LII:Machine Learning for Data Science and Analytics

Title: Machine Learning for Data Science and Analytics

Author for citation: Salleb-Aouissi et al.

License for content: Unknown

Publication date: 2021

This is a Columbia University-created course that is released on the edX platform. The self-paced five-week course is designed to help learners "develop a basic understanding of the principles of machine learning and derive practical solutions using predictive analytics." The course is free to take, requiring about seven to 10 hours per week of effort. A Verified Certificate can be added for $99.

The edX course description:

"Machine Learning is a growing field that is used when searching the web, placing ads, credit scoring, stock trading and for many other applications.

This data science course is an introduction to machine learning and algorithms. You will develop a basic understanding of the principles of machine learning and derive practical solutions using predictive analytics. We will also examine why algorithms play an essential role in big data analysis.

What you'll learn:

What machine learning is and how it is related to statistics and data analysis
How machine learning uses computer algorithms to search for patterns in data
How to use data patterns to make decisions and predictions with real-world examples from healthcare involving genomics and preterm birth
How to uncover hidden themes in large collections of documents using topic modeling
How to prepare data, deal with missing data and create custom data analysis solutions for different industries
Basic and frequently used algorithmic techniques including sorting, searching, greedy algorithms and dynamic programming"

About the authors

The course has six instructors associated with it. See the "meet the instructors" section to see more about each instructor.