Advanced Diploma in Advanced Diploma in Big Data Analytics and Applications programme is a 12-month part-time programme designed for secondary school graduates who have aspirations to pursue a career in the Big Data Analytics field. 

This programme is designed to help students develop basic skills in big data analytics. It provides students with the opportunity to gain in-depth knowledge and critical understanding of a range of issues and concepts in Big Data Analytics.

Introduction

"Big data" is a term for the collection of large and complex data sets and the analysis of these data sets for relationships. Big data is characterized by 5 Vs: volume, variety, velocity, veracity and value. The quantity of data in these sets is so large that prevents traditional methods of analysis from being effective. Rather than focusing on precise relationships between individual pieces of data, big data uses various algorithms and techniques to infer general trends over the entire set. Good management of big data can lead to great insights; can help to figure out the root cause of problems and failures as well as deceitful behaviour that affects the revenues of a business. Therefore, big data analytics today becomes a key basis of competition and it will drive new waves of productivity, growth and innovation.

 

Intended Learning Outcomes (ILOs) of the Programme

On completion of the programme, students should be able to

• Apply big data analytics approach to solve business problems.
• Apply big data concept in marketing and retailing.
• Apply security solution in big data environment.
• Explore the potential use of Big Data tools and techniques in a business environment and fit these techniques within an organisation’s information system strategy
• Apply the knowledge of business intelligence and skills of mathematical modeling to synthesize, manage and evaluate information.
• Identify problems using a graph analytics approach and choose appropriate techniques to solve the problems.

 

News about Big Data Analytics Industry in Hong Kong:

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Core Modules Title	Contact hours
1. Introduction to Big Data Applications and Analytics	48
2. Search Engine Optimisation and Web Analytics	48
3. Big Data Privacy and Information Security	48
4. Big Data and Information Systems	48
5. Big Data and Marketing Analytics	48
6. Big Data and Business Intelligence	48
7. Big Data and Mathematical Modeling	48
8. Graph Analytics for Big Data	48

 

Students will be assessed by continuous coursework, including assignments, projects, mid-term tests, and final examinations.

Application Code	2270-IT057A	Apply Online Now
Apply Online Now

Venue

• Fortress Tower Learning Centre
• Island East Campus
• HKU SPACE Po Leung Kuk Stanley Ho Community College (HPSHCC) Campus

IMAT4046 Introduction to Big Data Applications and Analytics

This module is designed to help students develop an appreciation of the Big Data analytics approach to problem formulation and solution. The aim is to build up students’ ability to understand the importance of the applications of Big Data analytics in their daily life, particularly in commercial areas. Emphasis will be placed on both application modeling and solution methodology.

 

IMAT4047 Search Engine Optimisation and Web Analytics

This module is designed to teach marketing strategies and tactics on the Internet with a combination of using search engine optimization (SEO) and web analytics. Students will learn how to reach target customers, increase social influence and improve search engine positioning. Key topics to be discussed include optimising searchable websites, link building, web metrics measurements and analytics data.

 

IMAT4048 Big Data Privacy and Information Security

Students will explore information security risks and different approaches that organizations can use to mitigate these risks and implement security plans and processes.

 

IMAT4049 Big Data and Information Systems

This module is designed to provide students with skills and techniques to manage Big Data information systems and examine the benefits of managing Big Data.

 

IMAT4050 Big Data and Marketing Analytics

This module builds on various analytical models typically used in marketing nowadays. It aims to develop student’s abilities to use big data to drive decision in a marketing context. The emphasis is not only on theory and concept but also on enhancing their learning experience in applying and interpreting a range of data sources to generate insight for developing marketing solutions.

 

IMAT4051 Big Data and Business Intelligence

This module is designed to provide students with a foundation of the conceptual, theoretical and practical knowledge in the fields of Big Data and Business Intelligence required for various business purposes. Students will be trained to synthesize, manage and evaluate the information together with the use of information technology to convey the results of the analysis appropriately for business decision-making.

