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  2. 2019/20 fall
  3. Introduction to Data Science (LTAT.02.002)
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Introduction to Data Science 2019/20 fall

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  • Lectures
  • Practice sessions
  • Homeworks
  • Projects
  • Projects from 2018
  • Call for Data
  • Tutorials
  • Dictionary ENG-EST

Lectures

Lecture 01 - Sept 5 - Introduction

Slides part 1, slides part 2, video

Lecture 02 - Sept 12 - First look at the data

Slides part 1, slides part 2, video

Lecture 03 - Sept 19 - Tableau and visualisation

Video 1, video 2

Lecture 04 - Sept 26 - Frequent pattern mining

Slides, video

Lecture 05 - Oct 3 - Relations of attributes, clustering and dimensionality reduction

Slides part 1, slides part 2, video 1, video 2

Lecture 06 - Oct 10 - Introduction to machine learning

Slides part 1, Slides part 2, video

Lecture 07 - Oct 17 - Machine learning 2

Slides, video

Lecture 08 - Oct 24 - Machine learning 3

Slides, video

Lecture 09 - Oct 31 - Machine learning 4 + Project information

Slides, video

Project information slides, video

Nov 7 - Consultation for projects (same room and time as the lecture)

Lecture 10 - Nov 14 - Computational statistics

Slides part 1, slides part 2, video part 1, video part 2

Lecture 11 - Nov 21 - CRISP-DM, Graph mining, and NLP

Slides part 1, slides part 2, video

Lecture 12 - Nov 28 - Databases and privacy

Slides part 1, slides part 2, video

Dec 5 - Consultation for projects and consultation for exam (same room and time as the lecture)

Dec 12 - No lecture

Dec 19 - Poster session in the atrium of Paabel (Ülikooli 17) at 14:00-17:00

  • Institute of Computer Science
  • Faculty of Science and Technology
  • University of Tartu
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