Master the basics of data analysis in Python. Expand your data science skill set by learning scientific computing with numpy.
Master the basics of data analysis by manipulating common data structures such as vectors, matrices and data frames.
Continue your journey to become an R ninja by learning about conditional statements, loops, and vector functions.
This course provides a basic introduction to clustering and dimensionality reduction in R from a machine learning perspective.
Learn to train and assess models performing common machine learning tasks such as classification, regression and clustering.
Learn how to build and tune predictive models and evaluate how well they will perform on unseen data.
Learn to produce meaningful and beautiful data visualizations with ggplot2 by understanding the grammar of graphics.
Learn to explore your data so you can properly clean and prepare it for analysis.
In this course, you will learn to read CSV, XLS, and text files in R using tools like readxl and data.table.
Master fundamental techniques for data manipulation using the select, mutate, filter, arrange, and summarise functions in dplyr.
Learn how to pull character strings apart, put them back together and use the stringr package.
Learn how to access financial data from local files as well as from internet sources.