Master in Data Science

The master in data science (mds) program is meticulously designed to equip students with advanced knowledge and skills in data science, ensuring they are well-prepared for various professions requiring expertise in this field. 

Graduates of this program will be:

• Data Science Specialists with Advanced Knowledge: Capable of making or assisting in decision-making based on data-driven insights and solving complex problems using data.
• Technically Proficient Innovators: Equipped with enhanced technical and numeracy skills to provide innovative solutions in the area of data science and analytics.
• Effective Communicators and Leaders: Possessing strong leadership, interpersonal, and communication skills to interact effectively with stakeholders.
• Lifelong Learners with an Entrepreneurial Mindset: Committed to engaging in lifelong learning activities and fostering an entrepreneurial spirit.
• Ethical Professionals: Upholding and defending ethical conduct, professional practices, and integrity in their work.

The MDS program utilizes cutting-edge computing tools to provide a high-quality learning experience. This integration of technology ensures that learners receive an education that is both practical and theoretically robust. Students engage with advanced software and analytical tools, gaining hands-on experience essential for solving real-world problems.  By connecting the data science discipline directly to career advancement opportunities, the program offers significant benefits to its learners, enhancing their employability and potential for growth in the industry. This aligns with OUM’s mission to widen access to quality education and provide lifelong learning opportunities by leveraging technology, adopting a flexible mode of learning, and offering a conducive and engaging learning environment at competitive and affordable costs.

Program Educational Objectives (PEO)

• PEO 1- Data science specialists have advanced knowledge and can make or assist decision-making based on data-driven problems or insights;
• PEO 2- Data science specialists capable of applying enhanced technical and numeracy skills to provide innovative solutions in the area of data science and analytics;
• PEO 3- Data science specialists have leadership skills, good interpersonal and communication skills to interact with stakeholders effectively;
• PEO 4- Data science specialists who engage and advocate lifelong learning activities and have an entrepreneurial mindset; and
• PEO 5- Data science specialists who uphold and defend ethical conduct, professional practices and issues in maintaining the integrity

Programme Learning Outcomes (PLO)

• PLO 1 Integrate advanced knowledge related to data science.
• PLO 2 Recommend innovative solutions related to data science.
• PLO 3 Construct data science solutions in terms of their usability, efficiency and effectiveness.
• PLO 4 Demonstrate effective interaction within a group and with a diverse audience through discussions and participation in discourses related to data science.
• PLO 5 Exhibit effective communication by publishing and presenting technical materials in the field of data science.
• PLO 6 Utilise digital skills to acquire, interpret and extend knowledge in data science.
• PLO 7 Apply numerical skills to acquire, interpret and extend knowledge in data science.
• PLO 8 Demonstrate leadership, teamwork, autonomy and responsibility in delivering services related to data science.
• PLO 9 Exhibit capabilities to extend relevant data science knowledge through life-long learning.
• PLO 10 Exhibit capabilities of having an entrepreneurial mindset in data science.
• PLO 11 Uphold professional and ethical practices in conducting research and delivering services related to data science.

Common career fields and examples of career opportunities for graduates with a Master of Data Science (MDS):

• Data Scientist: Analyze and interpret complex data to help companies make informed decisions.
• Data Analyst: Perform statistical analysis and create visualizations to communicate findings.
• Machine Learning Engineer: Develop algorithms and models that enable machines to learn from data.
• Business Intelligence Analyst: Use data to provide insights that inform business strategy and operations.
• Big Data Engineer: Design, build, and manage large-scale data processing systems.
• Data Consultant: Provide expert advice on data strategy, management, and utilization to organizations.
• Research Scientist: Conduct advanced research in data science and contribute to academic and industrial advancements.

These roles span various industries, including technology, finance, healthcare, marketing, and more, providing a diverse range of opportunities to apply your data science expertise.