HR Analytics: Exploring Employee Data in R
Learn how to manipulate, visualize, and perform statistical tests through a series of HR analytics case studies.
Follow short videos led by expert instructors and then practice what you’ve learned with interactive exercises in your browser.
Learn how to manipulate, visualize, and perform statistical tests through a series of HR analytics case studies.
Learn about experimental design, and how to explore your data to ask and answer meaningful questions.
Learn to analyze and visualize network data with the igraph package and create interactive network plots with threejs.
Learn how to pull character strings apart, put them back together and use the stringr package.
Learn how to analyze survey data with Python and discover when it is appropriate to apply statistical tools that are descriptive and inferential in nature.
This course will introduce the support vector machine (SVM) using an intuitive, visual approach.
Learn dimensionality reduction techniques in R and master feature selection and extraction for your own data and models.
Learn the principles of feature engineering for machine learning models and how to implement them using the R tidymodels framework.
Dive into our Tableau case study on supply chain analytics. Tackle shipment, inventory management, and dashboard creation to drive business improvements.
Learn Java from the ground up with this beginner-friendly course, mastering essential programming concepts and skills.
This course is for R users who want to get up to speed with Python!
Gain an overview of all the skills and tools needed to excel in Natural Language Processing in R.
In this course, you’ll learn to classify, treat and analyze time series; an absolute must, if you’re serious about stepping up as an analytics professional.
Explore HR data analysis in Tableau with this case study.
Learn the basics of A/B testing in R, including how to design experiments, analyze data, predict outcomes, and present results through visualizations.
This course will show you how to combine and merge datasets with data.table.
Learn sentiment analysis by identifying positive and negative language, specific emotional intent and making compelling visualizations.
Learn how to import, clean and manipulate IoT data in Python to make it ready for machine learning.
Learn how to analyse and interpret ChIP-seq data with the help of Bioconductor using a human cancer dataset.
Learn to use R to develop models to evaluate and analyze bonds as well as protect them from interest rate changes.
In ecommerce, increasing sales and reducing expenses are top priorities. In this case study, youll investigate data from an online pet supply company.
Learn how to visualize time series in R, then practice with a stock-picking case study.
Learn how to access financial data from local files as well as from internet sources.
Practice your Shiny skills while building some fun Shiny apps for real-life scenarios!
Learn how bonds work and how to price them and assess some of their risks using the numpy and numpy-financial packages.
This course covers the basics of financial trading and how to use quantstrat to build signal-based trading strategies.
Strengthen your knowledge of the topics covered in Manipulating Time Series in R using real case study data.
Learn to easily summarize and manipulate lists using the purrr package.
In this course youll learn how to apply machine learning in the HR domain.
Learn to distinguish real differences from random noise, and explore psychological crutches we use that interfere with our rational decision making.