8498 modules
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CHEM6149 2028-29
Principles, Techniques and Energy Applications of Electrochemistry
Electrochemistry is an important area of science covering many interesting and important topics of current scientific research. For example, it is key to the development of new power sources (for example new batteries, fuel cells and supercapacitors) as well as for the development of new sensing strategies or the understanding of parasitic corrosion effects. This course is designed to build on previous courses and extend this understanding to encompass new techniques and approaches (e.g., AC impedance and microelectrodes) as well as exploring advanced aspects of battery technologies relevant for the 21st century. Students are expected to gain advanced knowledge from the course, which will help prepare them for modern electrochemistry research in both the academic/industrial arena. -
CHEM6149 2029-30
Principles, Techniques and Energy Applications of Electrochemistry
Electrochemistry is an important area of science covering many interesting and important topics of current scientific research. For example, it is key to the development of new power sources (for example new batteries, fuel cells and supercapacitors) as well as for the development of new sensing strategies or the understanding of parasitic corrosion effects. This course is designed to build on previous courses and extend this understanding to encompass new techniques and approaches (e.g., AC impedance and microelectrodes) as well as exploring advanced aspects of battery technologies relevant for the 21st century. Students are expected to gain advanced knowledge from the course, which will help prepare them for modern electrochemistry research in both the academic/industrial arena. -
CHEM6149 2030-31
Principles, Techniques and Energy Applications of Electrochemistry
Electrochemistry is an important area of science covering many interesting and important topics of current scientific research. For example, it is key to the development of new power sources (for example new batteries, fuel cells and supercapacitors) as well as for the development of new sensing strategies or the understanding of parasitic corrosion effects. This course is designed to build on previous courses and extend this understanding to encompass new techniques and approaches (e.g., AC impedance and microelectrodes) as well as exploring advanced aspects of battery technologies relevant for the 21st century. Students are expected to gain advanced knowledge from the course, which will help prepare them for modern electrochemistry research in both the academic/industrial arena. -
CHEM3059 2028-29
Principles, Techniques, and Applications of Electrochemistry
Electrochemistry is an important area of science covering many interesting topics of current scientific research. For example, it is key to the development of new power sources (fuel cells and electroysers) as well as for the development of new sensing strategies, and the understanding of parasitic corrosion effects, which will be covered in this module. The course is designed to build on previous courses and extend the understanding and knowledge developed to encompass new techniques and approaches (e.g. cyclic voltammetry, rotating disc electrodes, microelectrodes and AC impedance) and their applications to characterise electrochemical systems and reactions. -
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. -
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. -
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 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.