Recently, fairness has emerged as a matter of concern within machine learning applications. There have been instances of unintended discrimination that arises as a result if using black box machine learning algorithms to drive decision making. We will provide a brief overview of some common biases that can manifest in the training data and equip you with strategies to identify them and evaluate their effects.