DATA - Data Science

This course provides an interdisciplinary introduction to data analytics and visualization. Students will solve practical data science problems, analyze datasets, and create effective data visualizations for storytelling and decision support. Standard analytical methods and visualization tools commonly used in research, government, and private sector contexts will be used to explore how data-related facts can be communicated to reveal or challenge common misconceptions. Ethical topics, including data imbalance, under- and over-representation, cultural sensitivity, and misrepresentation, will be introduced.

This course equips students with a foundational understanding of statistical concepts essential to data science and AI. Topics include exploratory data analysis, hypothesis testing, probability theory, the impact of biased or incomplete datasets, and statistical inference, with an emphasis on supporting evidence-based decision-making in research, policy, and professional environments. Students will gain hands-on experience with statistical software tools and programming libraries to address real-world data problems.

This course introduces students from all disciplines to essential data science techniques and AI tools, enabling them to transform ideas into impactful analyses. Students will gain practical skills in programming, data visualization, and ethical AI usage, preparing them to apply these competencies across various fields and professional contexts.