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Our Faculties

MSC TOURISM AND HOSPITALITY MANAGEMENT (MHTM)

MSC TOURISM AND HOSPITALITY MANAGEMENT (MHTM) 

Module CodeModule NameDescription
 MHTM501  The Tourism and Hospitality Industry  This module will reintroduce students to the Tourism and hospitality industry with major focus on critical operational issues like the nature of the industry, governance issues, human capital development and other managerial issues
MHTM502 Community Based Tourism and Sustainable Development The Community Based Tourism part looks at the introduction to tourism and theoretical frameworks, community-based tourism labelling and certification, case studies and examples of community-based tourism and the critical approaches to community-based tourism development.
MTIC503 Tourism Informatics and Web Design The Tourism and Hospitality Industry is dominated by the use of information communication technologies in conducting of business. The module enables students to expand their knowledge on information communication systems applied in the Tourism and Hospitality Industry.The students will have competencies to: the development of websites, Facebook pages and twitter accounts and other ICT enabled platforms that will enable organizations to competitively promote their products and services globally. It will also enable students to appreciate tourism guest management systems like Galerio, Amadeus, Fidelio, Host-It and Inn Keeper
MTIC504 Strategic Destination Marketing This module creates a comprehensive and focused management approach to marketing a destination in the domestic and global markets. The increasing role of the internet and cyber-marketing will also be looked at and in this case, students will learn how to design and manage their own websites in order to effectively market their organizations. Issues of branding, advertising and public relations will also be addressed. Students will also acquire expertise in applying tourism marketing strategies in countries other than their own.
MHTM505 Models in Tourism Development and The Environment The module focuses on an overview of the impact Tourism and Hospitality Development on the physical environment, the economy and on the host communities and their cultures. The students will acquire knowledge and skills to develop models and strategic frameworks that will be used to mitigate negative physical, economic and social impacts of the development of the tourism industry at local and national levels.Further, students will acquire technical skills to carryout environmental, economic and social impact of tourism projects within the country. Outcome will be models/frameworks of green tourism.
MHTM506 Strategic Event Management

The module will widen and deepen students’ knowledge on Events Management. It will enable students to design management systems and models for the operationalization of Event of any magnitude. The module will further motivate students to participate in the planning and running of events during their degree programme on a part-time basis which will give them the necessary experience to run their own companies after graduation. Expected outcomes are the ability to plan and run events and make Zimbabwe a renowned MICE destination.
MTIDD507 International Tourism Policies and Development The module will enable students to acquire knowledge and be aware of the policies and regulations that govern the development of tourism sector in the Zimbabwe. Students will assess and analyse current policies and regulations and draw up new policies to improve the operative environment for Tourism and Hospitality stakeholders in Zimbabwe. The new policy frameworks to be based on international best practices once adopted by the government will assist Zimbabwe to become a competitive tourism destination.
 MHTM508  International Tourism Investment and Financing  The module enables students to acquire knowledge on sources of funding for tourism projects regionally and internationally. It further gives them skills to develop project proposals for funding by financial Institutions. Students will be capacitated to appraise projects and develop fund raising models. Expected outcomes will be funded and resourced Zimbabwean tourism destination and projects.
 MHTM509  Tourism Entrepreneurial Leadership and Innovation  The module deepens students’ skills in business development, business marketing, human resources management, preparation of business plans, idea generation, environmental and opportunities identification and screening. The module further motivates students to register their own business enterprises and to participate in practical business management through opportunities that will be availed by the University and the Tourism Industry in the country. Expected outcomes are more Zimbabwean owned companies serving tourists.
 MMTM510  Research Methods  The module will equip students with the practical skills necessary to successfully complete a research project leading to the submission of a dissertation report. Students will be taken through the process and different stages of undertaking research. This module equips students with the skills and competencies that enable them to understand real-life management problems, collect and analyse data using different methodologies culminating to them being researchers.
 MHTM570  Dissertation  The dissertation is the culmination of the master’s study and recognition of the student’s capability to conduct a research project independently. Students are encouraged to undertake an organisation-based dissertation project. Working with an organisation, students can structure their project around a real business issue of challenge. A student project will develop their employability skills, enhance the student’s CV and give the student the chance to use his/her insight to help an organisation develop. Some of the outcomes here are publications in recognised journals, practical management solutions, policy recommendations, and models/frameworks to address issues of public sector accounting and finance.

