Introduction to Data Science

Content:

Data science is a rapidly developing field with numerous application areas. In this course you will learn basic tools of data science. You will also become familiar with advanced methods involving deep learning and their practical applications. In the first part of the course you will get an introduction to fundamental statistical methods underpinning data science. You will also learn techniques for analyzing and visualizing datasets of different modalities like text, images and tabular. You will dive deep into data-driven prediction methods from machine learning and deep learning. In the final parts of the course we will introduce you to advanced topics, including recent progress in large language modelling and use of data-driven decision making in a trustworthy manner.

Learning Outcomes:

At the end of this course, you would be familiar with:

  1. Key contemporary methods for data-driven prediction
  2. Methods for processing, exploring and visualizing data of different modalities like image, text and tabular
  3. Building proof-of-concept code bases for solving real-world data science problems
  4. Issues around trust and potential remedies in applications of data science
Learning Methods:

Each session of the course consists of a lecture part, introducing the theoretical concepts, and a practical part, providing you with hands-on experience using Jupyter Notebooks.

Exam:

Written final module examination of 120 minutes

Lecturers

Details

Course type
Lectures
Credits
5
Term
Winter Term 2024/2025
E-Learning
moodle course available

Dates

Lecture
Takes place every week on Tuesday from 08:30 to 10:00 in room ND 3/99.
First appointment is on 08.10.2024
Last appointment is on 28.01.2025
Exercise
Takes place every week on Tuesday from 10:15 to 11:45 in room ND 3/99.
First appointment is on 08.10.2024
Last appointment is on 28.01.2025

Requirements

Basic knowledge of calculus, linear algebra and programming in Python

About the INI

The Institut für Neuroinformatik (INI) is a central research unit of the Ruhr-Universität Bochum. We aim to understand the fundamental principles through which organisms generate behavior and cognition while linked to their environments through sensory systems and while acting in those environments through effector systems. Inspired by our insights into such natural cognitive systems, we seek new solutions to problems of information processing in artificial cognitive systems. We draw from a variety of disciplines that include experimental approaches from psychology and neurophysiology as well as theoretical approaches from physics, mathematics, electrical engineering and applied computer science, in particular machine learning, artificial intelligence, and computer vision.

Contact

Universitätsstr. 150, Building NB, Room 3/32
D-44801 Bochum, Germany

Tel: (+49) 234 32-28967
Fax: (+49) 234 32-14210

sekretariat@ini.rub.de
www.ini.rub.de