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Data Science with Python

Winter University Online: January 3rd - 28th, 2022

6 ECTS credit points, max. 24 participants

Registration Deadline: December 20th, 2021

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Overview

This course will focus on Data Science with Python, starting with the basic of Python programming and machine learning algorithms to solving arbitrary complex models using graphical Bayesian modelling and sampling.

Learning Goals and Syllabus

Learning Goals:

Code in Python with Jupyter Notebooks

  • Use popular libraries such as Numpy, Pandas, Matplotlib etc. in Python
  • Manipulate and visualize data in Python
  • Do object orientated coding in Python
  • Run exploratory analysis on data and gain new insights
  • Implement simple Machine Learning algorithms

 

Course Structure:

Reading week: January 3rd - 7th, 2022. Flexible, 10 hours preparatory work to be done on-demand.

Online course: January 10th - 28th, 2022. Estimated session times are Mondays through Fridays from 9 am to 2 pm CET for live lectures and group sessions.

Please note that exact session times will be confirmed once registrations have closed (sessions will be scheduled according to the time zones of the registered course participants).

Should you have any questions regarding the course timetable, please contact us at

Please note this is a full-time, intensive course and participants will be expected to attend lectures and/or complete independent study Monday through Friday. Additional study may also be required on weekends.

 

Syllabus:

A detailed syllabus with information on the schedule will be made available to registered participants.

You may find the syllabus useful when discussing with your home university whether the ECTS credits attainable for this course are accepted by them.

 

Course Components:

  • Live lectures
  • Independent assignments
  • Webinars for assignments discussion and solutions
  • Independent projects
  • Webinars for project discussion/tutoring
  • Online tests

Target Audience

This course is designed for current university students, working professionals and any individuals interested in knowing how to apply machine learning techniques in order to do data analysis efficiently with Python programming language.

Participants from all fields and disciplines are welcome.

Prerequisites and Technical Requirements

Participants of the TU Berlin Summer & Winter University must meet the following requirements: (i) B2 level English, or equivalent and (ii) at least one year of university experience. Working professionals are also welcome to take part in the program.

Basic programming knowledge is also required for this course. Students should be able to write and run small programs in the language of their choice. Students should also have basic knowledge in linear algebra and statistics/probability theory and know what loops, conditionals, methods/functions, libraries, vectors, matrices, gradient and probability distributions are.

  • Linear algebra
  • Calculus
  • Elements of probability theory
  • Basic programming knowledge

Technical Requirements

We will ask participants to fulfil the following technical requirements:

  • Fully functional device (laptop, tablet, PC)
  • Stable internet connection
  • Software: Zoom (App installed on desktop or over browser. Participants are requested to use their real name as zoom account name)
  • Recommended: external headset for better sound quality

Lecturer(s)

Sergej Dogadov is a Teaching Assistant at TU Berlin in the department for Intelligent Data Analysis and Machine Learning with more then five years of teaching experience.

He holds B.S. and M.S. degrees in computer science from the TU Berlin, with a focus on intelligent systems and theoretical informatics.

His current research interests are Bayesian methods, probabilistic neural networks, explainable AI and joint energy models.

Course fees

Course fees for Data Science with Python are as follows:

*Please register here*

Student: 980 Euro

Working professional/Non-student: 1460 Euro

The early bird discount is available for all participants until November 1st 2021.

Please note that students will be required to upload proof of their student status (student card/ enrolment information) during the registration process.

Winter University Online: January 3rd - 28th, 2022

6 ECTS credit points

Zusatzinformationen / Extras

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Contact

TU Berlin Summer & Winter University
+49 30 4472 0230