Free Economics & Finance Courses for Data Scientists : There also exists plenty of data in both economics and finance, providing myriad opportunities for the application of your skills.
Are you interested in expanding your economics and/or finance domain knowledge? The key to being able to apply your data science skills to any field is to have at least a minimal understanding of it. There also exists plenty of data in both economics and finance, providing myriad opportunities for the application of your skills.
Economics and finance are related, but distinct, fields; economics "is the social science that studies the production, distribution, and consumption of goods and services" (Wikipedia), while the finance "is a term for matters regarding the management, creation, and study of money and investments" (Wikipedia). It is this related nature which leads us to group and discuss them together herein.
This is a selection of economics and finance courses which are freely available online, and which can help further your understanding of these domains. There are a high number of free finance and economics courses available online, so instead of flooding the zone with all the courses, here are a few select choices to get you started. They have been separated into the broad topics of economics foundations, finance foundations, and specialized topics, which are a more advanced mix of the two. Definitions come directly from the respective course websites.
Data science is omnipresent to advanced statistical and machine learning methods. For whatever length of time that there is data to analyse, the need to investigate is obvious.
The agenda of the talk included an introduction to 3D data, its applications and case studies, 3D data alignment and more.
Tableau Data Analysis Tips and Tricks. Master the one of the most powerful data analytics tool with some handy shortcut and tricks.
Analysis, Price Modeling and Prediction: AirBnB Data for Seattle. A detailed overview of AirBnB’s Seattle data analysis using Data Engineering & Machine Learning techniques.
DISCLAIMER: absolutely subjective point of view, for the official definition check out vocabularies or Wikipedia. And come on, you wouldn’t read an entire article just to get the definition.