- R Programming
- Applied Machine Learning
- Exploratory Data Analysis
- Feature Engineering
- Supervised Learning
- Machine Learning
- Data Wrangling
- Regression Analysis
- Machine Learning Algorithms
- Data Preprocessing
- Predictive Modeling
- Classification Algorithms
Practical Machine Learning
Completed by David Salama
December 19, 2024
8 hours (approximately)
David Salama's account is verified. Coursera certifies their successful completion of Practical Machine Learning
What you will learn
Use the basic components of building and applying prediction functions
Understand concepts such as training and tests sets, overfitting, and error rates
Describe machine learning methods such as regression or classification trees
Explain the complete process of building prediction functions
Skills you will gain
