This course intends to introduce special topics of current trends in data science and. Topics covered in this course should be approved by the department council. These topics cover a range of foundational, intermediate, and advanced topics to provide students with a comprehensive understanding of the field of data science. Such possible topics include: feature engineering, time series analysis, natural language processing (NLP), big data technologies, incorporating tools like Spark, Hadoop, and transformer-based models such as BERT and GPT, explainable AI (XAI), causal inference, reinforcement learning, sustainability-focused data science, geospatial analysis.