The Tool Desk
Outbyte PC Repair FREEClear out junk files and repair common Windows errorsFree Scan →Outbyte Driver Updater FREEScan for outdated or missing drivers - takes under a minuteDriver Scan →KDnuggets’ April 16, 2019 survey is a historical guide to campus-based master’s programs in data science and related fields across Europe—not a current ranking or a source for today’s tuition. It describes fees for the 2019–20 academic year, converted to U.S. dollars using prices as of April 6, 2019. Use it to understand the programs and cost context it recorded, then verify current details with each university.
What the 2019 Europe survey includes
Dan Clark’s KDnuggets survey, published April 16, 2019, organizes graduate programs by country and gives descriptions, stated durations, tuition figures, and a World University Computer Science rank where applicable. The article describes its entries as campus-based and excludes online degrees.
The programs are not all degrees with “Data Science” in the title. The survey covers related areas including data analytics, business analytics, statistics, machine learning, and data engineering. That variety matters: a shared label such as “analytics” does not establish that two programs teach the same subjects or prepare students for the same work.
How to interpret “best” and the rankings
“Best” is the survey’s editorial framing, not a documented, uniform league table. Some entries include a CS Rank, while others do not; the article does not set out an overall scoring method that makes every program directly comparable. For example, it shows CS Rank 9 for ETH, 15 for Imperial, and 24 for EPFL. Those are examples from individual entries, not a consistent ranking of all listed degrees.
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The survey also reports no common measure of graduate employment, earnings, admissions outcomes, or student experience. Treat any ranking label as limited context, not proof that a program is the best choice for a particular applicant.
What the tuition figures mean
The fee figures refer to the 2019–20 academic year. KDnuggets says it converted tuition to USD using prices as of April 6, 2019, and that the listed figures are for full-time tuition. Most entries do not include living expenses such as housing and transportation. They therefore should not be read as total costs of attendance, and they are not current prices.
Do not compare figures across entries as though they necessarily use the same eligibility categories or fee definitions. Where a program distinguishes EU and non-EU tuition, or uses another statutory or institutional category, the applicant must confirm which rate applies and what it covers with the university.
How to use the survey when comparing programs
Use the historical listings to identify questions worth checking, rather than to make an application or budgeting decision on their own:
- Subject emphasis: Determine whether the curriculum prioritizes data science, business analytics, statistics, machine learning, data engineering, or a particular application area.
- Duration and format: The survey gives individual program lengths, with examples of 12, 18, and 24 months. These are examples, not a complete summary of every program. Confirm current duration, full-time status, and delivery format directly with the institution.
- Location and language: Location can affect both practical costs and fit. The survey notes that EPFL’s program is two years and taught in English, but it does not provide a consistent language field for every entry. Check the current teaching language and campus location for the specific degree.
- Total cost: Ask the university for current tuition for your applicant category, mandatory fees, payment schedule, and any additional program costs. Separately estimate housing, transport, food, insurance, and other living expenses.
- Academic and career fit: Review current admissions requirements, course lists, faculty, project or internship options, and any published outcome information. The survey does not supply a common outcomes measure.
What the article cannot establish today
A 2019 listing does not confirm that a program is still offered, retains the same name or curriculum, accepts applications, or charges the same tuition. It also cannot establish present-day rankings or current admissions rules. Treat it as a snapshot of the 2019–20 academic context and confirm availability, fees, language, duration, and requirements on the university’s own current pages before relying on any entry.
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