Prospectus

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Data Science

Course
2024-2025

Admission requirements

Required course(s):

None.

Description

Data Science is an interdisciplinary field that applies methods and techniques to extract insights and drive decision-making from data. It is a rapidly growing and exciting area with applications across numerous domains, including business, technology, social sciences, environmental studies, and more. Data science helps us understand patterns, predict outcomes, and inform strategies to solve complex problems in diverse fields.

In this course, we will learn the fundamentals of data science, including the data science roadmap, the theoretical background, and the basic skills to use programming tools such as Python and R. We will explore different types of data, articulate coherent and complete research questions, design and interpret data queries, and communicate findings effectively. No previous programming experience is required for this course. Students will be guided step by step to use programming for data science from the ground up. This course will equip students with the knowledge and skills to apply data science techniques to solve real-world problems and create value in various sectors.

Course Objectives

By the end of this course, students will be able to:

Knowledge:

  • Demonstrate an understanding of key terminology and concepts related to data science, such as data types, data sources, data analysis, data visualization, and data ethics.

  • Demonstrate an understanding of how to apply data science methods and techniques to solve real-world problems with data.

Skills:

  • Develop and carry out a scientifically sound data science project, from defining a research question and collecting data to performing data analysis and reporting results.

  • Effectively demonstrate scientific and technical skills related to data science topics, such as data cleaning, data exploration, data modeling, and data communication.

  • Effectively demonstrate critical thinking and problem-solving skills related to data science topics.

Timetable

Timetables for courses offered at Leiden University College in 2024-2025 will be published on this page of the e-Prospectus.

Mode of instruction

This course focuses on both the theoretical ideas underpinning how data science works and the practical skills needed to apply data science. To this end, the course will combine in-person classroom lectures to introduce key concepts and skills with hands-on exercises, assignments, and projects that allow students to apply the material in practice.

Assessment Method

  • Participation in class 10%

  • 3 assignments (15% each) 45%

  • Final exam 15%

  • Final project 30%

Reading list

Literature and reading materials will be announced during the course.

Registration

Courses offered at Leiden University College (LUC) are usually only open to LUC students and LUC exchange students. Leiden University students who participate in one of the university’s Honours tracks or programmes may register for one LUC course, if availability permits. Registration is coordinated by the Education Coordinator, course.administration@luc.leidenuniv.nl.

Contact

Dr. Joy Lee, j.y.lee@luc.leidenuniv.nl

Remarks

It is assumed that students have no previous computer programming experience.