Data & Analytics
Courses on working with data: querying, modelling, visualisation, and turning measurement into decisions.
Verified courses first, then the rest of the category
Stanford’s introduction to statistics, the foundation under most of the data courses in this catalog. Delivered through Coursera; the browse listing publishes no price.
Not independently verified
An IBM specialization introducing cloud, data and AI to a business rather than a technical audience, for people deciding what to adopt rather than how to build it.
Not independently verified
UC Davis on SQL for analysis specifically, rather than for building applications. Delivered through Coursera; the browse listing publishes no price.
Not independently verified
A general statistics course, broader than the business statistics course in the same catalog and useful before any data analysis work. Free from Saylor, readable as a guest without an account, with a free certificate on completion.
Not independently verified
Emory’s marketing analytics specialization, on measuring marketing rather than executing it. Delivered through Coursera; the browse listing publishes no price.
Not independently verified
The mathematics behind machine learning taught as its own ninety-four hour specialization, for people who want the foundations rather than to take them on trust. Beginner level, from DeepLearning.AI.
Not independently verified
Meta’s marketing analytics certificate, on measurement and attribution across its advertising products. Delivered through Coursera; the browse listing publishes no price.
Not independently verified
W3Schools’ MongoDB tutorial, covering the document database in short written lessons. Free to read without an account, with an optional paid certificate.
Not independently verified
W3Schools’ tutorial on MySQL specifically, as distinct from its language-level SQL course. Short written lessons with runnable queries, free without an account.
Not independently verified
A written tutorial on NumPy, the array library underneath most Python numerical work. Short lessons with runnable examples, published free by W3Schools.
Not independently verified
W3Schools’ tutorial on pandas, the Python library most data analysis work is actually done in. Short written lessons with runnable examples, free without an account.
Not independently verified
Wharton on applying analytics to workforce decisions, sitting between the data and management sections of this catalog. Delivered through Coursera; the browse listing publishes no price.
Not independently verified
A written PostgreSQL tutorial covering the database in short lessons with runnable examples. Published free by W3Schools, with certification available separately.
Not independently verified
Financial analysis taught through Python and statistics rather than spreadsheets, which puts it between the finance and data sections of this catalog. Delivered through Coursera; the browse listing publishes no price.
Not independently verified
A written introduction to R, the language most associated with statistics and data analysis. Short lessons with runnable examples, published free by W3Schools.
Not independently verified
UC Davis’ standalone SQL course, the entry point to its data science sequence. Delivered through Coursera; the browse listing publishes no price.
Not independently verified
A tutorial on SQL as a language rather than on one particular database, taught as short written lessons with queries that run in the page. Free to read without an account, with an optional paid certificate.
Not independently verified
Colorado Boulder’s SQL course, taught as the language rather than around one database product. Delivered through Coursera; the browse listing publishes no price.
Not independently verified
A digital marketing analyst certificate published by Unilever, unusual for being taught by a consumer goods advertiser rather than a platform. Delivered through Coursera; the browse listing publishes no price.
Not independently verified
About this subject
Courses on working with data: the statistics underneath it, the languages and tools used to query and shape it, and the visualisation and communication that decide whether any of it changes a decision. The catalogue covers both ends of this, from spreadsheet fundamentals through to graduate statistics, and the gap between them is wider than course titles suggest.
Guidance
Verification tells you that a course delivers the material it advertises. It cannot tell you whether the methods it teaches suit your data. These are the things worth checking yourself.
A course on a business intelligence product teaches you to operate software. A course on statistics teaches you which questions the software can honestly answer. Analysts need both, and the second is the one people skip, because the first produces visible output faster. A dashboard built on a misunderstanding of sampling is worse than no dashboard.
SQL, Python, R, Excel and the major BI tools all appear in this catalogue and all lead somewhere different. If your workplace runs on spreadsheets, a course in R may be intellectually satisfying and practically irrelevant for a year. If you intend to move into engineering, the reverse. Each listing names the tool in the title or summary.
Hypothesis testing, sampling and regression are where most self-taught analysis goes wrong, because the tools will happily produce a confident-looking number from a method that does not apply. Several courses here teach statistics on its own, and taking one early tends to make everything after it faster.
Analysis that nobody acts on has not finished. The stronger courses in this subject cover how a finding is presented, what a chart encodes and how a recommendation is framed, not only how the calculation is done. It is worth checking whether a course stops at the output.
A course built on a clean teaching dataset is a different experience from one that makes you find, join and repair real data. Both have a place, but only the second prepares you for the part of the job that takes the most time. Where a provider describes exercises or projects, the summary says so.
Standards
The published standard applies unchanged. These are the checks that tend to matter most in this subject.
A verification says nothing about whether the statistical methods taught are appropriate for your data, or whether the conclusions in the teaching examples are sound. We do not review analytical correctness.
Questions
For a great deal of business analysis, yes. Most workplace analysis still happens in spreadsheets, and the courses here treat that as legitimate rather than as a stepping stone. Whether you also need SQL or Python depends on the size and source of your data.
Sometimes. Some courses run entirely in a browser, others assume a licence or a paid tier. Where a provider states what is required we record it, and where they do not, the listing says only what we could confirm.
That is between you and whoever is hiring. We verify that a certificate is described accurately, including its cost and what it requires, and we make no claim about its value in the market.
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