This course introduces machine learning in an approachable way and provides step-by-step guidance on how to get started with machine learning via the most in-demand language in use today, Python.
In this course, you can learn how to apply core OOP principles like inheritance and composition along with some Python-specific features like “magic” methods and data classes to build programs that are extensible and efficient.
This course, leveraging the Python programming language, explains concepts in a fun and accessible way.
Get a fast-paced introduction to Python. In this course, you can learn what Python is and why it's become such a powerful and in-demand programming language.
Python—the popular and highly readable object-oriented language—is both powerful and relatively easy to learn. This course provides an overview of the installation process, basic Python syntax, and an example of how to construct and run a simple Python program.
Python is one of the most used dynamic languages for many large organizations, including Google, Yahoo, and IBM. Learn day-to-day programming in Python, including data types, data structures, operators and statements, control flow, loops, functions, classes, exception handling, and file management.
This training series provides a thorough introduction to R, with detailed instruction for working with R and RStudio and hands-on examples, from exploratory graphics to neural networks.
Review language basics, discover methods to improve existing R code, explore new and interesting features, and learn about useful development tools and libraries that will make your time programming with R that much more productive.
This training series provides a thorough introduction to R, with detailed instruction for installing and navigating R and RStudio and hands-on examples, from exploratory graphics to neural networks.
Data scientists who use Excel realize that R is emerging as the new standard for statistical wrangling (especially for larger data sets). This course serves as the perfect bridge for the many Excel-reliant data analysts and business users who need to update their data science skills by learning R.