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skills necessary to analyze and improve the communication policies of organizations of various
                   types
                   Expected learning outcomes:
                   They know how to apply response algorithms in various crisis situations, establish
                   effective  interaction  within  the  team  to  achieve  a  common  goal,  build  the  reputation  of  a
                   government body, effectively manage conflicts, build work with key stakeholders

                                              «7М04118 – Regional Development»
                            MRD – 2024 (1 year part-time) modular form of training (for winter set)

                  It is necessary to dial 4 credits

                   1. Urban and rural management
                   Credits                                        4
                   Semester                                       Module 6
                   Short course description:
                   The course is aimed at developing knowledge in the field of urban and rural management. In
                   particular,  the  organization  of  urban  space,  models  of  urban  culture  of  megacities,
                   agglomerations, small and single-industry towns; features of the formation and development of
                   “Smart City”; monitoring the effectiveness of urban management and urban planning; economic
                   development of rural areas, employment and income of rural and urban populations; quality of
                   life of rural and urban populations; local government; making management decisions to improve
                   the socio-economic development of cities and rural areas
                   Expected learning outcomes:
                   Able to analyze and identify problems in the development of cities and rural areas; develop and
                   monitor the effectiveness of urban management and urban planning; manage city projects; are
                   able to determine approaches to the balanced development of rural areas, improving the quality
                   of  life  and  creating  a  comfortable  living  environment  in  urban  and  rural  areas;  ways  of
                   developing local self-government; make management decisions to improve the socio-economic
                   development of cities and villages

                   2. Project management
                   Credits                                        2
                   Semester                                       Module 6
                   Short course description:
                   The course is aimed at developing the competencies necessary for project management and
                   practical  skills  in  the field of  project  management  as a  tool for  increasing  the efficiency  of
                   government agencies and other organizations based on national and foreign standards in the
                   field of project management.
                   Expected learning outcomes:
                   They  acquire  skills  in  working  with  tools  and  methods  of  project  management,  developing
                   project documentation, are able to manage project stakeholders, deadlines, costs, resources,
                   content, procurement, quality, risks, communications within the project, and also understand
                   how to properly initiate and plan a project project efficiently activities and what to pay attention
                   to during further implementation and closure of projects.

                   3. Decision making based on data analysis
                   Credits                                        2
                   Semester                                       Module 6
                   Short course description:
                   The course aims to develop skills in statistical and economic processing of large amounts of
                   data  as the foundation for  making  regional/urban  development decisions;  visualization  and
                   analysis,  search  for  hidden  patterns,  and  processing  algorithms.  The  course  will  explore
                   methods of data analysis and further interpretation of the obtained results, methods of reducing
                   data dimensions, and new methods of data analysis based on Data Mining technology. Modern
                   application software packages will be used to solve problems of processing experimental data
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