11311 modules
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MATH6122 2025-26
Probability and Mathematical Statistics
The module is designed for postgraduate students whose first degree is in Mathematics or another discipline where development of mathematical skills is a significant component (Science, Engineering, Economics, Quantitative Social Sciences). While the material covered is similar in technical level to that which might be found in an undergraduate mathematics curriculum, the quantity of material is much larger, and the pace of delivery correspondingly much faster. Hence the module requires students to have developed study skills to graduate level.
The module is comprised of three submodules, in probability and distribution theory, statistical inference and statistical modelling, as described in the syllabus below. -
MATH6122 2026-27
Probability and Mathematical Statistics
The module is designed for postgraduate students whose first degree is in Mathematics or another discipline where development of mathematical skills is a significant component (Science, Engineering, Economics, Quantitative Social Sciences). While the material covered is similar in technical level to that which might be found in an undergraduate mathematics curriculum, the quantity of material is much larger, and the pace of delivery correspondingly much faster. Hence the module requires students to have developed study skills to graduate level.
The module is comprised of three submodules, in probability and distribution theory, statistical inference and statistical modelling, as described in the syllabus below. -
MATH6122 2028-29
Probability and Mathematical Statistics
The module is designed for postgraduate students whose first degree is in Mathematics or another discipline where development of mathematical skills is a significant component (Science, Engineering, Economics, Quantitative Social Sciences). While the material covered is similar in technical level to that which might be found in an undergraduate mathematics curriculum, the quantity of material is much larger, and the pace of delivery correspondingly much faster. Hence the module requires students to have developed study skills to graduate level.
The module is comprised of three submodules, in probability and distribution theory, statistical inference and statistical modelling, as described in the syllabus below. -
MATH6122 2027-28
Probability and Mathematical Statistics
The module is designed for postgraduate students whose first degree is in Mathematics or another discipline where development of mathematical skills is a significant component (Science, Engineering, Economics, Quantitative Social Sciences). While the material covered is similar in technical level to that which might be found in an undergraduate mathematics curriculum, the quantity of material is much larger, and the pace of delivery correspondingly much faster. Hence the module requires students to have developed study skills to graduate level.
The module is comprised of three submodules, in probability and distribution theory, statistical inference and statistical modelling, as described in the syllabus below. -
COMP6261 2029-30
Probability in Computing
Computer Science has evolved significantly over the past decades, and various subfields require a strong foundation in probability. Such fondation is important in studying randomized algorithms, algorithm analysis, approximation algorithms and artificial Intelligence. -
COMP6261 2030-31
Probability in Computing
Computer Science has evolved significantly over the past decades, and various subfields require a strong foundation in probability. Such fondation is important in studying randomized algorithms, algorithm analysis, approximation algorithms and artificial Intelligence. -
COMP6261 2025-26
Probability in Computing
Computer Science has evolved significantly over the past decades, and various subfields require a strong foundation in probability. Such fondation is important in studying randomized algorithms, algorithm analysis, approximation algorithms and artificial Intelligence. -
COMP6261 2027-28
Probability in Computing
Computer Science has evolved significantly over the past decades, and various subfields require a strong foundation in probability. Such fondation is important in studying randomized algorithms, algorithm analysis, approximation algorithms and artificial Intelligence. -
COMP6261 2026-27
Probability in Computing
Computer Science has evolved significantly over the past decades, and various subfields require a strong foundation in probability. Such fondation is important in studying randomized algorithms, algorithm analysis, approximation algorithms and artificial Intelligence. -
COMP6261 2028-29
Probability in Computing
Computer Science has evolved significantly over the past decades, and various subfields require a strong foundation in probability. Such fondation is important in studying randomized algorithms, algorithm analysis, approximation algorithms and artificial Intelligence.