Teaching

  • Signals and Systems (Fall-2018)
    • Classical undergraduate course covering liner time-invariant systems, Laplace transform, Fourier series, Fourier transform, etc.
    • Syllabus
  • Data Analytics (Spring-2017,2018,2019)
    • Introductory machine learning course covering Bayesian learning, regression, classification, clustering, dimensionality reduction, etc. (own design)
    • Syllabus
  • Advanced Data Analytics (Fall-2017,2018)
    • Graduate machine learning course covering manifold learning, mixture models, graphical models, approximate inference, etc. (own design)
    • Syllabus