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MANG6260 2026-27 Marketing Data Science This module focuses on in-depth and advanced statistical tools for analysing big data. The module uses real raw data (as well as big data) that require knowledge of data pre-processing prior to systematic data analy

University of Southampton ยท England ยท MANG6260

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MANG6260 2026-27 Marketing Data Science This module focuses on in-depth and advanced statistical tools for analysing big data. The module uses real raw data (as well as big data) that require knowledge of data pre-processing prior to systematic data analy is a subject at University of Southampton, England. It covers topics like business-analytics, data-analytics, data-mining, data-science. It is part of 1 degree. The information below is compiled from public course material โ€” approximate, not official.

University
University of Southampton
Code
MANG6260
Credit points
3.00

Topics covered

business-analyticsdata-analyticsdata-miningdata-science

Degrees that include MANG6260 2026-27 Marketing Data Science This module focuses on in-depth and advanced statistical tools for analysing big data. The module uses real raw data (as well as big data) that require knowledge of data pre-processing prior to systematic data analy

Frequently asked questions

What is MANG6260 2026-27 Marketing Data Science This module focuses on in-depth and advanced statistical tools for analysing big data. The module uses real raw data (as well as big data) that require knowledge of data pre-processing prior to systematic data analy about?

MANG6260 2026-27 Marketing Data Science This module focuses on in-depth and advanced statistical tools for analysing big data. The module uses real raw data (as well as big data) that require knowledge of data pre-processing prior to systematic data analy covers topics like business-analytics, data-analytics, data-mining, data-science.

Which degrees include MANG6260 2026-27 Marketing Data Science This module focuses on in-depth and advanced statistical tools for analysing big data. The module uses real raw data (as well as big data) that require knowledge of data pre-processing prior to systematic data analy?

MANG6260 2026-27 Marketing Data Science This module focuses on in-depth and advanced statistical tools for analysing big data. The module uses real raw data (as well as big data) that require knowledge of data pre-processing prior to systematic data analy is part of 1 degree, including MSc Marketing Analytics Typical offer: 2:1 degree Duration: 1 year.

How many credit points is MANG6260 2026-27 Marketing Data Science This module focuses on in-depth and advanced statistical tools for analysing big data. The module uses real raw data (as well as big data) that require knowledge of data pre-processing prior to systematic data analy?

MANG6260 2026-27 Marketing Data Science This module focuses on in-depth and advanced statistical tools for analysing big data. The module uses real raw data (as well as big data) that require knowledge of data pre-processing prior to systematic data analy at University of Southampton is typically around 3.00 credit points. Approximate โ€” confirm with the university.

Where is MANG6260 2026-27 Marketing Data Science This module focuses on in-depth and advanced statistical tools for analysing big data. The module uses real raw data (as well as big data) that require knowledge of data pre-processing prior to systematic data analy taught?

MANG6260 2026-27 Marketing Data Science This module focuses on in-depth and advanced statistical tools for analysing big data. The module uses real raw data (as well as big data) that require knowledge of data pre-processing prior to systematic data analy is taught at University of Southampton, England.

Studying MANG6260 2026-27 Marketing Data Science This module focuses on in-depth and advanced statistical tools for analysing big data. The module uses real raw data (as well as big data) that require knowledge of data pre-processing prior to systematic data analy?

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Sources: University of Southampton 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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