Data Science

Course description Data Science
Year: 2017-2018
Catalog number: 4609HCDS5
Teacher(s):
  • Dr. A.J. Knobbe
  • Dr. M. van Leeuwen
Language: English
Blackboard: No
EC: 5
Level: 400
Period: Semester 2, Block III, IV
  • No Elective choice
  • No Contractonderwijs
  • No Exchange
  • No Study Abroad
  • No Evening course
  • No A la Carte
  • Yes Honours Class

Admission requirements

This course is an Honours Class and therefore only available to students of the Honours College. There are a few places available for regular students.

Because of substantial overlap, this class is only open to Computer Science students after permission of the course coordinator Judith Havelaar: j.havelaar@liacs.leidenuniv.nl

Description

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 Judith Havelaar: j.havelaar@liacs.leidenuniv.nl

Course objectives

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

Timetable

Monday 5, 12, 19, 26 February, 5, 12, 19, 26 March; 16.00-18.00hrs. Final session: Monday 14 May: 16.00-20.00hrs.

Location

Old Observatory, Leiden. Room c006 except for the final session. The final session will take place in room c104.

Programme

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

Course Load

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

Assessment method

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

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.

Reading list

Recommended literature: to be announced.

Obligatory: the papers specified in blackboard beforehand and during the lectures.

Registration

Enrolling in this course is possible from Monday November 6th until Thursday November 16th through the Honours Academy, via this link

Please note: We definitely advise Computing Science students against registering for this course, because this Honours Class overlaps with courses in their regular programme.

Contact

Judith Havelaar

Languages