The purpose of the program is to develop young data scientists with
- understanding of theoretical principles of computing, statistics and data management to support continual learning,
- experience with current data science techniques and producing value from data,
- understanding of their role in an organisation and in broader society of managing data and using it productively.
This will allow them to contribute as practicing Data Scientists demonstrating creativity, innovation, leadership and professionalism.
Program Educational Objectives
The educational objectives of the Bachelor of Science in Data Science program are that within a few years of graduation, the majority of our graduates will demonstrate excellence in (i) top graduate programs; or (ii) technical or managerial leadership tracks in technology-based industries or sectors; or (iii) pursuing entrepreneurial ventures.
In these roles they will:
- Demonstrate proficiency with data science principles and knowledge of specific computing or statistical methods, also to serve as a basis for continual learning;
- Acquire, manage, explore and analyze large or complex data sets in order to provide useful insight, while properly respecting economic, environmental, cultural, life safety, and ethical standards or constraints;
- Discover and apply new knowledge, and develop new tools for the practice of data science and the development of data processing pipelines;
- Be sensitive to professional and societal contexts, committed to ethical action, engaged in life-long learning and be prepared for future academic career, should they want one;
- Be leaders with an entrepreneurial mindset, and effective communicators as members of multidisciplinary teams, both in the profession and in the community;
- Engage with their communities, profession, the nation, and the world.
Students should, as data scientists, be able to:
- Acquire, manage, explore, and analyse large or complex data sets in order to provide insight about specific organizational or science problems;
- Do so using agile development and an entrepreneurial mindset;
- Design, implement, evaluate, and maintain a data processing pipeline using standard tools;
- Apply appropriate computer science and statistical theory and software development fundamentals when approaching data science problems;
- Use visualization and communicate effectively for a variety of professional contexts
In addition, as professionals they should:
- Recognize professional responsibilities and make informed judgments in data science practice based on legal, ethical, privacy and security considerations;
- Function effectively as a member or leader of a team engaged in activities appropriate to the program’s discipline.