This course provides students with knowledge of the performance management process. Students will enhance their understanding of the relationship between performance management and strategic planning. The course will further provide students with an understanding of the performance appraisal methods, appraisal feedback, conducting Performance interviews, and performance reward systems.
Introduces marketing as a powerful tool to provide value to consumers through innovative products, services, ideas and experiences. Engages in critical discourse of the historical and emerging marketing context through lectures, discussions, critiques and videos. Students will have an opportunity to be trained to acquire the knowledge and develop the mindset needed to become a marketer who provides superior value in the marketplace.
This course will prepare students for advanced research by examining how to plan, conduct and report on empirical investigations with an emphasis on data science within an application domain (e.g., NLP, Finance, Healthcare, Agriculture, and Telecommunications). It will also introduce students to practical but scientific research work, and to encourage independent academic and/or commercial research among students. The overall outcome is to develop novel solutions to data science-related problems and communicate the findings (concepts, designs and techniques) effectively and professionally in accordance with NUST requirements.
Students have to submit three (3) Progress Reports during the year of Thesis, using the link provided.
Due dates are: 17 April, 17 July and 13 November for Report No1, No2 and No3 respectively.
This course will prepare students for advanced research by examining how to plan, conduct and report on empirical investigations with an emphasis on data science within an application domain (e.g., NLP, Finance, Healthcare, Agriculture, and Telecommunications). It will also introduce students to practical but scientific research work, and to encourage independent academic and/or commercial research among students. The overall outcome is to develop novel solutions to data science-related problems and communicate the findings (concepts, designs and techniques) effectively and professionally in accordance with NUST requirements.
Students have to submit three (3) Progress Reports during the year of Thesis, using the link provided.
Due dates are: 17 April, 17 July and 13 November for Report No1, No2 and No3 respectively.