There are so many different trading or investing approaches as people in the market.
Many existing tools support the most common ones, but if you really want to success with an innovative practice, you have to build it on your own.
Due to its characteristics, Python is being adopted by the financial industry as its reference programming language.
But Python is not expensive as other financials tools are, in fact it is completely free. And it is not difficult to learn. So, why don't give it a try?
Learn how to apply Python to Trading and Investing with this Hands-on Course.
Improve your Programming and Investing Skills at a time.
Either if you can already program and are interested in Finance. Or if you are already a Finance practitioner and are interested in applying programming to your career. This is a course for you.
In addition to using this new knowledge for your own investments, new opportunities will widely open up for you if you are able to combine these two disciplines.
The volume of data is increasing at not seen before rates. And new algorithms and tools are needed to get the most of it. It is difficult to imagine a more promising skill in your career path than learning to manage and analyze data through programming.
Content and Overview
This course will start with a review of main Python libraries to use for Data Analysis.
Although due to the readability of Python it is not necessary to have previous knowledge of it. It is recommended at least to have a previous contact with it.
The main goal is to focus in the application of it to Finance concepts. So not much time will be addressed to common functions or data structures. You will be able, anyway, to send any doubt to the Instructor and if necessary new lectures will be upload replying most frequently asked questions.
The best way to learn is doing. So in the second part of the course, actual applications with the complete code will be developed. You will be able to test and modify them with your desired parameters or strategies and even propose new ones. Building, in this way, a community around the course that will help us to grow up individually.
New projects will be added periodically in the future, but the course price will go up accordingly. So enroll now, It will be your best investment.
In this lecture, the tool Ipython will be introduced.
Ipython is an interactive solution for running Python scripts very recommended for data analysis.
In this lecture, a demo run over Ipython will be shown, just to see how it works.
An overview of the different data structures for Data Analysis that will be explained in next lectures.
In this lecture, we will see the main Numpy Data Structures and their main functionality.
In this lecture, we will see the main Pandas Data Structures and their main functionality.
In this lecture, we will see how to save data to a plain file or csv and how to retrieve them from it.
In this lecture, we will see how to save data to an excel file and how to retrieve them from it.
In this lecture, we will see how to save data to a json file and how to retrieve them from it.
In this lecture, we will see how to index and select data from different Data Structures.
In this lecture, we will see how to Join, Merge and Concatenate different Dataframes.
In this lecture, we will see how to create basic charts from Dataframes.
Goals of this session are two:
In this second lecture about Time Value of Money we will see how to calculate:
Introduction to Platform Quantopian for backtesting algorithms written in Python
Ricardo Naya, Industrial Engineer, CPIM (Certified in Production and Inventory Management), SAP PP certified and MBA among other titles, has worked during more than 12 years in SAP implementation or improvement projects in main leader companies worldwide in different industries (Nestle, Alcatel, Roche, Burberry, ...).
SAP consulting experience has allowed him to know the processes and best practices in different industries, as long as adquire a deep knowledge of this ERP.
SAP consulting does not only require technical knowledge of the system, like execute the different transactions. But also a functional knowledge of why SAP offers the different options and which standard ones are allowed.
By means of his training courses, Ricardo hopes to deliver both approaches and in this way to ease the learning and understanding of SAP.
Ricardo Naya, Ingeniero Industrial Superior en Organización Industrial, CPIM (Certified in Production and Inventory Management), certificado en SAP PP y MBA entre otros estudios, ha trabajado durante más de 12 años en proyectos de implantación o de mejora de SAP en las principales empresas líderes mundiales de diferentes sectores (Nestlé, Alcatel, Roche, Burberry,...).
La experiencia en consultoría SAP le ha permitido conocer los procesos y las mejores prácticas en diferentes industrias, así como adquirir un amplio conocimiento de este ERP.
Trabajar con SAP no solo requiere unos conocimientos técnicos del sistema, cómo realizar las distintas transacciones por ejemplo. Sino también un conocimiento funcional de el porqué SAP las ofrece de una manera y qué opciones de configuración estándar permite.
Por medio de sus cursos de formación, Ricardo espera poder transmitir ambos enfoques y de este modo facilitar el aprendizaje y entendimiento de este ERP.