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Course Enquiry
Mr YIP Shui Wah, Kelvin Tel: 2595-2537 Email: kelvinyip@vtc.edu.hk
Big Data Analytics
Module Code: IT524030Q
Duration: 36 hours
Course Fee: (To be confirmed)
Intended Learning Outcomes
On completion of the module, students are expected to be able to:
- explain how businesses can extract information and insights from IoT Data;
- explain the different types of data analytics: descriptive, predictive and prescriptive;
- apply exploratory data analysis to extract insights from data;
- understand how Machine Learning algorithms can be used for predictive analytics;
- present and communicate using data storytelling; and
- understand and explain the evolution of a modern data center computing platform and be aware of distributed scalable Big Data.
Entry Requirements
- 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.
Award
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.
Note : This module is one of the two modules of IT524110P Professional Certificate in Big Data and AI
This module is one of the four modules of IT524108P Professional Diploma in Smart Technologies and Cybersecurity Operations