This course provided a comprehensive and thoughtful introduction to Big Data, Artificial Intelligence, and research ethics, with a strong emphasis on real‑world implications. One of the key strengths of the course was how it connected technical concepts—such as data collection, AI decision‑making, and NLP—to social, ethical, and policy concerns. This helped move beyond a purely technical understanding and highlighted why responsible use of AI matters.
The discussions on digital footprints, bias, transparency, and fairness were particularly impactful. They challenged the assumption that data and algorithms are neutral and showed how historical data can reinforce inequality if ethical considerations are ignored. Case studies and examples made abstract ethical principles easier to understand and relevant to modern applications like hiring, healthcare, education, and governance.