Data Analysis with Python Certification
Data Analysis with Python teaches the standard Python toolkit for working with tables of data: NumPy, pandas, Jupyter notebooks and the plotting libraries, applied in five projects on real datasets.
It now lives in freeCodeCamp's archive. You can still earn it, but nobody is maintaining it, and it has no exam.
Certificate facts
- Level
- Associate
- Field
- Data & AI
- Access
- Free
- Assessment
- Graded projects
- Languages
- English
- Price
- Free (read 26 September 2026)
- Validity
- never expires
- Exam delivery
- Unproctored online exam in freeCodeCamp's own open-source Exam Environment desktop app, every attempt reviewed by staff; legacy and archived certifications by project submission only
Prerequisites: None formally. The projects assume you can write basic Python; freeCodeCamp's own project pages point beginners to a separate introductory Python video course first
Renewal: None. freeCodeCamp says claimed certifications stay yours; this one is in the archive, still claimable, but its content is no longer updated
Source: certificate page at freeCodeCamp · Price: Course, projects and certificate cost nothing; freeCodeCamp is funded by optional donations
How to prepare
1. The vendor's free learning path
freeCodeCamp publishes the exam objectives and a learning path free of charge — the authoritative source for scope and weighting. Open the learning path (opens in a new tab)
2. The programme
The certificate is earned inside this programme. Its facts, price and the provider's own page are on the course page; the link there carries no commission.
Affiliate disclosure: the course link above is an affiliate link — buying through them may earn us a commission at no extra cost to you. The vendor's learning path and booking links carry no commission.
Archived, not retired
freeCodeCamp moved this certificate to its archive when it rebuilt the main curriculum. It remains claimable, and anyone who earns it keeps it, but the page carries a notice that the content is no longer updated. Library versions, datasets and instructions will drift over time, and support on the forum may thin out. Earn it for the practice; do not expect it to be refreshed.
Five projects and your word
The credential rests on five projects, each supplied as starter code with a file of unit tests. You write the analysis, run the tests yourself, and submit a link to your project with a confirmation that it is complete. No exam follows, and nobody reviews the code unless something prompts an audit under freeCodeCamp's honesty pledge, which requires that the code be your own and allows the team to replace a certificate with a public notice if plagiarism is found. In other words, the tests confirm your output matches what was asked; your signature confirms you wrote it. That makes this certificate weaker evidence than the exam-backed ones in the current curriculum, and it is worth being candid about that on a CV.
| Project | Focus, as the brief and title indicate |
|---|---|
| Mean, variance and standard deviation calculator | NumPy arrays, axes and summary statistics |
| Demographic data analyzer | Answering questions about a table with pandas |
| Medical data visualizer | Turning a dataset into charts |
| Page view time series visualizer | Plotting a series over time |
| Sea level predictor | Projecting a trend forward from historical data |
What the course actually teaches
The learning material is a set of recorded lessons rather than interactive steps: notebooks, NumPy, pandas indexing and selection, creating columns, handling duplicates and missing values, reading data from CSV and text files, from databases and from web pages, and a brief Python refresher. The project pages also point to longer freeCodeCamp video courses for anyone who needs Python basics or more pandas practice before starting. The toolkit is the right one: data wrangling with pandas and data visualisation with Python plotting libraries are still what most analysis in code looks like.
- Take it if you already know some Python and want a structured reason to practise pandas on real data.
- Take it as a bridge between spreadsheets and code: every project is something you could do in a spreadsheet, done reproducibly instead.
- Look elsewhere if you need a credential that proves you sat a test, or want statistics and modelling taught properly. This course touches statistics only lightly.
freeCodeCamp's configuration credits the certificate with three hundred hours. For someone who already writes Python, the five projects are far less than that; the figure makes more sense if you count the introductory video courses the project pages recommend.
If you are choosing between this and the current curriculum, note that freeCodeCamp's main learning page now offers a Python certificate of its own, built on the new model with interactive lessons, five projects and an exam. It teaches the language rather than the analysis libraries, which makes it a sensible first step. Earn that, then come back here for pandas and plotting practice.
What a question looks like
Written by us in the exam's style. It is not a real question from any question bank, and we do not publish those.
A dataset of daily page views contains a few extreme spikes caused by a bot. You are asked to plot the monthly average without those days distorting the picture. Which step belongs before the grouping by month, and why?
The mechanics are easy once you know them. The judgement is not: you have to decide what counts as an outlier and remove it before aggregating, because averaging first bakes the spike into every monthly figure. The projects are full of small ordering decisions like this.
What it costs to get and to keep
| Item | Amount | Note |
|---|---|---|
| Course, projects and certificate | 0 USD | free; donations are voluntary (read 26 September 2026) |
| Renewal | not published | none; claimed freeCodeCamp certificates do not expire (read 26 September 2026) |
How much preparation, from where you are
- Comfortable with basic Python
- The intended reader. The projects are the real work; the video lessons are worth skimming for pandas idioms.
- Analyst who lives in spreadsheets
- Do an introductory Python course first. After that, this is one of the better free bridges into analysis in code.
- Already using pandas at work
- Little to gain beyond a line on a profile.
What passing this does not prove
- Anything under exam conditions: there is no test beyond the unit tests you run yourself.
- Statistics beyond the descriptive measures and simple trends the projects use.
- Business intelligence tools, dashboards or communicating findings to stakeholders.
- SQL in any depth, beyond reading data from a database into pandas.
Against the alternatives
- Microsoft Certified: Power BI Data Analyst Associate (PL-300)
- A paid, proctored Microsoft exam for Power BI analysts, with an annual renewal. It is a hiring filter in organisations that run on Microsoft's stack; this certificate is not a filter anywhere. Choose this one to learn analysis in code for free, and that one when an employer's tooling and job adverts name Power BI.
- Relational Databases Certification
- A current freeCodeCamp certificate with an exam, teaching SQL rather than pandas. Analysts benefit from both; if you must choose, SQL is the skill more job adverts ask for.
Data Analysis with Python Certification — quick answers
Can I still earn Data Analysis with Python?
Yes. It is in freeCodeCamp's archive, which keeps it claimable, but the content is not being updated.
Is there an exam?
No. You complete five projects, run their unit tests yourself and submit the project links. The newer freeCodeCamp certificates add an exam; this one never received one.
Is it free?
Entirely. Lessons, projects and the certificate cost nothing.
Will it help me get a data analyst job?
It shows you practised the standard Python tools on real data, a fair signal at the start of a career. Employers screening analysts tend to look for SQL, a BI tool and a portfolio, so pair it with those.
Where this certificate sits in the field
What comes next
Concepts this certificate draws on
Glossary entries with the reason each one matters for Data Analysis with Python Certification.
- Data Analysis
The certificate's whole subject.
- Python
All projects use Python with NumPy and pandas.
- Data Wrangling
Data cleaning, duplicates and reading from CSV, SQL and HTML.
- Data Visualization
Three of the five projects are visualisers.
Last reviewed 26 September 2026 · Getting Digital