Here I provide up to date description of teaching activities. Some courses have Github repositories where handouts, problem sets and other resources are available. Let me know if you have any questions or comments regarding the materials.

Lecturer (2015-)

Bayesian Optimization

  • Info: Barcelona Graduate School of Economics, Master of Data Science, 6 hours, part of Topics in Big Data Analytics II.
  • Description: The objective is to provide introduction to the theory behind the Bayesian optimization and give sufficient amount of know-how to immediately incorporate it into the workflow and substitute less efficient grid-search methods where appropriate.
  • Offerings: 2016/2017.

Introduction to Computing

  • Info: Barcelona Graduate School of Economics, Master of Data Science, 20 hours.
  • Description: Provides introduction to Unix operating systems and programming in Bash, computing on servers and cloud (Amazon Web Services), and a thorough overview of programming in R.
  • Offerings: 2015/2016, 2016/2017, 2017/2018.

The Data Science Toolbox

  • Info: Barcelona Graduate School of Economics, Data Science Summer School, 8 hours.
  • Description: Course provides introduction to Python and R for Machine Learning and scaling up computations with cloud computing (Amazon Web Services).
  • Offerings: Summer 2016.

Advanced Computational Methods

  • Info: Barcelona Graduate School of Economics, Master of Data Science, 20 hours.
  • Description: The course covers the practical side of classification machine learning algorithms, focusing on selected few and programming them from scratch. It stresses various computational aspects of the implementation – from running computations in parallel to distributed computing with tools such as Spark. A classification competition on Kaggle in Class serves as a practice ground.
  • Offerings: 2015/2016

Teaching Assistant (2011-2016)

  • Machine Learning: Barcelona Graduate School of Economics, Master of Data Science, prof. Gabor Lugosi; Nominated for the best teaching assistant award in the Department of Economics and Business; 15 hours, 2015.
  • Computational statistics with R: Universitat Pompeu Fabra, Econ undergraduate, prof. Albert Satorra; 20 hours; 2016.
  • Econometrics 1: Universitat Pompeu Fabra, Econ undergraduate, prof. Christian Fons Rosen; 30 hours; 2015.
  • Social psychology in Organizations: Universitat Pompeu Fabra, Econ undergraduate, prof. Gael Le Mens; ~80 hours; 2012/2013/2014.
  • Microeconomics 1: Universitat Pompeu Fabra, Econ undergraduate, prof. Helena Perrone; 20 hours; 2012.
  • Introduction to Game theory: Universitat Pompeu Fabra, Econ undergraduate, prof. Helena Perrone; 30 hours; 2012.
  • Introduction to Microeconomics : Universitat Pompeu Fabra, Econ undergraduate, prof. Rosemarie Nagel; 30 hours; 2011.