Course Code: IT524116P
Duration: 72 hours
Course Fee: To be confirmed
Individual Module: To be confirmed
Assessment & Examination
The assessment of students is made through class work, assignments, written test, laboratory works, project and presentations. The weighting of these assessment components varies among modules.
Mode of Study
Dr. Richard Wu Tel: 2436 8556 Email:firstname.lastname@example.org
Need for the Course
With the explosive growth of the volume, variety, velocity and veracity of data in the past decade, the needs for data analytics and AI-based predictive systems sparked new product and service offerings across disciplines from finance, business, automobile, manufacturing, healthcare, city planning and even homeland security. Governments and commercial organizations have been investing a huge amount of money and human resources in developing data analytic applications to capitalize its benefits. For instance, analyze customer behavior data to improve the hit rate of cross-selling and up-selling; determine customers' lifestyle and their preferences by deep mining all relevant data, structured or unstructured, including billing records, application forms, social media messages and mobile Internet browsing behavior. The goal is to ensure a better understanding of their customers over their rivals and secure the lead in the competition.
The course comprises of the following modules:
- Data Science Fundamentals (24 hours)
- Data Mining with R (24 hours)
- Data Analytics and Visualization (24 hours)
- A Module Certificate is awarded upon completion of each module, i.e. pass the assessment. An attendance certificate is also issued with an attendance rate of at least 70% of a module.
Applicants should either have:
- Five HKDSE subjects at Level 2 or above, including English and Chinese Languages, plus at least one year of relevant work experience, or equivalent; or
- Five HKCEE subjects at Grade E/Level 2 or above, including English and Chinese Languages, plus at least two years of relevant work experience, or equivalent ; or
- Completion of a QF Level 3 programme that is deemed acceptable to the respective Programme Board plus at least one year of relevant work experience; or
- Relevant RPL qualification(s) at QF Level 3 or above plus at least one year of relevant work experience AND a pass in an entrance assessment, which can be either oral or written; or
- Other relevant verifiable prior learning plus at least two years of relevant work experience that are deemed appropriate by respective Programme Board AND a pass in an entrance assessment, which can be either oral or written.