Statistics: Data Mining and Visualization

Course · 7.5 credits


With rapid advances in information technology, we have witnessed an explosive growth in our capabilities to generate and collect data in the last decade. How to analyse huge bodies of data so that they can be understood and used efficiently remains a challenging problem.

Data mining is a collection of more universal methods that address this problem by providing techniques and software to automate the analysis and exploration of large complex data sets. Research on data mining has been pursued by researchers in a wide variety of fields, including statistics, machine learning, database management and data visualization. This is an emerging and rapidly developing field that requires understanding both established method and newly adopted techniques.

Course Content

This course on data mining and visualization covers methodology, major programming tools and applications in this field. By introducing principal ideas in statistical learning, the course helps you to understand methods in data mining and computational aspects of algorithm implementation. To make an algorithm efficient for handling very large scale data sets, issues such as algorithm scalability need to be carefully analysed. Data mining and learning techniques developed in fields other than statistics, e.g., machine learning and signal processing, will also be introduced. The course also explores the question of what visualization is, and why one should use visualizations for quantitative data.

You are required to work on projects to practce applying existing software and to a certain extent, developing their own algorithms. Classes are provided in three forms: lecture, project discussion, and special topic survey. Project discussion will enable you to share and compare ideas with other students and to receive specific guidance from the instructors. Efforts will be made to help you formulate real-world problems into mathematical models so that suitable algorithms can be applied with consideration of computational constraints.

By surveying special topics, you will be exposed growing range of new methodologies. In particular, basics for classification and clustering, e.g., linear classification methods, prototype methods, decision trees, and hidden Markov models, are introduced. Roughly five course lab sessions are included with emphasis on understanding and using existing learning algorithms. You will be encouraged to bring to discussion your own research problems with potential applications of data mining methods. Possible topics include image segmentation and image retrieval; text search, link analysis, and microarray data analysis. Lab sessions focus on providing practice using real-world data.

More information can be found at

Closed for applications

Application opportunities


Department of Statistics

Visiting address
Tycho Brahes väg 1, 223 63 Lund

Postal address
Box 7080, 220 07 Lund

+46 46 222 89 21

Pierre Carbonnier

Study advisor

+46 46 222 89 06

pierre [dot] carbonnier [at] stat [dot] lu [dot] se

Requirements and selection

Entry requirements

90 hp (ECTS) in Statistics

Selection criteria

Seats are allocated according to: Previous college/university studies (APAV): 100 %.

English language requirements

Most of Lund University’s programmes require English Level 6 (unless otherwise stated under 'Entry requirements'). This is the equivalent of an overall IELTS score of 6.5 or a TOEFL score of 90. There are several ways to prove your English language proficiency – check which proof is accepted at the University Admissions in Sweden website. All students must prove they meet English language requirements by the deadline, in order to be considered for admission.

Country-specific requirements

Check if there are any country-specific eligibility rules for you to study Master's studies or Bachelor's studies in Sweden.


Study Options

There are no open applications at the moment.

How to apply

Lund University uses a national application system run by University Admissions in Sweden. It is only possible to apply during the application periods.

Step 1: Apply online

  • Check that you meet the entry requirements of the programme or course you are interested in (refer to the section above on this webpage).
  • Start your application – go to where you create an account and select programmes/courses, during the application period.
  • Rank your programme/course choices in order of preference and submit them before the application deadline.

Step 2: Submit documents

  • Read about how to document your eligibility and how to submit your documents at Follow any country-specific document rules for Master's studies or Bachelor's studies.
  • Get all your documents ready: official transcripts and high school diploma (Bachelor's applicants), official transcripts and degree certificate or proof of expected graduation (Master's applicants), passport/ID and proof of English proficiency (all applicants).
  • Prepare programme-specific documents if stated in the adjacent column on this webpage.
  • Upload or send all required documents to University Admissions before the document deadline.
  • Pay the application fee (if applicable – refer to the section below on this webpage) before the document deadline.

*Note that the process is different if you are applying as an exchange student or as a part of a cooperation programme (such as Erasmus +).
*If you have studied your entire Bachelor's programme in Sweden and all of your academic credits are in Ladok, you do not have to submit transcripts or your diploma when applying for a Master's programme. However, there may still be other documents you need to submit! See the link below. 

*Svensk student? Läs instruktionerna om att söka till ett internationellt masterprogram på

Tuition fees

Non-EU/EEA citizens

Full programme/course tuition fee: SEK 15 000

First payment: SEK 15 000

Convert currency

Citizens of a country outside of the European Union (EU), the European Economic Area (EEA) and Switzerland are required to pay tuition fees. You pay one instalment of the tuition fee in advance of each semester.

Read more about tuition fees, payments and exemptions

EU/EEA citizens and Switzerland

There are no tuition fees for citizens of the European Union (EU), the European Economic Area (EEA) and Switzerland.

Application fee

If you are required to pay tuition fees, you are generally also required to pay an application fee of SEK 900 (approximately EUR 100) when you apply at You pay one application fee regardless of how many programmes or courses you apply to.

Read more about paying the University Admissions in Sweden application fee and exemptions on the University Admissions website.

*Note that there are no tuition or application fees for exchange students or PhD students, regardless of their nationality.

Scholarships & funding

Lund University Global Scholarship programme

The Lund University Global Scholarship programme is a merit-based and selective scholarship targeted at top academic students from countries outside the EU/EEA.

Lund University Global Scholarship

Swedish Institute Scholarships

The Swedish Institute offers scholarships to international students applying for studies in Sweden at Bachelor's, Master's, PhD and post-doctoral levels.

Scholarship options at the Swedish Institute website

Country-specific scholarships and funding options

Lund University has agreements with scholarship organisations and funding bodies in different countries, which may allow applicants to apply for funding or scholarships in their home countries for their studies at Lund University.

External scholarships

Information about scholarships from external organisations