Hyperparameter tuning courses can help you learn techniques for optimizing model performance, understanding overfitting and underfitting, and applying cross-validation methods. You can build skills in parameter selection, grid search, and random search strategies to enhance your machine learning projects. Many courses introduce tools like Scikit-learn, TensorFlow, and Keras, showing how to implement these tuning techniques effectively in artificial intelligence and AI applications.