HR Analytics: Workforce Optimization with Machine Learning

Welcome to HR Analytics: Workforce Optimization with Machine Learning course. This is a comprehensive project based course where you will learn step by step on how to build predictive models for employee retention, performance assessment, and promotion eligibility using Random Forest, XGBoost, and LightGBM. This course is a perfect combination between machine learning and HR analytics, making it an ideal opportunity to level up your data science skills while improving your technical knowledge in human resource management. The course will be mainly focusing on three major aspects, the first one is data analysis where you will explore the HR dataset from various angles, the second one is predictive modeling where you will learn how to build HR predictive models using machine learning, and the third one is to evaluate the accuracy and performance of the model. In the introduction session, you will learn the basic fundamentals of human resources analytics, such as getting to know predictive modeling use cases in human resources, getting to know more about machine learning models that will be used, and you will also learn about technical challenges and limitations in HR analytics. Then, in the next section, you will learn how the HR predictive model works. This section will cover data collection, data preprocessing, feature selection, splitting the data into training and testing sets, model selection, model training, making predictions based on training data, and model evaluation. Afterward, you will also learn about several factors that contribute to an employee's performance and turnover rate, for example like job satisfaction, work life balance, career development opportunities, working environment, benefits, and compensations. Once you have learnt all necessary knowledge about HR analytics, we will start the project. Firstly you will be guided step by step on how to set up Google Colab IDE. In addition to that, you will also learn how to find and download HR dataset from Kaggle. Once everything is ready, we wil