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CM1001 Applied Machine Learning and Data Mining 7.5 credits

This course deals with how to process and draw conclusions of data through mining and machine learning. The course introduces some theory on machine learning, but focuses mainly on current applied methods.

Choose semester and course offering

Choose semester and course offering to see current information and more about the course, such as course syllabus, study period, and application information.

Application

For course offering

Spring 2025 Start 14 Jan 2025 programme students

Application code

60586

Headings with content from the Course syllabus CM1001 (Autumn 2020–) are denoted with an asterisk ( )

Content and learning outcomes

Course contents

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Intended learning outcomes

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Literature and preparations

Specific prerequisites

Följande slutförda kurser: HF1006, Linjär algebra och analys; HF1012, Matematisk statistik; HI1024 Programmering, grundkurs

Recommended prerequisites

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Equipment

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Literature

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Examination and completion

If the course is discontinued, students may request to be examined during the following two academic years.

Grading scale

A, B, C, D, E, FX, F

Examination

  • LAB1 - Practial assignments, 5.0 credits, grading scale: A, B, C, D, E, FX, F
  • RED1 - Accounting, 2.5 credits, grading scale: P, F

Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.

The examiner may apply another examination format when re-examining individual students.

Opportunity to complete the requirements via supplementary examination

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Opportunity to raise an approved grade via renewed examination

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Examiner

Ethical approach

  • All members of a group are responsible for the group's work.
  • In any assessment, every student shall honestly disclose any help received and sources used.
  • In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.

Further information

Course room in Canvas

Registered students find further information about the implementation of the course in the course room in Canvas. A link to the course room can be found under the tab Studies in the Personal menu at the start of the course.

Offered by

Main field of study

Technology

Education cycle

First cycle

Add-on studies

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Contact

Jayanth Raghothama (jayanthr@kth.se)