11354 modules
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MANG3073 2027-28
Analytics in Action
This course provides part of the essential knowledge and skills required for conducting the Final Project module in the final year.
Having learnt the basic techniques and principles of business analytics in previous modules, this module will introduce you to a number of advanced applications of business analytics in practice. These include pricing and revenue management, credit scoring, big data solutions and technologies, and advanced models to extract complex non-linear patterns from large amounts of diverse data. The focus will be on the underlying principles, modelling methodologies, and implementation using appropriate software packages. -
MANG3073 2028-29
Analytics in Action
This course provides part of the essential knowledge and skills required for conducting the Final Project module in the final year.
Having learnt the basic techniques and principles of business analytics in previous modules, this module will introduce you to a number of advanced applications of business analytics in practice. These include pricing and revenue management, credit scoring, big data solutions and technologies, and advanced models to extract complex non-linear patterns from large amounts of diverse data. The focus will be on the underlying principles, modelling methodologies, and implementation using appropriate software packages. -
MANG3108 2030-31
Analytics in Action I
Companies today collect large volumes of data from a variety of sources. This module introduces the key concepts of using ‘Big Data’ to support organisational decision-making. The module begins by defining the concept of data analytics. We then focus on predictive analytics techniques (e.g., regression and classification) and descriptive analytics techniques (e.g., clustering, association analysis, and sequence analysis). The module also illustrates how data analytics can be applied successfully in a range of areas, including marketing, retail credit risk, healthcare, and fraud detection. Theoretical concepts are supported by real-world case studies and demonstrations using commercial software. -
MANG3108 2027-28
Analytics in Action I
Companies nowadays have collected a large volume of data from various sources. This module aims to introduce the key concepts of using ‘Big Data’ to support organisations in making decision. The module will start by defining the concept of data analytics. We will then focuses on the use of predictive (e.g. regression and classification) and descriptive (e.g. clustering, association and sequence rules) techniques. The module will illustrate how data analytics can be successfully used to develop different application areas such as marketing, retail credit risk, healthcare, fraud detection, etc. The theoretical concepts will be illustrated using real-life application cases and world-class commercial software. -
MANG3108 2028-29
Analytics in Action I
Companies today collect large volumes of data from a variety of sources. This module introduces the key concepts of using ‘Big Data’ to support organisational decision-making. The module begins by defining the concept of data analytics. We then focus on predictive analytics techniques (e.g., regression and classification) and descriptive analytics techniques (e.g., clustering, association analysis, and sequence analysis). The module also illustrates how data analytics can be applied successfully in a range of areas, including marketing, retail credit risk, healthcare, and fraud detection. Theoretical concepts are supported by real-world case studies and demonstrations using commercial software. -
MANG3108 2029-30
Analytics in Action I
Companies today collect large volumes of data from a variety of sources. This module introduces the key concepts of using ‘Big Data’ to support organisational decision-making. The module begins by defining the concept of data analytics. We then focus on predictive analytics techniques (e.g., regression and classification) and descriptive analytics techniques (e.g., clustering, association analysis, and sequence analysis). The module also illustrates how data analytics can be applied successfully in a range of areas, including marketing, retail credit risk, healthcare, and fraud detection. Theoretical concepts are supported by real-world case studies and demonstrations using commercial software. -
MANG3098 2030-31
Analytics in Action II
Having learnt the basic techniques and principles of business analytics in previous semester 1 modules, this module will introduce you to a number of advanced machine learning methods and their applications in practice. These include machine learning methods, big data solutions and technologies, and advanced models to extract complex non-linear patterns from large amounts of diverse data. The focus will be on the underlying principles, modelling methodologies, and implementation using appropriate software packages. -
MANG3098 2027-28
Analytics in Action II
Having learnt the basic techniques and principles of business analytics in previous semester 1 modules, this module will introduce you to a number of advanced machine learning methods and their applications in practice. These include machine learning methods, big data solutions and technologies, and advanced models to extract complex non-linear patterns from large amounts of diverse data. The focus will be on the underlying principles, modelling methodologies, and implementation using appropriate software packages. -
MANG3098 2028-29
Analytics in Action II
Having learnt the basic techniques and principles of business analytics in previous semester 1 modules, this module will introduce you to a number of advanced machine learning methods and their applications in practice. These include machine learning methods, big data solutions and technologies, and advanced models to extract complex non-linear patterns from large amounts of diverse data. The focus will be on the underlying principles, modelling methodologies, and implementation using appropriate software packages. -
MANG3098 2029-30
Analytics in Action II
Having learnt the basic techniques and principles of business analytics in previous semester 1 modules, this module will introduce you to a number of advanced machine learning methods and their applications in practice. These include machine learning methods, big data solutions and technologies, and advanced models to extract complex non-linear patterns from large amounts of diverse data. The focus will be on the underlying principles, modelling methodologies, and implementation using appropriate software packages.