Hands-on HR Analytics - Predict Job Offer Drop Out Using R

Our mission is simple – “Help anyone learn Data Science, HR Analytics, create projects they were passionate about, and use those projects to improve their careers and lives”.This is hands-on project-based course which offers an end-to end statistical project, guiding you to develop and master practical skills to solve any HR business problem using Step-by-step approach called “Anatomy of a Statistical Model for HR Analytics”.This is the course you’ve been looking for, to start building a portfolio of great HR Analytics projects. This without any doubt, is one of the best ways you can advance your HR analytics and data science career.In fact, when we spoke to data science recruiters and hiring managers all over the world, we heard the same thing over and over again: data science portfolios and Git-hub repositories are among the first things they look at. Employers want to see if you can really do the job you’re being hired for, so having real-world projects to prove your skills you’re claiming on your resume is a must, whether or not you have a fancy degree.Major takeaways:1. In this course you will learn to use a logistic regression machine learning technique to reduce an important HR issue “RENEGE”
2. This course starts with a fundamental understanding of what is Recruitment process, Various Recruitment metrics you must know, and how renege can actually impact the Business ROI
3. After finishing this course, you will be able to convert Renege business problem into a Statistical problem, know how to discover and collect data, how to prepare and explore the data for meaningful insights using various methods such as Uni-variate and Bi-variate Analysis, hypothesis testing etc,Apply appropriate machine learning technique to predict offer dropout, extract major findings and insights from the statistical solution and finally how the insights will help leaders make strategies and policies to reduce offer dropout.
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