Course
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In this course you will learn the basics of machine learning for classification.
In this course you will learn the basics of machine learning for classification.
Track
Predict categorical and numeric responses via classification and regression, and discover the hidden structure of datasets with unsupervised learning.
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Make progress on the go with our mobile courses and daily 5-minute coding challenges.
Course
In this course you will learn the basics of machine learning for classification.
In this course you will learn the basics of machine learning for classification.
Course
In this course you will learn how to predict future events using linear regression, generalized additive models, random forests, and xgboost.
In this course you will learn how to predict future events using linear regression, generalized additive models, random forests, and xgboost.
Project
Help a fast food chain save money and place more accurate orders by building a model to predict food sales.
Help a fast food chain save money and place more accurate orders by building a model to predict food sales.
Course
This course provides an intro to clustering and dimensionality reduction in R from a machine learning perspective.
This course provides an intro to clustering and dimensionality reduction in R from a machine learning perspective.
Course
This course teaches the big ideas in machine learning like how to build and evaluate predictive models.
This course teaches the big ideas in machine learning like how to build and evaluate predictive models.
Machine Learning Fundamentals in R
Track
Complete
VP, Data Science at DataRobot
Yes, this track is suitable for beginners. Working through this track, users will gain a comprehensive understanding of the basics of machine learning such as how to process data for modeling, how to train models, evaluate their performance, and tune their parameters for better performance.
This track uses the R programming language.
This track is beneficial for individuals interested in jobs such as data science, machine learning engineer, and artificial intelligence specialist.
This track will provide users the foundational knowledge for using machine learning in a variety of scenarios. Users will be able to understand and leverage the principles of supervised and unsupervised learning, creating and visualizing models, and understanding and tuning their parameters.
This track typically takes 24 hours to complete as it consists of several courses.
A skill track typically consists of a series of courses/content that teaches users a specific domain-specific topic/skill from start to finish. In comparison, a career track typically involves a set of courses/content that teaches more advanced topics and subjects, which are geared towards professional development and job readiness.
No, this track is specifically designed for the R programming language.
This track covers predicting categorical and numeric responses via classification and regression, and discovering the hidden structure of datasets (unsupervised learning). It also teaches users about how to process data for modeling, how to train your models, how to visualize your models and assess their performance, and how to tune their parameters for better performance.
The tracks helped me complete my journey without feeling lost. Each course builds on the last, keeping me motivated and on track

DataCamp helped me transition from someone curious about data to someone actively applying these skills in my job
I've been using DataCamp for four years, and it's helped me transition from filling gaps in my skills to proactively creating value for my company