This course is an (extracurricular) Honours Class: an honours elective in the Honours College programme. There are limited spots available for non honours students. Admission will be based on motivation.
***Because of substantial overlap, this class is only open to Computer Science students after permission of the course coordinator Esme Caubo: firstname.lastname@example.org ***
Data Science deals with handling, processing, analyzing, interpreting, and extracting knowledge from data, ultimately to derive optimal decisions. Often, the term is associated with the concept of big data, i.e., data that is characterized by large volume, high velocity of generation, and data variety, meaning many different types of information.
Today, data science is of paramount importance in just about any domain, ranging from the life sciences, including e.g. health and biosciences, to banking, insurances, retail, and heavy industries.
The possibilities for generating new insights and decisions based on data are considerable. This Honours Class first introduces students to some of the fundamental concepts of Data Science and then continues with overviews of specific application domains.
Because of substantial overlap, this class is only open to Computer Science students after permission of the course coordinator Esme Caubo: email@example.com
Upon successful completion of this course, students will:
Have a general overview of the possibilities in the field of data science
Have knowledge of different types of data
Be able to understand and perform basic data analysis tasks
Have basic knowledge of some of the tools used in data science
Have developed skills for several tools for analyzing data
Have experience with performing basic analyses for real-world applications
Monday 5, 12, 19, 26 February, 5, 12, 19, 26 March, 9 April; 16.00-18.00hrs. Final session: Monday 14 May: 16.00-20.00hrs.
Old Observatory, Leiden. Room c005 except for the final session. The final session will take place in room c104.
The lectures are a combination of lectures and hands-on sessions with different tools:
During the first 4 sessions students are introduced into the field of Data Science: What is data science and why is it important? Which techniques are being used? What different kinds of data do we distinguish? How is Data Science related to statistics?
Lectures 1 to 4:
1. General Introduction
2. Classification and Regression
3. Clustering & Outlier Detection
4. Pattern Mining & Data Science in Society
In the five following lectures, guest lecturers with different backgrounds will go over several fields of application. In the final session every students will present his/her paper.
**Lectures 5 to 10: **
5. Data Science & Social Sciences
6. (Social) Network Analysis
7. Recommender Systems and Search Engines
8. Text Mining and Natural Language Processing
9. Data Science & Life Sciences
10. Final seminar with student presentations, discussions and dinner
This course is worth 5 EC, which means the total course load equals 140 hours.
Lectures: 9 lectures of 2 hours
Seminars: 1 seminars of 4 hours
Literature reading & practical work: on average 6,5 hours a week
Final essay, reviews and presentation: 60 hours
The final grade will be composed from the following aspects:
25% presentation (5 minutes) during final seminar
50% paper (3000 words) about one of the subareas
25% double open peer review of two student papers from other subareas
Presence is obligatory. Students missing more than two lectures will not be able to fulfill the requirements of this course.
Blackboard will be used in this course. From December 2017 and on the course materials will be uploaded.
Please note: students are not required to register through uSis for the Honours Classes. Your registration will be done centrally.
Recommended literature: to be announced.
Obligatory: the papers specified in blackboard beforehand and during the lectures.
Enrolling in this course is possible from Monday November 6th until Thursday November 16th 23.59 hrs through the Honours Academy, via this link. It is not necessary to register in uSis.
Please note: We definitely advise Computing Science students against registering for this course, because this Honours Class overlaps with courses in their regular programme.