Computational Statistics & Data Science
The University of Melbourne ยท VIC ยท MAST90083
Computational Statistics & Data Science is a subject at The University of Melbourne, VIC in School of Mathematics & Statistics. It covers topics like data-science, statistical-computing, statistics. It is part of 11 degrees. The information below is compiled from public course material โ approximate, not official.
The University of Melbourne
MAST90083
12.50
School of Mathematics & Statistics
Topics covered
Degrees that include Computational Statistics & Data Science
- Graduate Diploma in Biostatistics
- Graduate Diploma in Data Science
- Graduate Diploma in Foundational Data Science
- Graduate Diploma in Foundational Data Science
- Master of Biostatistics
- Master of Biostatistics (Enhanced)
- Master of Commerce (Actuarial Science)
- Master of Data Science
- Master of Science (Epidemiology)
- Master of Science (Mathematics and Statistics)
- Ph.D.- Engineering
Frequently asked questions
What is Computational Statistics & Data Science about?
Computational Statistics & Data Science covers topics like data-science, statistical-computing, statistics.
Which degrees include Computational Statistics & Data Science?
Computational Statistics & Data Science is part of 11 degrees, including Graduate Diploma in Biostatistics, Graduate Diploma in Data Science, Graduate Diploma in Foundational Data Science, Graduate Diploma in Foundational Data Science, Master of Biostatistics.
How many credit points is Computational Statistics & Data Science?
Computational Statistics & Data Science at The University of Melbourne is typically around 12.50 credit points. Approximate โ confirm with the university.
Where is Computational Statistics & Data Science taught?
Computational Statistics & Data Science is taught at The University of Melbourne, VIC.
Studying Computational Statistics & Data Science?
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Sources: The University of Melbourne public course catalogue. Information is compiled and summarised โ not copied verbatim โ and is approximate; always confirm with the original source.
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