Python has become one of the most important programming languages for professional finance worldwide. This workshop intends to present and to practice Python basic components and features together with several practical examples of Python applications related to finance. It will be presented mainly through exercises to practice during classes. Students are encouraged to bring their laptops to classes and practise ongoing exercises. At the end,  students will be able to develop basic Python applications with Data Extraction, Data Analysis and Data Output features.

1–Basics 1
.Python Language History and Overview 
.Python Installation, Interpreters and Versions 
.Variables
2–Basics 2
.Functions and Loops
.Data and Variable  Types
.Data Input and Output
3–Modules 1
.Python Modules–general view
.Python Module installation
.Numpy
.SciPy
4–Modules 2
.Matplotlib
.Statsmodels
.Pandas
.Other useful Python modules for finance
5–Sources of Data, Extracting Output Data 
.Sources of Data
.From Financial APIs
.From Excel file
.Extracting Output Data
.to a text file
.to a .csv file
.to a Excel file
.Using Pandas DataFrame 
6–
.Special DataSets-Dictionaries 
.Financial Applications A-Examples
.NPV and IRR
.Stock Price Movements, Return Distributions
7–Financial Applications
.Financial Applications B-Examples
.Bond Valuation
.CAPM–computing beta
.Time Series Analysis
.Portfolio Theory
8–Financial Applications–C
.Options 
.VaR and Expected Shortfall
.Monte Carlo Simulation

Brief presentation of  Python main concepts, features and modules as well as its proper installation. Practical exercises during classes to be performed  by teacher and students in their laptops will be the main methodology in order  to achieve workshop learning objectives.  Final qualitative evaluation will consist on  the development of  a financial application by each one of the  students to be delivered at the end of the Workshop.