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.
Learn the fundamentals of neural networks and how to build deep learning models using Keras 2.0.
Learn to train and assess models performing common machine learning tasks such as classification, regression and clustering.
Learn to produce meaningful and beautiful data visualizations with ggplot2 by understanding the grammar of graphics.
Learn more complex data visualization techniques using Matplotlib and Seaborn.
In this course, you will learn to read CSV, XLS, and text files in R using tools like readxl and data.table.
Learn the art of writing your own functions in Python, as well as key concepts like scoping and error handling.
Learn to explore your data so you can properly clean and prepare it for analysis.