Machine Learning Fundamentals
About this Course
Do you want to build systems that learn from experience? Or exploit data to create simple predictive models of the world? In this course, part of the Data Science MicroMasters program, you will learn a variety of supervised and unsupervised learning algorithms, and the theory behind those algorithms. Using real-world case studies, you will learn how to classify images, identify salient topics in a corpus of documents, partition people according to personality profiles, and automatically capture the semantic structure of words and use it to categorize documents. Armed with the knowledge from this course, you will be able to analyze many different types of data and to build descriptive and predictive models. All programming examples and assignments will be in Python, using Jupyter notebooks.Created by: The University of California, San Diego
Level: Advanced
Related Online Courses
Designing a data lake is challenging because of the scale and growth of data. Developers need to understand best practices to avoid common mistakes that could be hard to rectify. In this course we... more
This advanced Excel course builds on the teachings of Course 1: Core Foundations and Course 2: Data Management. Designed for experienced Excel users, master the techniques needed to draw insights... more
If you’re interested in data analysis and interpretation, then this is the data science course for you. We start by learning the mathematical definition of distance and use this to motivate the u... more
In this course, gain experience in data visualization and cloud technologies to support business analytics. In the first half of the course, create and share compelling data visualizations to... more
The first in our Professional Certificate Program in Data Science, this course will introduce you to the basics of R programming. You can better retain R when you learn it to solve a specific... more
Powered by
