Data Science is a rapidly growing and interdisciplinary field that consists of extracting knowledge and insights from data to help understand a problem area and make decisions. To do these, the data scientist must master a large number of domains ranging from Mathematics to Computing (both fundamental and technological aspects) while also having a broad knowledge in order to propose the best possible models and to be able to interpret results in the most efficient ways.
Data scientists should be able to develop algorithms to process data, visualize and analyze them using either conventional statistical tools or techniques such as machine learning. There is a growing demand for data professionals in both public and private sectors as the amount of data generated grows and modern technologies such as the Internet of Things (IoT), Big Data and Cloud Computing become more prevalent. This Bachelor is a three-year program, run jointly by the University of Mauritius and the University of Paris-Seine, France.
The objective of this Bachelor's degree is to enable the training of data scientists on a wide spectrum of knowledge in different domains. Introductory courses in fields where data science will be applied such as maths, statistics, and physics are also offered to ensure that students are imparted with the knowledge and analytical skills required to transform data into intelligence.
Job prospects for graduates exist in the fields of Data Science, Data Engineering, Business Analytics, Business Intelligence, Banking, Artificial Intelligence, Software Development, Statistics, and Digital Marketing among others. Level 1 & 2 modules cover the fundamental topics in Mathematics and Computing. They also deal with the technical aspects of the field. The modules have been designed to impart students with a wide range of skills as well as the aptitude to deal with an ever-changing field. Level 3 modules are specialized modules that cater to innovation in the field. Students will undertake research and projects to enable them to bring together a large number of concepts from the program.
The program has been designed to enable students to:
- Acquire problem-solving skills which will allow them to transform data into intelligence;
- Have a deep understanding of the professional responsibilities related to the use of data science techniques in organizations;
- Acquire and apply analytical skills which will enable them to work with data from social media, web and search engines;
- Analyze a complex problem and make informed decisions based on analysis of existing data and rate the different proposed solutions;
- Engage in different activities which involve problem-solving and critical thinking to analyze business problems, propose and implement solutions;
- Impart essential technical and soft skills in graduates allowing a smooth transition to the industry; and
- Demonstrate the ability to be a productive team member in a data science context and business environment.
After successful completion of this program, graduates should be equipped with the following competencies:
- Analytical, problem solving and programming skills;
- Effective communication skills, adaptability, and flexibility;
- Project management skills; and
- Data and business analytics skills.
At the end of this program, the student should be able to:
- Analyze business or social or economic problems and apply data science knowledge to provide effective and efficient solutions;
- Use tools and techniques to model and implement data science solutions;
- Conduct statistical analyses for data, including performing data cleansing steps and creating visuals as part of the exploratory data analysis step;
- Apply analytical skills for enterprise systems, business intelligence and emerging fields in data science;
- Interpret results obtained from analyses both graphically and numerically, and
- Demonstrate the ability to work in team projects and communicate effectively using both verbal and written skills.
Teaching and Learning Methods
The Bachelor Data Science program consists of Teaching Contact Hours, Self-Study and Other Learning Activities. Teaching methods may include face to face lectures, online delivery, tutorials or practical sessions. Other Learning Activities may comprise of the following:
- Working on assignments;
- Sitting for Class Tests and preparation time for same;
- Sitting for Examinations and preparation time for same;
- Group work;
- Attending Workshops/Conferences recommended by the Department/Faculty;
- Site Visits/Trips;
- Additional Practicals;
- Presentations among peers;
- Experiential Learning;
- Guest lectures.
As per General Entry Requirements for admission to the University for Undergraduate Degrees.
Program Specific Requirements
At least 2 GCE ‘A’ Level passes including Mathematics and any other Science subject.
For French High School System: Applicants with Stream S for Science. Or any equivalent qualification acceptable to the University.
Minimum LCCS Credits Required
- For Degree Award For the degree award in Bachelor Data Science, the student must obtain at least 192 LCCS credits including Modules LCCS Credits Minimum LCCS Credits for Core Modules 165 Project 18 Internship 9 TOTAL 192.
- For Each Academic Year, Students may register for a minimum of 3 LCCS credits and a maximum of 48 LCCS credits per semester.
- Exit Points This program does not make provision for exit points (at a lower level).
Assessment and Deadlines
The assessment for each module may be based on one or a combination of the following:
- Continuous Assessment (teamwork and individual)
- Software Evaluation
- Portfolio Evaluation
- Oral or Written Examination
The specific details and/or formula for the calculation of the final mark are provided in the Module Catalogue for each module.
About the School
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