Course Description




Data science is the study of data. Its aim is to understand how to read and extract information from both structured and unstructured data. It combines statistics, data analysis, and machine learning to capture and decipher real-world facts with the use of computers and software. As such, it involves a strong familiarity with mathematics, computer science, and information theory; and it applies these to better understand real-world statistics.

Core Curriculum

The core topics introduce the field of data science and give students the skills and understanding to choose and pursue their interests in the specialized topics. On completing the core, students will be able to independently read the historical and academic literature. The core topics are:

  • Statistics and Probability Theory
  • Linear Algebra
  • Introductory Network Theory
  • Databases
  • Data Mining
  • Numerical and Scientific Programming
  • Data Visualization
  • Machine Learning
  • Scientific Writing

The student is expected to be a competent computer scientist, mathematician, physicist, or engineer with computer programming expertise before commencing their studies in data science.


Specializations should be discussed with the Director of Studies. On completing specializations, students will be able to independently read advanced literature and conduct a final project in that topic. Some suggested specializations are:

  • Statistical Learning
  • Statistics in Finance
  • Agents and Multi-Agent Systems
  • Nature-Inspired Learning Algorithms
  • Deep Learning
  • Big Data Technologies
  • Simulation
  • Computer Vision
  • Machine Learning
  • Optimization Methods
  • Artificial Intelligence

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