ML: Concepts & Applications

• Acquire the skills necessary to utilize Python and libraries such as Scikit-learn, TensorFlow, and Pandas for data ingestion, investigation, preparation, and modeling.
• Support vector machines, decision trees and ensembles, clustering, PCA, hidden Markov models, deep learning, and linear regression are among the techniques that are employed to train and evaluate models.
• Acquire a conceptual understanding of these techniques in order to understand the significance and reasoning behind the results.
• Based on an introductory machine learning course from the University of Chicago, work with real-world datasets, primarily from public policy, to establish a foundation for advanced research.

Level: Intermediate

Certification Degree: Yes

Languages the Course is Available: 21

Offered by: On Coursera provided by The University of Chicago

Duration: 3 weeks at 12 hours a week

Schedule: Flexible