DataCamp · on DataCamp

Data Scientist with Python Career Track

4.7(14,800) on DataCamp·180K enrolled
Beginner 88 hours English Specialization
SkillsPythonStatisticsData manipulationMachine learningPandasData visualisation

Is this course right for you?

Our take
One of DataCamp's flagship routes into data science, a long, structured climb from Python basics to statistics, data wrangling and machine learning.

Good for: Beginners who want a structured, hands-on route into data science with Python.

Skip if: You already know Python data science, or you prefer video lectures.

It all runs on short, interactive, in-browser exercises, which is what makes it approachable for genuine beginners: you write code from the first lesson rather than watch someone else, and over the full track that builds real, job-relevant Python skills.

The catch is the same one that runs through all of DataCamp: the exercises hold your hand, so it's easy to finish a chapter and still stall on a blank script. Pair it with your own projects so the skills transfer, and skip it if you prefer video lectures or already know Python data work.

Access is a DataCamp subscription, roughly $14 a month billed annually, with a limited free tier to start. The tools shift, but the foundations it teaches hold (as of 2026).

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About this course

Data Scientist with Python is one of DataCamp's flagship career tracks — a long sequence of short, interactive courses you complete in the browser. It runs on DataCamp's subscription (around $25–29/month) and totals roughly 88 hours.

Instructor

HB
Hugo Bowne-Anderson
DataCamp instructor

The track features DataCamp's data-science instructors, including well-known names like Hugo Bowne-Anderson, and reflects DataCamp's interactive, code-in-the-browser approach.

Frequently asked questions

Yes. The track starts from Python fundamentals and builds up, so no prior programming or data-science experience is assumed. Because DataCamp is interactive — short lessons followed immediately by hands-on coding in the browser — beginners practise each concept as they go rather than only watching, which suits people starting from zero. It is broad, though, so treat it as a substantial commitment, not a quick course.

It is a browser-based platform: brief video explanations followed by coding exercises you complete right there with instant feedback, no setup needed. This 'career track' bundles many courses into an ordered path. It runs on a subscription — the first chapter of each course is free and there is usually a free-trial week, but finishing the whole track requires Premium, around 25 US dollars a month.

A broad data-science foundation in Python: data manipulation with pandas, visualisation, importing and cleaning data, statistics, working with SQL, and an introduction to machine learning. Across roughly a hundred hours it aims to take you from Python basics to building and evaluating models, so you come away with the practical toolkit a working data scientist uses day to day.

The full track is around a hundred hours of content, self-paced, so realistically a few months for most people alongside other commitments. The interactive exercises take longer than passive video, but that is the point — the time goes into actually writing code. Rushing the exercises undermines the format, so it rewards steady, regular practice over cramming.

For low-friction, interactive practice that builds genuine Python and data-science fluency, it is a strong option — arguably its biggest edge over video-only courses is that you code constantly. Be clear on the limits, though: it teaches skills through tidy exercises, so job-readiness also needs your own projects on messy real data and a portfolio. Use the track to build fluency, then apply it independently.
$29
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