first chapters, 365 Data Science's free plan and edX's free audit together give you a month of real signal for $0. The starter plan below sequences them.
- You cannot name the job. "Data science" spans analyst, engineer, scientist and machine-learning roles, and the platforms suit them differently. Pick a role title before picking a platform.
- You need a degree. None of these subscriptions includes one. Coursera and edX offer degrees separately at a very different price, which is a different decision.
- Your gap is a portfolio, not knowledge. If you can already write the code and interviews are not happening, another subscription will not fix that. Build two public projects on real data instead, and consider Udacity or 365 Data Science's feedback only if you need review.
- You have fewer than five hours a week. Google's estimate for its certificate is 10 hours a week for 6 months. At under five, every subscription here gets expensive per hour of actual study. Start with the free material and see whether the hours appear.
A 30-day starter plan using the free tiers
The aim is to spend $0 for most of the month and to pay, at the end, for at most one platform, with evidence.
Days 1–7: DataCamp free chapters and an edX audit
- Create a free DataCamp account and complete the first chapter of an introductory SQL course and an introductory Python course. Note whether typing from minute one suits you.
- Audit one introductory statistics course on edX for free and watch the first week. Note whether you want the theory or find yourself skipping it.
Days 8–14: Coursera 7-day trial
- Start the 7-day free trial on the Google Data Analytics certificate, or on Coursera Plus Monthly if you also want to sample courses outside data. Set a reminder for day 13 so it does not convert by accident.
- Complete the first week of the first course at your real pace and count the hours. If a week takes you well over 10 hours, the 6-month estimate will stretch and the per-month pricing gets costlier.
Days 15–21: 365 Data Science free plan
- Create the free account, no card required. Watch previews in the career track that matches your target role, attempt one of the 51 projects, and use the one free AI mock interview.
- Decide whether you want the order of learning chosen for you. If yes, this is your structure platform.
Days 22–30: decide and pay once
- Name your bigger gap from the five above. Credential: keep or restart the Coursera subscription at $49 a month, or Coursera Plus if you will complete three or more programs. Fluency: DataCamp Premium on the annual price. Structure: 365 Data Science Self-Study, protected by its 30-day guarantee. Theory: pay for one edX verified certificate only if you need the paper. Reviewed projects: consider Udacity only after one of the others.
- Cancel anything you are not keeping before its trial converts. Certificates earned during Coursera Plus Annual's 14-day refund window are revoked if you refund.
- Commit to one platform for 90 days before adding a second. Two subscriptions with five study hours a week is how people end up paying for none of the learning.
If the credential gap is the bigger one, which it is for most career changers, start the Google Data Analytics certificate and use DataCamp's free chapters alongside it. Our guide to the best learning platforms for a career change covers the non-data paths.
Check current Coursera Plus pricing →
Frequently asked questions
What is the best platform to learn data science for beginners?
For most beginners who need something to show an employer, Coursera's Google Data Analytics Professional Certificate is the safest start: a structured 9-course program with a capstone, about $49 a month after a 7-day trial, which Google says most learners finish for less than $300. Beginners who mainly need coding repetitions do better on DataCamp, and those who want the order of learning decided for them do well on 365 Data Science.
Which data-science platform is cheapest?
On the pages checked August 23–24, 2026, the cheapest paid subscriptions are DataCamp Premium at roughly $25 a month billed annually and 365 Data Science Self-Study at $29 a month billed annually. edX can be cheapest of all if you audit for free and never buy a certificate. Coursera is about $49 a month per certificate or $399 a year for Plus, and Udacity is premium-priced at roughly $249 a month on monthly billing at the time of writing.
Is Coursera or DataCamp better for data science?
Coursera is better for a recognised credential and for theory; DataCamp is better for daily coding practice. For a data career, many learners use both, with the Coursera certificate as the CV line and DataCamp as the gym. See our guide to the Coursera Plus break-even maths before choosing between a single certificate and Plus.
Can I learn data science for free?
You can learn a large part of it for free. edX lets you audit most courses at no cost, DataCamp's free plan includes the first chapter of every course, 365 Data Science's free plan includes previews and 51 projects, and Coursera offers 7-day trials. What you cannot get for free is the certificate, and on DataCamp's free plan there are no certificates at all.
Does a data-science certificate get you a job?
No certificate guarantees a job. Google's own claim for its Data Analytics certificate is that 75% of graduates report a positive career outcome within six months, from a self-reported survey, and that graduates can apply to Google and 150+ US employers. The entry-level analyst market is competitive, and employers look for a portfolio and SQL fluency alongside any certificate.
Is Udacity worth the price for data science?
Only if you will use the human project review and structured sprint it is built around. At roughly $249 a month on monthly billing at the time of writing, it is the premium option here, and a beginner still deciding whether they like data work is better served by the free tiers and a cheaper subscription first. Check Udacity's program page for current pricing, as we describe it qualitatively.
Fact-checking note: official Coursera, DataCamp, 365 Data Science, edX and Udacity pricing and product pages were reviewed August 24, 2026. Reconfirm prices, plan limits, and features before purchase.