Kursens beskrivning

LEARNING OUTCOMES

At the end of this course, the student can

• describe the main algebraic methods used in data science
• apply these methods
• recognize problems in data science that can be solved using algebraic methods

Credits: 5

Schedule: 13.01.2023 - 14.04.2023

Teacher in charge (valid for whole curriculum period):

Teacher in charge (applies in this implementation): Kaie Kubjas

Contact information for the course (applies in this implementation):

CEFR level (valid for whole curriculum period):

Language of instruction and studies (applies in this implementation):

Teaching language: English. Languages of study attainment: English

CONTENT, ASSESSMENT AND WORKLOAD

Content

• valid for whole curriculum period:

  The contents of this course include the following topics:

  • Numerical algebraic geometry
  • Matrix and tensor decompositions
  • Topological data analysis
  • Graphical models

  Time permitting further topics will be considered. 

Assessment Methods and Criteria

• valid for whole curriculum period:

  Teaching methods: lectures and exercises

  Assessment methods: homework and final project

Workload

• valid for whole curriculum period:

  Contact hours 36h, self-study ca 96h

DETAILS

Substitutes for Courses

• valid for whole curriculum period:

  Substitutes for Courses

Prerequisites

• valid for whole curriculum period:

  Prerequisites

FURTHER INFORMATION

Further Information

• valid for whole curriculum period:

  Teaching Language : English

  Teaching Period : 2022-2023 Autumn III - IV
  2023-2024 No teaching

  Enrollment :

  Sisu (sisu.aalto.fi)

Beskrivning