Data Mining I
Course, Master's level, 1DL360
Autumn 2023 Autumn 2023, Uppsala, 33%, On-campus, English
- Location
- Uppsala
- Pace of study
- 33%
- Teaching form
- On-campus
- Instructional time
- Daytime
- Study period
- 28 August 2023–30 October 2023
- 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.
- Application fee: SEK 900
- First tuition fee instalment: SEK 12,083
- Total tuition fee: SEK 12,083
- Application deadline
- 17 April 2023
- Application code
- UU-11031
Admitted or on the waiting list?
- Registration period
- 28 July 2023–4 September 2023
- Information on registration.
Autumn 2023 Autumn 2023, Uppsala, 33%, On-campus, English For exchange students
- Location
- Uppsala
- Pace of study
- 33%
- Teaching form
- On-campus
- Instructional time
- Daytime
- Study period
- 28 August 2023–30 October 2023
- 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
- 28 July 2023–4 September 2023
- Information on registration.
Autumn 2024 Autumn 2024, Uppsala, 33%, On-campus, English
- 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.
- Application fee: SEK 900
- First tuition fee instalment: SEK 12,083
- Total tuition fee: SEK 12,083
- 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.
Autumn 2024 Autumn 2024, Uppsala, 33%, On-campus, English For exchange students
- 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.
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.
Reading list
- Reading list valid from Autumn 2024
- Reading list valid from Autumn 2022
- Reading list valid from Autumn 2020
- Reading list valid from Autumn 2019, version 2
- Reading list valid from Autumn 2019, version 1
- Reading list valid from Spring 2019
- Reading list valid from Autumn 2015
- Reading list valid from Autumn 2010