Page 89 - PG-Handbook23-24-finale

WQD7011 Numerical Optimization

Learning Outcomes
At the end of the course, students are able to:
1. Explain the key principles and values pertinent to numerical optimization and linear algebra
2. Apply and implement numerical solution methods
3. Interpret the numerical solutions with respect to their accuracy and suitability

Synopsis of Course Content
The course will provide an opportunity for in-depth study of numerical methods and linear algebra.
Topics relevant to the course are as follows: Numerical analysis, Polynomial Interpolation, Numerical
Integration, Resolution of non-linear systems, Resolution of large linear systems, Eigenvalues
approximation, Numerical solution of ODEs and Numerical solution of PDEs
Evaluation and Weightage
Continuous Assessment : 60%
Final Examination : 40%

WQD7002 Data Science Research Project

Learning Outcomes
At the end of the course, the student are able to:
1. Apply data science techniques to solve data science problems in real world environment
2. Professionally present the project plan and results
3. Write a project report

Synopsis of Course Content
The capstone project allows students to use public data or create data product by applying their
knowledge in foundations, theory and methods of data science to address problems in industry and
government. During the project, students engage in the entire process of solving a real-world data
science project, from collecting and processing data, to designing the best method to solve identified
problem, to applying suitable analytic methods, and finally, to implementing a solution.

Evaluation and Weightage
Continuous Assessment : 100%