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20秋新港录取案例分享-南洋理工大学
  • 案例分类:
  • 录取专业:
  • 录取时间:20年3月
  • 奖学金:
  • 申请语言成绩:7
  • 申请人GPA:3.7
  • 申请人毕业院校:中山大学
  • 申请人所学专业:应用数学
  • 录取院校:南洋理工大学
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背景介绍

申请难点

留学规划与提升

 
 

Financial Technology (FinTech) refers to a cluster of emerging innovations that have the potential to revolutionize the nature of the finance industry, enhancing the productivity of financial firms by employing data science and cyber technologies. Global investment in FinTech has been so active in recent years that the Monetary Authority of Singapore has launched an in​itiative, the FinTech and Innovation Group, and pledged to spend S$225 million over the next five years to develop the FinTech sector in Singapore.

Nanyang Technological University, Singapore (NTU Singapore) offers a Master of Science in FinTech (MSc in FinTech) hosted by the School of Physical and Mathematical Sciences. The curriculum is built upon data science, artificial intelligence, and information technology to provide students with the FinTech skills necessary for navigating the changing landscape of the finance industry. Strong emphasis is placed on the in-depth mastery of disruptive technologies in finance, including financial automation (e.g. robo-advisors) and financial cryptography (e.g. blockchain technology).


Programme & Curriculum Structure

The MSc in FinTech Programme is an intensive 1-year full-time or 2-year part-time programme by coursework taught in 3 trimesters per year. The curriculum consists of two specializations: Artificial Intelligence and Operations and Compliance. ​​The courses in the MSc in FinTech programme are delivered in intensive periods of 7 weeks. In other words, each trimester is split into two halves. All courses are conducted at NTU (main campus) in the evenings of weekdays or Saturdays.

Practicum module, MH6809, starting in Trimester 3, will comprise either a research-based project or a self-sourced internship where students work on a professional consulting project mentored by experienced instructors to solve financial problems. The internship companies our students previously involved with include GIC, Julius Baer, Lumiq, DBS, OCBC, Macquarie Bank, CIMB, Grab, etc.​

The programme consists a total of 33 Academic Units (AUs), with 21 AUs of compulsory modules, 6 AUs from the chosen specialization's electives, and 6 AUs from other electives:

Compulsory courses 21 AUs
Prescribed Electives of the chosen specialization 6 AUs
Unrestricted Electives 6 AUs
Total graduation requirements 33 AUs

The requirements for graduation are as follow:

  1. ​​Successful completion of all requirements as prescribed by the programme of study; and
  2. A minimum CGPA of 2.50 is attained at the completion of the programme of study.​

For students who matriculated in AY2019/2020

AY2020/2021​

Compulsory Courses

MH8801 Introduction to ​FinTech (1.5AU)
MH8802 FinTech Ecosystem and Innovations (1.5AU)
MH8803 Principles of Finance and Risk Management (1.5AU)
MH8805 Algorithmic Trading and Robo-Advisors (1.5AU)
MH8807 Blockchain Systems I: Concepts and Principles (1.5AU) - Tentative
MH8811 Python Programming (1.5AU)
MH8812 Python for Data Analysis (1.5AU) - Tentative
MH8131 Probability and Statistics (1.5AU)
MH6151 Data Mining (3AU)
 
MH6809 Practicum (6AU)

ARTIFICIAL INTELLIGENCE PRESCRIBED ELECTIVE COURSES

MH6812 Advanced Natural Language Processing with Deep Learning (3 AU)
MH8804 Quantitative Methods in Finance (1.5AU)
MH8808 Blockchain Systems II: Development and Engineering (1.5AU) - Tentative

OPERATIONS AND COMPLIANCE PRESCRIBED ELECTIVE COURSES

MH8822 Regulatory Technology (1.5AU)
MH8821 Anti-Financial Crime and Compliance (1.5AU)
MH8331 Financial and Risk Analytics I (1.5AU)
MH8332 Financial and Risk Analytics II (1.5AU)

UNRESTRICTED ELECTIVE COURSES

MH8101 Operations Research I (1.5AU)
MH8102 Operations Research II (1.5AU)
MH8141 Time Series Analysis (1.5AU)
MH8341 Data Management and Business Intelligence (1.5AU)
MH6301 Information Retrieval and Analysis (3AU)
MH8831 Applied Cryptography (1.5AU)

院校解读

留学方案

案例分析

 

Message from the Head

Associate Professor Chan Song Heng 

The Division of Mathematical Sciences (MAS), founded in 2005, is one of three divisions under the School of Physical and Mathematical Sciences. In its first year, the division admitted 47 undergraduates while having only five faculty members. Today, the division has 35 faculty members from various research areas of pure mathematics, applied mathematics, statistics, and theoretical computer science. Our faculty members are active in research, and many have been successful in winning competitive research funding. The biggest and strongest research group in our division is the coding and cryptography group. The division has a graduate program with approximately 50 graduate students.

The division offers degree programs in Mathematical Sciences (MATH), Mathematical Sciences with a minor in finance (MAFI), and Mathematics and Economics (MAEC). Each year, we admit approximately 200 undergraduates into these programs. At the end of their second or third semester, students in MATH and MAFI will choose to specialize in one of four tracks: Business analytics, Pure Mathematics, Applied mathematics, or Statistics.

Our graduates have consistently proven to be highly employable, as reflected in the yearly MOE graduate employment survey. Our graduates have also gained admission to some of the top graduate schools around the world, including Cornell, the London School of Economics, Princeton, UC Berkeley, and University College London.

The division takes feedback seriously, whether it is from students, or from potential employers of our graduates, and we are constantly finding ways to further improve our students' overall experience and employability.

I invite you to explore our website to learn more about our division.

Associate Professor CHAN Song Heng
Head, Division of Mathematical Sciences


The Division of Mathematical Sciences offers the following Master of Science (MSc) programmes by coursework: MSc in Analytics and MSc in Financial Technology. These interdisciplinary post-graduate programmes are suitable for professionals seeking to leverage Business Analytics or Financial Technology in their chosen fields, as well as recent college graduates pursuing a career in business or finance.
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