- Examiner: Dr. Diana Nandagire Ntamu
MUBSEP
Search results: 173
Note : Whoever is dissatisfied about these results is advised to approach the attached faculty.
- Examiner: Dr. Dickson Turyareeba
- Lecturer: Dr. Miria Nakamya, PhD
- Lecturer: Susan Watundu
- Examiner: Vincent Obedgiu
Course Description
Big data involves storing, processing, analyzing and making sense of huge volumes of data extracted in many formats and from many sources. This course is designed to teach students the fundamentals of Big Data, Big Data analysis tools and how these tools can be used to extract value out of Big Data.
Course Objectives
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Understand fundamental principles of Big Data.
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Understand the key components of the computing environment for Big Data including hardware, software, distributed systems, and analytical tools.
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Understand and discuss the application of data mining methodologies, algorithms, and enabling technologies on Big Data to deliver extraordinary results and value.
Learning Outcomes
Upon successful completion of this course, students should be able to:
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Describe Big Data and its characteristics.
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Demonstrate ability to work with Big Data using the main Big Data tools (Hadoop & Spark)
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Describe how Big Data can be resourcefully used in a corporate environment
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Effectively apply predictive analytics on Big Data
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Design and implement a prototypical Big Data Analytics Solution to address a decision making situation facing an organization of your choice.
- Examiner: Dr. Abdal Kasule (PhD)
- Lecturer: Prof. Francis Kasekende (Phd)
Project management is increasingly recognized as an indispensable management function and an alternative business model for modern management. With the changing regulatory opportunities such as accelerated practice of joint ventures, consortium arrangements and contract-based business engagements, the need to develop project management capacity is more visible and feasible today. Uganda and the general African Continent still grapple with lack of professional experts in the project management discipline and this course makes a paramount contribution towards filling this intellectual gap. Moreover, with the adoption of programme-based methods of development in Uganda, the course opens up a wide space for students to prepare to take up these emerging opportunities. This course covers the concepts and skills that are used by managers to propose, plan, secure resources, budget and lead projects to successful completion.
- Examiner: Assoc. Prof.. Ernest Abaho
- Lecturer: Dr. Levi Kabagambe Bategeka
- Lecturer: Francis Kenneth Kimbugwe
Good morning students. The attached take-home assignment is the first coursework. Please ensure that you follow instructions detailed as per the question paper. Schedule and sequence activities well so as to meet the deadline with quality deliverables.
MAKERERE UNIVERSITY
MAKERERE UNIVERSITY BUSINESS SCHOOL
PRODUCTION STATISTICS TAKEHOME (COURSEWORK ONE) FOR BACHELOR OF BUSINESS STATISTICS OF MAKERERE UNIVERSITY,
ACADEMIC YEAR 2023/2024
YEAR OF STUDY: III SEMESTER: II
COURSE NAME: PRODUCTION STATISTICS COURSE CODE: BBM3204
START DATE: FEBRUARY 18, 2024 TIME: 9:00 AM
END DATE: FEBRUARY 29, 2024 TIME: 9:00 AM
INSTRUCTIONS:
This take-home assignment should be individually done. Attempt all the questions. Use either SPSS, STATA or Excel to analyze production data. You will be required to present and disseminate knowledge in class. Please submit the typed work of not more than 10 pages. Academic dishonesty will automatically lead to disqualification.
Question One
From global and local context, production metrics measure, compare the performance of processes and provide useful data to manage production activities over time. Such production metrics include; costs, quality, volume, downtime, overall operations effectiveness, rate of return, productivity in revenue per employee, asset turnover, inventory turns, return on assets, yield, capacity utilization among others. Accordingly, modelling efficiency and effectiveness of production processes have attracted attention to policy makers, researchers and other stakeholders. As a student equipped with competencies of production statistics, identify organization (s) of your choice to answer the questions that follow;
i) Using the knowledge of production statistics, develop a short story or case of the identified production related issues based on the organization (s) of your choice highlighting context, actions and results with catastrophic evidence. (5 marks)
ii) Gather production data (either secondary or primary data) based on identified production metrics from the organization (s) of your choice and state any two objectives to address the stated production related issues identified in (i) above. (5 marks)
iii) Use the appropriate production statistical tools to develop a production-oriented model (s) basing on the stated objectives and the gathered data in (ii) above. (15 marks)
iv) Suggest the possible evidence-based and action-oriented recommendations to managers and policy makers of the identified organization (s). (5 marks)
END OF EXAMINATION PAPER
Best wishes.
- Lecturer: Dr. Gideon Nkurunziza
- Lecturer: Mr. Lukyamuzi Vicent
- Lecturer: Ali Kasaija
- Lecturer: Dr. Warren Tibesigwa
This course will test your application of Research Methods that you did in the last semester. You will be required to upload your proposal for a project you are doing in groups of 5. Thereafter you will be expected to upload your report as well. The datelines have been communicated and must be adhered to.
This course will be evaluated out of 100%; evaluation is done during presentation. All members of the group must be present for the presentation and marks allocation will be according to individual participation. In case a group doesn't present their project, they shall be required to wait till next offered (next academic year) like is the case with missing an examination. You are therefore cautioned not to miss presentation.
In case of queries, please feel free to contact Dr. Samali V. Mlay (smlay@mubs.ac.ug) or Mr. Ismael Kato (ikato@mubs.ac.ug)
Have a good semester.
- Examiner: Ismael Kato
- Examiner: Assoc. Prof. Robert Kyeyune (PhD)
Systems Analysis and Design course for Executive MBA introduces students to theoretical and practical aspects of information systems development and management. In particular, students learn systems fundamentals, systems development life cycle, systems development methodologies, database concept, process modeling, and systems security.
The course creates awareness of systems development knowledge to non technical managers, explores approaches of developing systems and exposes students to security concerns in computerized systems.
- Lecturer: Onesmus Kamacooko
- Lecturer: Mr. Lukyamuzi Vicent
- Lecturer: Onesmus Kamacooko
- Lecturer: RITAH Nabagereka
- Lecturer: Mr. Lukyamuzi Vicent