This series explores the crucial role of ethics in data science, covering a range of aspects from data collection to decision-making frameworks. The first post highlights the importance of ethics in data science and its impact on individuals, organizations, and society. The second post delves into ethical considerations of data collection, including informed consent and responsible data use. The third post delves into the challenges of bias and fairness in data science, addressing algorithmic fairness and discrimination. The fourth post emphasizes the need for transparency and accountability in data science practices. The final post examines ethical decision-making frameworks to guide data scientists in addressing moral dilemmas.