 

IMAT4052 Big Data and Mathematical Modeling

This module covers the key characteristics and the process of Big Data analysis, including Big Data preparation and transformation. It focuses on how Mathematics and Statistics underpin Big Data analysis. Students will develop the ability to analyse and summarise the main characteristics of Big Data sets by using the Modeling Process and Mathematical Modeling.

 

IMAT4053 Graph Analytics for Big Data

This module is designed to introduce the fundamentals of graph analytics. Students will develop the ability to formulate real-world problems using the graph analytics approach and choose appropriate techniques to solve real-world problems.

Application Fee

HK$150

Course Fee

• HK$52,000 (to be paid in 2 instalments)
  

Applicants shall

• have gained in the HKDSE Examination Level 2 in 5 subjects, including English Language; OR

• have gained in the HKALE Grade E in 1 AL or 2AS subjects, and HKCEE Level 2 in English Language* or equivalent

* With effect from 2007, HKU SPACE recognizes Grade E previously awarded for English Language (Syllabus B) (Grade C in the case of English Language (Syllabus A)) at HKCEE as an acceptable alternative to Level 2 in this subject at HKCEE.

 

• The CEF Institution Code of HKU SPACE is 100

CEF Courses
Advanced Diploma in Big Data Analytics and Applications
COURSE CODE 34F104400	FEES $52,000	ENQUIRY 2587-3233
Introduction to Big Data Applications and Analytics (Module from Advanced Diploma in Big Data Analytics and Applications)
COURSE CODE 34Z104411	FEES $6,500	ENQUIRY 2587-3233
Search Engine Optimisation and Web Analytics (Module from Advanced Diploma in Big Data Analytics and Applications)
COURSE CODE 34Z10442A	FEES $6,500	ENQUIRY 2587-3233
Big Data Privacy and Information Security (Module from Advanced Diploma in Big Data Analytics and Applications)
COURSE CODE 34Z104438	FEES $6,500	ENQUIRY 2587-3233
Big Data and Information Systems (Module from Advanced Diploma in Big Data Analytics and Applications)
COURSE CODE 34Z104446	FEES $6,500	ENQUIRY 2587-3233
Big Data and Marketing Analytics (Module from Advanced Diploma in Big Data Analytics and Applications)
COURSE CODE 34Z104454	FEES $6,500	ENQUIRY 2587-3233
Big Data and Business Intelligence (Module from Advanced Diploma in Big Data Analytics and Applications)
COURSE CODE 34Z104462	FEES $6,500	ENQUIRY 2587-3233
Big Data and Mathematical Modeling (Module from Advanced Diploma in Big Data Analytics and Applications)
COURSE CODE 34Z104470	FEES $6,500	ENQUIRY 2587-3233
Graph Analytics for Big Data (Module from Advanced Diploma in Big Data Analytics and Applications)
COURSE CODE 34Z104489	FEES $6,500	ENQUIRY 2587-3233

	Continuing Education Fund This course has been included in the list of reimbursable courses under the Continuing Education Fund.
	Continuing Education Fund Reimbursable Course (selected modules only) Some modules of this course have been included in the list of reimbursable courses under the Continuing Education Fund.
	Advanced Diploma in Big Data Analytics and Applications This course is recognised under the Qualifications Framework (QF Level [4])

Online Application Apply Now

Application Form Download Application Form

Enrolment Method

1. All applicants are required to complete one Application Form (SF26) and, either submit them in person or post them to Ms Katrina Knip, College of Life Sciences and Technology, HKU SPACE, at any of the HKU SPACE Enrolment Centres.
2. All applications, either by post or in person must be accompanied by:
   1. Certified photostat copies of full educational certificates and transcripts.

Note: When submitting your application in person at any of the HKU SPACE enrolment centers, please bring along the originals of your educational certificates / transcripts for certification.  If you are posting your application, please arrange to bring the originals of the relevant documents for certification at any of HKU SPACE Enrolment Centres before the commencement of classes.

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