Introduction to Data Science
Course Code: Y1A4
ECTS Credits: 5.0
Course Description
This course offers an introductory exploration of data science through the lens of the CRISP-DM (Cross Industry Standard Process for Data Mining) framework. Students will apply each phase of the CRISP-DM process while developing a Power BI dashboard focused on a Sustainable Development Goal (SDG) or goals of their choice. The course begins with formulating a research question and problem statement, emphasizing how to define the scope of inquiry—narrowing overly broad topics or expanding overly narrow ones. Students will then learn how to identify credible data sources, collect relevant data, and recognize various data formats. Key data preparation skills will be developed, including cleaning techniques and introductory data analysis. Students will use tools like Excel to perform descriptive statistics and explore patterns in the data. Next, students will learn how to create effective visualizations using Power BI, gaining insight into the appropriate use of different chart types based on data and context. They will interpret their visualizations to draw meaningful conclusions, identify limitations, and propose future directions for their research. The course concludes with a focus on communication and presentation skills, culminating in a final demonstration where students present their dashboards and insights to their peers.
Course Content
- Introduction to the data science process
- Framing and refining research questions & problem statements
- Sourcing, cleaning, and preparing real-world data
- Exploratory data analysis and interpretation
- Visualizing and communicating data insights
- Creating interactive dashboards or visual reports
- Presenting results to stakeholders
Prerequisites
- None
Recommended Reading
- None