This major is to provide graduates in data science with essential training of quantitative knowledge, statistical theory, machine learning technology for the effective use and analysis of big and complex data for real-world applications. The primal goal of this data science major is to train a generation of students who are equally versed in data processing, data analysis, predictive modeling, and computational techniques and enable them the skills for the challenges in future that involve making sense of complex data to realize planning and decision making. The major offers a suite of courses and programs to equip and empower students of quantitative background to become professionals and practitioners of rigorous, actionable, and ethical data science. To this end, besides providing rigorous education about data science models and methods, the major also emphasizes the interdisciplinary training and the expertise of particular subject domains as well as communication skills and ethical awareness. |
Upon successful completion of this major, students should be able to:
- Integrate the theories and principles of
mathematical, statistical, computing foundations for the data
science;
- Gain computing expertise with data collection,
data analysing, data visualization, statistical analysis and machine
learning.
- Build skills
and intelligence of organizing and analysing data with a level of
flexibility within different application modules.
- Use a
variety of software packages to conduct data curation, modeling,
computation and inference and draw conclusions and actionable insights.
- Create and formulate the data-driven models in
practice; master the spectrum of the data science life cycle and the
connection to specific domain knowledge and business models.
- Acquire work related experience and effective
communication skills necessary to work within a team in an international
and culturally diverse workplace.
- Recognize the social responsibility and ethic
awareness for the development of the data-driven technologies in the
modern era of big data.
|
| Requirements | Normative 4-year
Degree | Advanced Standing I1 | Advanced Standing II2 |
| Gateway Education requirement |
30 credit units |
21 credit units |
-- |
| College / School requirement |
18 credit units |
18 credit units |
-- |
| Major requirement |
54 credit units
(Core: 33
Elective: 21) |
45 credit units
(Core: 33
Elective: 12) |
-- |
| Free electives / Minor (if applicable) |
18 credit units |
6 credit units |
-- |
| Minimum Graduation Requirement: |
120 credit units |
90 credit units |
-- |
| Maximum Credit Units Permitted: |
144 credit units |
114 credit units |
-- |
| Note 1:
For students with recognised Advanced Level Examinations or equivalent qualifications.
Note 2:
For Associate Degree/Higher Diploma graduates admitted to the senior year.
|
| |
| |
