This course presents concepts and techniques in modern data science. The course is geared towards understanding at a technical level, the theory behind commonly used machine learning techniques, with practical considerations for model development, selection, evaluation, data exploration and feature engineering. The course examines the use of machine learning in business, how to effectively operate in a data science environment, and work through technical and business considerations for model deployment.
Course Author: Alik Sokolov
Who should take this course?
You aspire to become a better practitioner or consumer of machine learning. This course will be useful both for beginners looking for a deep introduction to the field, or intermediate level professionals who wish to improve their practical skills in machine learning.
What’s the minimum skill level necessary?
A Bachelor’s Degree in Business, Finance, or Mathematics. Intermediate-level competency in mathematics and Excel. Basic fluency in Python is helpful but not required.
How long do I have to complete this course?
You will have access to course content for 365 days from enrollment date and can choose to complete the course at any time during this period.
English, Chinese (Simplified)