Accounting & FinanceFinTech and Financial Intelligence
Executive Certificate in Financial Decision Making: Big Data and Machine Learning
- Course Code
- Application Code
- Study mode
- Start Date
- 30 Nov 2019 (Sat)
- Next intake(s)
- Feb 2020
- 1 month to 2 months
- Course Fee
- HK$8000 per programme
In the Big Data era, Machine Learning (ML), an important branch of Artificial Intelligence (AI), adopts scientific study of algorithms and statistical models to improve their performance. By using the techniques of ML, data mining and predictive modelling, data analysts will be able to identify hidden relationships, discover new patterns, explore potential opportunities, and thus make better financial decisions. This programme will cover popular techniques of ML and Predictive Analytics such as Regression Analysis, Decision trees, Random Forest, Naive Bayes, Nearest Neighbors, Neural Networks, K-Means, and Time Series Forecasting. To illustrate more applications, practical cases and issues related to Big Data platforms or model evaluation will be introduced.
This programme targets Executives who would like to acquire the knowledge of Big Data and Machine Learning to assist their decision making. Also, learners who plan to acquire knowledge of Data Analytics and apply ML in their workplace are highly welcomed. To handle Big Data, the basics of programming language will be briefly delivered at the beginning and various Machine Learning Models will be illustrated with program code in a simple manner. No advanced statistical knowledge or programming skills is assumed.
"Think BIG DATA, Think HKU SPACE"
This programme aims to provide students with the fundamental concepts and knowledge about Big Data and to develop their analytical skills by applying regression analysis and machine learning to solve business problems. It provides a practical approach for the students to apply regression and machine learning methodologies for analyzing big data and facilitating business and financial decision making.
On completion of the programme, students should be able to:
- Outline data preparation procedures and examine the process for handling Big Data;
- Interpret regression results and build business models using regression methods;
- Apply machine learning methodologies to perform analysis and forecasting;
- Evaluate various regression and machine learning methods as well as identify patterns for business and financial decision making.
1) Mr. Chung, is a specialist in Machine Learning, Statistical Analysis and Data Science. He received his Bachelor and Master Degree in Mathematics from the University of Toronto. He had been a Mathematics and Statistics lecturer in HKUSPACE Community College for more than six years. Since 2013, he became interested and has been doing research in Data Science and Machine Learning. Coming from an academic background, and then working as a machine learning engineer and data scientist, Mr. Chung likes to discuss Data Science and Machine Learning from both theoretical and practical perspectives.
2) Mr. W. C. Chan, FRM, has possessed rich experience in financial risk management, information technology and data science and worked as IT Manager over a decade. Being a practitioner in information technology, he is currently a consultant and trainer at Big Data Consultancy Services Company. Also, he is strong in Cloud-based solutions, Big Data Technology, Data Mining and Machine Learning. Moreover, Mr. Chan has obtained a Bachelor Degree in Mathematics from The Chinese University of Hong Kong as well as three Master Degrees in Risk Management Science from The Chinese University of Hong Kong, Quantitative Analysis for Business from City University of Hong Kong and Industrial Logistics Systems from The Hong Kong Polytechnic University.
3) Ms. Rowena Lai , is a practitioner in Business and Data Analytics. With a Bachelor of Science (Major in Mathematics and Minor in Economics) from The Chinese University of Hong Kong, two Master of Science degrees in both International Shipping and Transport Logistics as well as Global Supply Chain Management from The Hong Kong Polytechnic University, she has worked with different industries on business analytics area. Ms Lai is currently working in a leading banking and leading various data analytics projects. She has also worked in an airline industry leader, and shipping industry on Revenue Management and Business Analytics. Thanks to her strong business and analytical sense together with her extended working exposure, she would like to share her academic knowledge and practical experience in Data Science and Analytics.
|Application Code||1755-EP128A||Apply Online Now|
|Apply Online Now|
Days / Time
- Saturday, 2:00pm - 7:00pm
- 30 hours per module
- Kowloon East Campus
- Hong Kong Island Campus
(1) Data Preparation for Big Data
- Data Preparation Process: Data Cleansing, Data Integration, Data Evaluation
- Import Data
- Data Cleansing: Handle Missing Values, Recode and Rescale Variables, Separate into Training and Testing Sets
- Solution for handling Big Data: Hadoop, AWS, Azure
(2) Regression Analysis and Business Model Building
- Concepts and techniques of regression analysis
- Assumption Validation and Model Assessment by interpretation of statistical results
- Issues on analysis of financial Big Data and Cases on business model building
(3) Machine Learning and Forecasting for Big Data
- Supervised and unsupervised learning approaches: Decision Tree, Regression, Artificial Neural Networks, Cluster Analysis, Association Rule Mining
- Naïve Bayes Model for Machine Learning
- Time Series Model for forecasting and model building
- Multivariate Data Analysis (MDA)
- Natural Language Processing (NLP): Text Mining, Sentimental Analysis
- Case study of machine learning for business and financial decision making
November 2019 intake (M22164)
|1||30 Nov 19 (Sat)||14:00 - 19:00|
|2||7 Dec 19 (Sat)||14:00 - 19:00|
|3||14 Dec 19 (Sat)||14:00 - 19:00|
|4||21 Dec 19 (Sat)||14:00 - 19:00|
|5||4 Jan 20 (Sat)||14:00 - 19:00|
|6||11 Jan 20 (Sat)||14:00 - 19:00|
Remarks : Tentative timetable is subject to change and course commencement is subject to sufficient enrollment numbers.
Applicants shall hold:
- a bachelor’s degree awarded by a recognized University or equivalent; or
- an Associate Degree/ a Higher Diploma or equivalent, and have at least 2 years of relevant working experience.
Applicants with statistical background are preferred. Those with other qualification and substantial senior level work experience will be considered on individual merit.
**Please upload copy of HKID and proof of degree while applying online.
HK$150 student only needs to pay one time application fee for all EC in Big Data SeriesCourse Fee
- Course Fee : HK$8000 per programme (course fees are subject to change without prior notice)
Online Application Apply Now
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HKU SPACE provides 24-hour online application and payment service for students to make enrolment for most open admission courses (courses enrolled on first come, first served basis) and selected award-bearing programmes via the Internet. Applicants may settle the payment by using either PPS, VISA or Mastercard online.
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