How to code machine learning algorithms with Python
Machine learning algorithms with Python
The profession of data scientist is one of the most sought-after in the 21st century. This part time online course from StackFuel will teach you how to use supervised and unsupervised machine learning algorithms, different data visualization methods and data storytelling so that you are able to take on the role of data scientist after you finish the course. You will develop the skills you need to work as a data scientist. You can then apply the knowledge you gained in your department and implement machine learning algorithms by yourself. During the course, you will work in our browser-based, interactive learning environment, the Data Lab. This is a full programming environment where you can execute code you write yourself.
The objective of the course is to understand and use performance metrics and assumptions from supervised and unsupervised learning models with sklearn. You will also learn
data storytelling principles as well as best practices for informative visualization design with bokeh algorithms from supervised and unsupervised learning, such as decision trees and random forests.
A good knowledge of Python and common modules (pandas, matplotlib) is required to participate in the Data Scientist Course.
The Data Scientist course is suitable for anyone who wants to analyze data and make predictions based on this data in order to make data-driven decisions. You should be also be interested in machine learning.