Lectures and Material

GENERAL INFORMATION

  • Time: Thursdays, 10:00 – 11:30 (lecture), 11:30 – 13:00 (exercises)
  • Location: Room 235, Appelstraße 4 (building 3703)
  • Start: 17.10.2019
  • Language: English
  • Exam: Tuesday, 10.03.2020, 11:00-13:00 (Room MZ1 and MZ2 in Appelstraße 9a, building 3408)

LECTURES & RESOURCES

Preliminary lecture schedule

Lecture 1 – Course Overview

Lecture 2 – Programming Languages for Data Science

  • Date: 24.10.2019
  • Time: 10:00 – 11:30
  • Exercises: 11:30 – 13:00

Lecture 3 – Statistics for Data Science

  • Date: 07.11.2019
  • Time: 10:00 – 11:30
  • Exercises: 11:30 – 13:00

Lecture 4 – Exploratory Data Analysis

  • Date: 14.11.2019
  • Time: 10:00 – 11:30
  • Exercises: 11:30 – 13:00

Lecture 5 – Obtaining, Integrating & Cleaning Data

  • Date: 21.11.2019
  • Time: 10:00 – 11:30
  • Exercises: 11:30 – 13:00

Lecture 6 – Machine Learning

  • Date: 28.11.2019
  • Time: 10:00 – 11:30
  • Exercises: 11:30 – 13:00

Lecture 7 – Reinforcement Learning (Guest Lecture by Dr. Daniel Kudenko)

  • Date: 05.12.2019
  • Time: 10:00 – 11:30
  • Exercises: 11:30 – 13:00

Lecture 8 – Time Series Analysis

  • Date: 12.12.2019
  • Time: 10:00 – 11:30
  • Exercises: 11:30 – 13:00

Lecture 9 –  Big Data Analytics

  • Date: 19.12.2019
  • Time: 10:00 – 11:30
  • Exercises: 11:30 – 13:00

Lecture 10 – Deep Learning (Part I)

  • Date: 09.01.2020
  • Time: 10:00 – 11:30
  • Exercises: 11:30 – 13:00

Lecture 11 – Visual Analytics (Guest Lecture by Prof. Dr. Ralph Ewerth)

  • Date: 16.01.2020
  • Time: 10:00 – 11:30
  • Exercises: 11:30 – 13:00

Lecture 12 – Deep Learning (Part II)

  • Date: 23.01.2020
  • Time: 10:00 – 11:30
  • Exercises: 11:30 – 13:00

Lecture 13 – Q&A

  • Date: 30.01.2020
  • Time: 10:00 – 13:00