How We Compare Schools: The Method Behind Our Data Science Comparisons

For each programme we record the same fields: format, length, price, next intake, entry requirements, curriculum, portfolio or capstone, job support, accreditation or registration, and where reviews of the school live. Each field keeps the address of the page it came from and the date we read it.

The comparisons built from this are the best data science courses in Kenya, the best data science bootcamps in Africa and data science degree vs bootcamp in Kenya. If you are new to the field, the data science career map for Kenya explains the roles first.

First, the provider's own website: the programme page, its fee table or brochure, and its FAQ. Where a site refuses automated reading or leaves a gap, we use a named third party: a regulator's list such as KUCCPS's degree programmes or CUE's accredited programmes, a review site such as Course Report or SwitchUp, or a named news outlet. The comparison says which source each row uses.

We never estimate. If a school does not publish its fee, the table says "Not published" and links the page we checked. When two pages from the same school disagree, we quote both and say so, so you know what to ask.

A claim the school makes about itself, such as an accreditation or a placement rate, is reported as its claim. We quote a placement rate only when the school gives the date, the cohort and how it was counted.

In our first round, on 4 November 2026, we checked 112 programmes, our own included, and left out 28. A programme is left out when we cannot verify that it runs today, when it has closed or its pages are gone, when it is not a data science, analytics or AI programme, or when it is built for a different audience, such as a summer study-abroad course for overseas undergraduates. Programmes that admit only their own country's residents stay in, with that rule stated, because readers from that country need them.

Where a well-known school is missing, the comparison names it and says why, so the gap is visible rather than silent.

Our method gives no single score, so lists are alphabetical, grouped by country where that helps. No school pays to appear or to move up. Our own programme is never placed first by default; if a stated method ever put it first, the page would say why in writing.

The "Best for" lines pick one option per kind of learner, such as career changers or KCSE leavers, and give the reason from the facts in the table. They are judgments, and we label them as ours.

We copy each price exactly as published, in the provider's currency, with every payment plan we can see, because instalment plans often raise the total. KES equivalents use the Central Bank of Kenya's indicative rate on the day we checked; for the naira and the cedi we go through each central bank's dollar rate. Subscriptions are shown per month or per year, as the provider bills them.

Every programme, with its price in both currencies, is in the data science course price tracker, which you can download as a spreadsheet.

Every row is rechecked within 90 days. A script lists any row older than that, and when we recheck we update the facts and the "Last checked" date and add a line to the tracker's changelog. A date changes only when the facts behind it were read again.

McTaba runs coding and data bootcamps in Kenya. This guide is written to be useful whether or not you ever join one.

Our founder led software engineering at Zindua School from January 2023 to February 2024.

Because we sell a data science programme, our row goes through the same template as everyone else's, limits included: our first cohort starts on 11 January 2027, we have no graduate outcomes yet, and we hold no TVETA accreditation. The programme itself is described on the Data Science to AI Engineering page.

Spotted an error, or run a school we missed? Email hello@mctaba.com with the page that shows the fact. We recheck the row, correct it if needed and log the change. More guides are in the data science hub; if a bootcamp is your route, the plan for ours is on the Data Science to AI Engineering page.