Data Mining I

5 credits

Course, Master's level, 1DL360

Expand the information below to show details on how to apply and entry requirements.

Location
Uppsala
Pace of study
33%
Teaching form
On-campus
Instructional time
Daytime
Study period
2 September 2024–3 November 2024
Language of instruction
English
Entry requirements

120 credits with 25 credits in mathematics, including mathematical statistics, 45 credits in computer science and/or engineering, including Database Design I and a second course in computer programming. Algorithms and Data Structures I is recommended. Proficiency in English equivalent to the Swedish upper secondary course English 6.

Selection

Higher education credits in science and engineering (maximum 240 credits)

Fees
If you are not a citizen of a European Union (EU) or European Economic Area (EEA) country, or Switzerland, you are required to pay application and tuition fees.
  • First tuition fee instalment: SEK 12,083
  • Total tuition fee: SEK 12,083

Read more about fees.

Application deadline
15 April 2024
Application code
UU-11031

Admitted or on the waiting list?

Registration period
26 July 2024–9 September 2024
Information on registration from the department

Location
Uppsala
Pace of study
33%
Teaching form
On-campus
Instructional time
Daytime
Study period
2 September 2024–3 November 2024
Language of instruction
English
Entry requirements

120 credits with 25 credits in mathematics, including mathematical statistics, 45 credits in computer science and/or engineering, including Database Design I and a second course in computer programming. Algorithms and Data Structures I is recommended. Proficiency in English equivalent to the Swedish upper secondary course English 6.

Admitted or on the waiting list?

Registration period
26 July 2024–9 September 2024
Information on registration from the department

Expand the information below to show details on how to apply and entry requirements.

Location
Uppsala
Pace of study
33%
Teaching form
On-campus
Instructional time
Daytime
Study period
1 September 2025–2 November 2025
Language of instruction
English
Entry requirements

120 credits with 25 credits in mathematics, including mathematical statistics, 45 credits in computer science and/or engineering, including Database Design I and a second course in computer programming. Algorithms and Data Structures I is recommended. Proficiency in English equivalent to the Swedish upper secondary course English 6.

Selection

Higher education credits in science and engineering (maximum 240 credits)

Fees
If you are not a citizen of a European Union (EU) or European Economic Area (EEA) country, or Switzerland, you are required to pay application and tuition fees.
  • First tuition fee instalment: SEK 12,083
  • Total tuition fee: SEK 12,083

Read more about fees.

Application deadline
15 April 2025
Application code
UU-11031

Admitted or on the waiting list?

Registration period
25 July 2025–7 September 2025
Information on registration from the department

Location
Uppsala
Pace of study
33%
Teaching form
On-campus
Instructional time
Daytime
Study period
1 September 2025–2 November 2025
Language of instruction
English
Entry requirements

120 credits with 25 credits in mathematics, including mathematical statistics, 45 credits in computer science and/or engineering, including Database Design I and a second course in computer programming. Algorithms and Data Structures I is recommended. Proficiency in English equivalent to the Swedish upper secondary course English 6.

Admitted or on the waiting list?

Registration period
25 July 2025–7 September 2025
Information on registration from the department

About the course

Data mining studies effective methods to find interesting patterns in large data sets. Applications can be found in biotechnology, telecom, commerce, and the internet. This course introduces the terminology, an overview of the various kinds of data and their properties, and classification and clustering methods. Furthermore, it treats data on the web, search engines and personal integrity. Techniques from databases, statistics, machine learning and information retrieval are combined.

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