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Tuesdays 17:30 - 19:00 
Starting date: 12 February 2019
Finishing date: 5 March 2019
Duration: 4 lessons
Course instructor: Olga Bychkova

Registration for this course is closed.

Please read about our selection process. Follow EDH on Facebook for the latest news and tips.

If you need to improve your Math skills before diving deeper into economics studies or research, this is the right course for you.

Prerequisites:

• Basic knowledge of high school mathematics.

Lectures:

1. Differentiation: Functions of One and Multiple Variables. 

We will practice in finding first- and second-order, partial and total derivatives of different functions, explore the nature of functions' monotonicity.

2. Static and Constrained Optimization.

We will practice in finding the extrema of different functions and exploring their nature, determine the intervals of convexity and concavity, as well as inflection points.

3. Integration.

We will practice in finding both indefinite and definite integrals.

4. Linear Algebra: Vectors and Matrices.

We will discuss linear (in)dependency of the vectors and (non)singularity of the matrices, practice in computing the sum, difference, and product of vectors and matrices, solving the matrix equations. In addition, we will discuss how to determine the rank of the matrix and the inverse matrix and how to solve the systems of linear equations using matrices.

Participants who attend at least 75% of the sessions can claim a Certificate of Attendance issued by CERGE-EI.

About the facilitator:

Olga Bychkova

Olga is a CERGE-EI PhD Candidate and Junior Researcher. Her dissertation focuses on corporate as well as public finance. In particular, the three studies contribute to the venture capital investment and macro-financial shocks' spillovers fields. The analytical side of her research is based on mathematical modeling. Since 2015, she has regularly taught econometrics and finance courses heavily based on different mathematical concepts. In her free time, Olga enjoys reading, cooking, and traveling.

We thank our partners for supporting the Economics Discovery Hub.

Tuesdays and Thursdays 18:00 - 19:30 
Starting date: 12 February 2019
Finishing date: 28 February 2019
Duration: 6 lessons
Course instructor: Pablo Maldonado

Registration for this course is closed.

Please read about our selection process. Follow EDH on Facebook for the latest news and tips.

In this course we will go to the basics of Machine Learning. At the end of the course you would be familiar with the scikit-learn machine learning library.          

Prerequisites:

• Familiarity with Python.
• The Anaconda distribution for Python 3 should be installed and working on your computer.

Lectures:

• The ML pipeline for classification and regression.
• Decision Trees and ensemble models (gradient boosting, random forests).
• Unsupervised learning: clustering and dimensionality reduction.
• Case study.

Practical assignment:

• During the last lecture you will solve a case study end-to-end and present your findings.

Participants who attend at least 75% of the sessions can claim a Certificate of Attendance issued by CERGE-EI.

About the facilitator:

Pablo Maldonado
Pablo earned his Ph.D. in Applied Mathematics at the Universite Paris VI - Pierre et Marie Curie in France.  He is currently a data science consultant and lecturer at the Czech Technical University in Prague. Previously, he worked for O2 Czech Republic and PricewaterhouseCoopers as a data scientist, and lectured in two Mexican universities. In his spare time, Pablo enjoys cooking and improving his salsa and drumming skills.

We thank our partners for supporting the Economics Discovery Hub.