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4.2.2.4    Master of Science in Data Science and Machine Learning (Full-Time and Part-Time)

  Home / NUS Bulletin AY2020/21 / Faculty of Science / Graduate Education / Coursework Programmes / Degree Requirements / Master of Science in Data Science and Machine Learning (Full-Time and Part-Time)

The MSc in Data Science and Machine Learning programme is offered jointly by the Department of Mathematics, the Department of Statistics and Applied Probability and the Department of Computer Science. This one-year programme will help to meet the growing demands for big-data professionals by transforming graduates with Bachelor degrees in quantitative science (e.g. mathematics, applied mathematics, statistics and physics) into practitioners.

The curriculum incorporates inter-disciplinary learning from computer science, mathematics and statistics. It also combines data analytics with machine learning. In addition to learning knowledge in data science, students will also have opportunities to explore the integration of machine learning and data analytics in sectors such as financial industry, healthcare and government.

Admission Requirements

Candidates must have

  • An Honours degree in a quantitative science (e.g. mathematics, applied mathematics, statistics and physics), engineering or computer science.

In addition, a candidate whose medium of undergraduate instruction is not English must complete TOEFL or IELTS. A minimum TOEFL score of 85 is required for the internet-based test (with a minimum of 22 for the writing section), or 580 for the paper-based test, or 260 for the computer-based test; while a minimum IELTS score of 6.0 is required.

Programme Structure

  1. Students have to
    1. Read and pass five essential modules;
    2. Read and pass five elective modules from at least two Graduate Certificate (GC) tracks/clusters;

Module List

Five Essential Modules

  • CS5224 Cloud Computing
  • DSA4212 Optimisation for Large-Scale Data-Driven Inference
  • DSA5101 Introduction to Big Data for Industry
  • DSA5102X Foundations of Machine Learning
  • DSA5201 DSML Industry Consulting and Applications Project

Five Elective Modules

Graduate Certificate in Deep Learning for Data Scientists

  • DSA5202 Advanced Topics in Machine Learning
  • DSA5204 Deep Learning and Applications (or CS5242 Neural Networks and Deep Learning)

Graduate Certificate in Data Mining for Industry

  • CS5228 Knowledge Discovery and Data Mining
  • ST5227 Applied Data Mining

Graduate Certificate in Big Data for Industry

  • CS5344 Big-Data Analytics Technology
  • ST5201 Statistical Foundations of Data Science

Graduate Certificate in Computer Vision

  • CS4243 Computer Vision and Pattern Recognition
  • CS5240 Theoretical Foundation of Multimedia
  • DSA5203 Visual Data Processing and Interpretation

Graduate Certificate in Data Science for Quantitative Finance

  • QF5204 Numerical Methods in Quantitative Finance
  • DSA5205 Data Science in Quantitative Finance
  • ST5202 Applied Regression Analysis

Graduate Certificate in Data Science for Internet of Things

  • EE5022 Cyber Security for Internet of Things
  • EE5024 IoT Sensor Networks
  • EE5025 Intellectual Property: Innovations in IoT
  • EE5027 Statistical Pattern Recognition
  • ST5225 Statistical Analysis of Networks

Graduate Certificate in Health Informatics

  • SPH5414 Informatics for Health
  • SPH5104 Healthcare Analytics
  • SPH5411 Information Technology in Healthcare

Cluster in Mathematics

  • MA4230 Matrix Computation
  • MA5232 Modeling and Simulations
  • MA5266 Optimization

Cluster in Statistics

  • ST5207 Nonparametric Regression
  • ST5210 Multivariate Data Analysis

Cluster in Computing

  • CS4248 Natural Language Processing
  • CS5234 Algorithms at Scale
  • CS5246 Text Mining
  • CS5245 Big Data Systems for Data Science
  • IS5152 Data Driven Decision Making

 

2. Obtain a minimum Cumulative Average Point (CAP) of 3.00.

 

Candidature & Application

The candidature for full-time students is from a minimum of two semesters to a maximum of four semesters.
The candidature for part-time students is from a minimum of four semesters to a maximum of eight semesters.

Programme Intake

There is one intake per academic year in August.

  Home / NUS Bulletin AY2020/21 / Faculty of Science / Graduate Education / Coursework Programmes / Degree Requirements / Master of Science in Data Science and Machine Learning (Full-Time and Part-Time)