Machine Learning With TensorFlow

Tuesday 4 - 5:45 pm // Get hands-on experience in applying machine learning techniques with TensorFlow.



The course will be online. With confirming your participation we will send you a Zoom-Link to join the course.  

For students the participation is for free. For employees we charge a participation fee of 200€.

Your Background
You already have some programming knowledge and are interested in getting hands-on knowledge in how to train and use machine learning algorithms.

The Course Content
This course is based on the online Coursera Specialization "TensorFlow in Practice" provided by The instructors are Andrew Ng and Laurence Moroney. Andrew Ng was founding lead of the Google Brain Team and is a professor in computer science at Stanford University. Laurence Moroney is an AI developer at Google and author of a large variety of books.

The course will provide you with an introduction to machine learning and deep learning, teach you about computer vision using convolutional neural networks, natural language processing, and how to solve time series and forecasting problems. You will then apply the newly aquired knowledge to implement your own machine learning project in a team.

How It Works
The course will take place every Tuesday from 4 pm to 5:45 pm.

Before the first meeting there will be a semesterkick-off.

During the week you will be expected to work through the assigned online course content, which will take you between 3 to 5 hours each week, open questions considering the course content and possible additional implications will then be discussed in the weekly offline course on Tuesday. Towards the end of the semester you will then work in a team on your own machine learning project.
All needed software and online course content is free. For the practical assignments in the online course, however, it will be necessary to create a Google account.

The Formalities
In order to receive a certificate of attendance for this course, active participation is expected, and no more than two classes may be missed. The active participation is proven by screenshots of your taken online courses, the final presentation of your project by you and your team, and the delivery of a documented project source code.
The same conditions also apply in order to receive credit points.

Further details may be given in the course and here.

If you want to learn more about your Mentor, check out this link:


Machine Learning With TensorFlow
digital via Zoom
Wintersemester 2020/2021


Steffen Brandt