The Master of Science in Computing and Data Analysis (MSc in Computing and Data Analysis) program, conducted and awarded by KIMT University, is designed to equip students with advanced knowledge and skills in computing, data science, and analytics. The program emphasizes the integration of computational techniques, statistical methods, and machine learning to analyze and interpret complex data sets. Students will develop competencies in programming, data visualization, predictive modeling, and big data technologies to drive data-driven decision-making across various industries.

Graduates of the MSc in Computing and Data Analysis program will be prepared for leadership roles in data science, business analytics, software development, and research in both public and private sectors.

Upon successful completion of the program, graduates will be able to:

• Design and implement advanced computational models and algorithms.
• Analyze and interpret complex data sets using statistical and machine learning techniques.
• Develop and deploy data-driven solutions to solve real-world problems.
• Utilize big data technologies and tools for data processing and analysis.
• Conduct independent research to address challenges in computing and data analysis.
• Communicate data-driven insights effectively to diverse stakeholders.
• Lead multidisciplinary teams to deliver innovative data solutions.

• Applicants must hold a bachelor’s degree in computer science, information technology, mathematics, or a related field.
• Relevant professional experience in computing, data analysis, or a related area (preferred but not mandatory).
• Applicants with a Postgraduate Diploma or equivalent (Level 7 at RQF Level) in a related field may be considered for advanced standing under the Recognition of Prior Learning (RPL) policy. Such applicants must have completed a minimum of 60 credits at an advanced level and provide supporting documentation.

The MSc in Computing and Data Analysis program consists of 90 credits, divided into core courses and a thesis. Each course is worth 6 credits, while the thesis accounts for 12 credits. The course structure is as follows:

Summary of Courses

• Core Courses: 13 courses (78 credits)
• Capstone Thesis: 1 project (12 credits)

What you will Study

1. Advanced Programming and Algorithms
2. Data Structures and Databases
3. Statistical Methods for Data Analysis
4. Machine Learning and Predictive Modeling
5. Big Data Technologies and Tools
6. Data Visualization and Communication
7. Cloud Computing and Distributed Systems
8. Artificial Intelligence and Deep Learning
9. Natural Language Processing
10. Ethics and Privacy in Data Science
11. Business Analytics and Decision Support Systems
12. Research Methods in Computing and Data Analysis
13. Innovative Technologies in Computing
14. Thesis Research Project

To successfully complete the MSc in Computing and Data Analysis, students are expected to:

• Dedicate approximately 15-20 hours per week to coursework, including readings, assignments, and discussions.
• Actively participate in online forums, webinars, and collaborative projects.
• Complete all assignments, exams, and the capstone project within the stipulated deadlines.
• Maintain regular communication with faculty and peers to enhance learning outcomes.
• Exhibit strong self-discipline and time-management skills to balance studies with other commitments.

• 90% Assignments
• 10% Presentation and viva
• At the end of the program each student also submits a research project paper

All of the following items must be submitted on or before the application closing date. They may be submitted online.

• CV (maximum 2 pages).
• Passport size photograph
• A personal statement of approximately 350 – 400 words. The statement should focus on the applicant’s interest in computing and data analysis, how the program will impact their career, and how they plan to balance work, life, and study commitments.
• Copies of bachelor certificate (or equivalent) or post-graduate certificate diploma or degree parchments, as well as transcripts of associated results.

Students apply to the KIMT online application system. To apply, simply click on and follow the instructions. A non-refundable application fee applies. The application fee is paid online. Further information about applications, contact at admissions@kimtuniversity.com