 

 

MSC IN ECONOMETRICS AND COMPUTATIONAL ECONOMICS (MECE)

MSC IN ECONOMETRICS AND COMPUTATIONAL ECONOMICS (MECE)

Module CodeModule NameDescription
MECE501 Computational Microeconomics The module provides an introduction to the theory of incentives and contracts which has become an indispensable part of economics. It is an interaction between computer science and economics. As computer systems become more interconnected, multiple parties interact in the same environment and compete for scarce resources, which necessarily introduces economic phenomena. The module introduces students to major tools of microeconomic theory accompanied with applications. The module aims at developing strategic thinking needed for understanding many economic environments
MECE 506 Econometric Systems Econometric systems are designed to equip post-graduate students with a solid and up-to-date grounding in various systems of econometrics. The module helps students to appreciate theory and application of various systems of econometrics. Econometric systems prepare students to be able to identify appropriate econometric methodology for a particular economic research problem. It basically acts as the foundation of all the econometric courses in the Master of Science Degree in Econometrics and
MECE507 Computational Macroeconomics This module equips students with powerful computational tools to be used in macroeconomic analysis. Students will learn how to solve macroeconomic models using computational methods, calibrate these models, and use calibrated models to address interesting questions in macroeconomics. While students are exposed to some basic macro models throughout the module, the main objective is computer implementation
MECE508 Panel Data Econometrics Panel data econometrics is offered at post-graduate level as a micro-econometrics module. This module equips post-graduate students with a solid and up-to-date foundation in theoretical and applied panel data techniques. Unlike time series models which only studies time-specific variation, panel data models are richer since they analyse both period-specific and individual specific heterogeneity. Panel data econometrics has evolved rapidly over the last decade. The module prepares students with dynamic panel data estimation, non-linear panel data methods and non-stationary
MECE509 Financial Econometrics Financial econometrics applies statistical and econometric models to analyze financial market data, focusing on asset prices, volatility, risk, and market dynamics using techniques like time series analysis, regression, and GARCH models to understand complex relationships and forecast outcomes for portfolio management, risk assessment, and valuation. It bridges theoretical finance with empirical data analysis, using methods from basic statistics to advanced time-series modelling.
MECE502 Non-parametric Econometrics Most econometrics models are parametric/smoothed models or models with a defined functional form. While most relationships among economic, financial and business variables take the form of a defined functional form, there are equally several relationships without a well-defined functional form. Over the years, the non-parametric smoothing approach has been neglected and the popular parametric approach has been widely preferred because of its simplicity and mathematical convenience. This module therefore equips post-graduate students in economics, finance and business with a strong and up-to-date foundation in theoretical and applied non-parametric econometrics.
 MECE503  Machine Learning  This module provides a broad introduction to machine learning and statistical pattern recognition. Machine learning uses interdisciplinary techniques such as statistics, linear algebra, optimization, and computer science to create automated systems that can be used on large volumes of data at high speed in order to make predictions without human intervention. Machine learning as a course is universal, with applications bridging from business intelligence to homeland security. This module will familiarize students with a broad cross-section of models and algorithms for machine learning as well as preparing students for research and industry application of machine learning techniques.
 MECE504  Artificial Intelligence  This module introduces students to artificial intelligence as an introductory module. It looks at the design of intelligent agents, where an intelligent agent is a system that perceives its environment and takes actions that maximize its chances of success. Topics to be covered include artificial intelligence methodology and fundamentals, intelligent agents, search algorithms, game playing, supervised and unsupervised learning, decision tree learning, neural networks, nearest neighbour methods, dimensionality reduction, clustering, kernel machines, support vector machines, uncertainty and probability theory, Bayesian networks and statistical learning.
MECE505 Big Data Analysis Big data analysis can be offered as a Programme with several modules. However, as a module, big data analysis equips students with up-to-date foundation in big data analysis. This module prepares post-graduate students with critical skills required in the analysis of big data. Students are prepared to appreciate the handling of large data sets and exposed to data sets from the national statistical agency such as Census data, labour force surveys, Demographic Health Surveys, PICES, Integrated household surveys, World Bank surveys, IMF surveys, among others.
MECE510 Design and analysis of Algorithms Design and Analysis of Algorithms (DAA) is a core area of computer science that involves developing efficient methods to solve computational problems and evaluating their performance. The primary goal is to find optimal solutions, considering constraints like time, space, and cost. 
MECE570 Dissertation Students will do a dissertation related to theory and knowledge gained from the programme.  The dissertation will offer students an opportunity to apply computational knowledge on complex economic problems.

 

 

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